ACE Research Area:
Agent-Based Electricity Market Research
Table of Contents
The U.S. electricity industry is currently undergoing substantial changes in both its structure (ownership and technology aspects) and its architecture (operational and oversight aspects). These changes involve attempts to move the industry away from highly regulated markets with administered cost-based pricing and towards competitive markets in which prices more fully reflect supply and demand forces. The goal of these changes is to provide industry participants with better incentives to control costs and introduce innovations. The process of enacting and implementing policies and laws to bring about these changes has come to be known as restructuring.
This restructuring process has been controversial. The meltdown in the restructured California wholesale power market in the summer of 2000 has shown what can happen when market designs are implemented without sufficient pre-testing. Following the California crisis, many energy researchers have eloquently argued the need to combine sound physical understanding of electric power and transmission grid operation with economic analysis of incentives in order to develop electricity markets with good real-world performance characteristics.
The goal of this resource site is to encourage the study of restructured electricity systems from a perspective that adequately addresses both economic and engineering concerns. In line with this goal, stress is placed on research making use of powerful new
agent-based computational modeling tools.
These tools permit restructured electricity systems to be modeled as commercial networks of strategically interacting traders and regulatory agencies learning to operate through time over realistically rendered transmission grids.
A comprehensive repository of
general resources related to electricity restructuring
is also available.
- Can agent-based test beds function as a bridge between the conceptualization and practical implementation of market designs for electric power systems?
- What form should electricity restructuring take? To what extent should regions be permitted to design their own systems rather than adhere to a centralized design -- e.g., FERC's wholesale power market platform (aka standard market design) in the U.S.?
- How should transmission grid constraints and congestion be properly accounted for in electricity market design? What role might "financial transmission rights" play?
- How important is demand responsiveness for the effective functioning of electricity markets?
- To what extent can strategic participants "game the system" under currently proposed/implemented electricity market designs?
- To what extent should independent system operators and other regulatory agencies intervene in electricity markets in an attempt to mitigate market power and inefficiency problems?
- Are the goals of "market efficiency" and "reliable flow of electricity to consumers" necessarily at odds with each other?
- How can electricity markets be protected against hackers, insider trading, and other illegal disruptive activities as these markets come to depend more heavily on Internet transactions?
Surveys and Overviews
- Massoud Amin, Restructuring the Electric Enterprise: Simulating the
Evolution of the Electric Power Industry with Intelligent Adaptive Agents
Chapter 3 in Market Analysis and Resource Management, edited by A.
Faruqui and K. Eakin, Kluwer Publishers, March 2002.
- Abstract: The author discusses the development of the
Simulator for Electrical Power Industry Agents (SEPIA) sponsored by the
Electric Power Research Institute (EPRI). SEPIA uses autonomous adaptive
agents to represent possible industrial components (e.g., generation units,
transmission system, load) and the corporate entities (e.g., GenCos and
LoadCos) that own these components. Objectives are: (1) to develop a
high-fidelity scenario-free modeling and optimization tool to use for gaining
strategic insight into the operation of the deregulated power industry; (2)
to show how networks of communicating and cooperating intelligent software
agents can be used to adaptively manage complex distributed systems; and (3)
to investigate how collections of agents (agencies) can be used to buy and
sell electricity and participate in the electronic market place and,
ultimately, to create self-optimizing and self-healing capabilities for the
electric power grid and the interconnected critical infrastructures.
- Albert Banal-Estanol and Augusto Rupérez Micola, "Are Agent-Based Simulations Robust? The Wholesale Electricity Trading Case"
Working Paper, March 2010.
The authors explore the consistency of some of the standard techniques used in agent-based computational economics, particularly learning representations, with a special focus on prevailing wholesale electricity trading simulation methods.
Giulia Gallo, "Electricity Market Games: How Agent-Based Modeling can Help under High Penetrations of Variable Generation"
The Electricity Journal 29 (2016), 39-46.
The author explains how key elements of current and anticipated future wholesale electric power markets can be modeled using an agent-based approach. An innovative aspect of her study is her stress on the importance of modeling market participants as strategic decision-makers able to exploit poorly designed market rules for their own advantage.
Eric Guerci, Mohammad Ali Rastegar, and Silvano Cincotti,
"Agent-Based Modeling and Simulation of Competitive Wholesale Electricity Markets",
pp. 241-286 in Handbook of Power Systems II, Springer, 2010.
"This paper sheds light on a promising and very active research area for electricity market modeling, i.e., Agent-Based Computational Economics. The intriguing perspective of such research methodology is to succeed in tackling the complexity of the electricity market structure, thus the fast-growing literature appeared in the last decade on this field. This paper aims to present the state-of-the-art in this field, by studying the evolution and by characterizing the heterogeneity of the research issues, of the modeling assumptions and of the computational techniques adopted by the several research publications reviewed."
Auke Hoekstra, Maarten Steinbuch, and Geert Verbong, Creating Agent-Based Energy Transition Management Models that Can Uncover Profitable Pathways to Climate Change Mitigation
Complexity, Hindawi, Volume 2017, Article ID 1967645, 23pp. https://doi.org/10.1155/2017/1967645
"The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to
climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. ...
The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled.
But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within
the agent-based framework. We conclude with practical guidelines."
Vladimir S. Koritarov, "Real-World Market Representation with Agents"
IEEE Power and Energy Magazine, 2004, 39-46
"The electric power industry around the world is undergoing an extensive restructuring process. In many countries the traditional vertically integrated power utilities are being unbundled and replaced with a number of separate business entities dealing with the generation, transmission, and distribution of electric power. One of the most significant features of the restructuring process is the introduction of electricity markets, aimed at providing competitive electricity service to consumers. As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial, and regulatory environments in which they operate. (This paper argues that a) new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation approach."
- Hongyan Li and Leigh Tesfatsion, "Development of Open Source Software for Power Market Research: The AMES Test Bed"
Journal of Energy Markets, 2(2), Summer 2009, 111-128.
This study discusses potential benefits and drawbacks of developing open-source software for power market research, using the AMES Wholesale Power Market Test Bed for concrete illustration.
Philipp Ringler, Dogan Keles, Wolf Fichtner, "Agent-Based Modelling and Simulation of Smart Electricity Grids and Markets - a Literature Review"
Renewable and Sustainable Energy Reviews 57, 2016, 205-2015.
This paper provides a detailed review of the
literature using agent-based modeling techniques for analysing smart grids from a systems perspective. For that purpose, a general classification of applying agent-based modelling and simulation techniques to electricity systems is provided.
- Frank Sensfuß, Mario Ragwitz, Massimo Genoese, and Dominik Möst, Agent-Based Simulation of Electricity Markets: A Literature Review
Working Paper Sustainability and Innovation, No. S 5/2007, Fraunhofer Institute Systems and Innovation Research, 2007.
- Abstract: "Liberalization, climate policy, and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players, and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets."
Leigh Tesfatsion, "Electric Power Markets in Transition: Agent-Based Modeling Tools for Transactive Energy Support"
Chapter 13 (pp. 715-766) in Cars Hommes and Blake LeBaron (Eds.), Handbook of Computational Economics 4: Heterogeneous Agent Models, Handbooks in Economics Series, North Holland (Elsevier), Amsterdam, the Netherlands, 2018.
Electric power systems consist of large numbers of heterogeneous participants interacting within an intricate layered network of economic and operational relationships. Decision-making in these systems has been extensively decentralized in many industrialized countries over the past twenty years in an attempt to increase their reliability and efficiency. Given the high negative impact of power disruptions, these decentralization efforts have typically been preceded by extensive sensitivity studies with empirically-based computational models. This chapter discusses the current and potential use of agent-based computational modeling to develop novel transactive energy system (TES) designs for electric power systems. TES designs are decentralized market-based designs that permit electric power systems to operate more fully in accordance with basic economic principles while maintaining overall system reliability and efficiency.
- Leigh Tesfatsion, "Auction Basics for Wholesale Power Markets: Objectives and Pricing Rules"
Proceedings of the IEEE Power and Energy Society General Meeting 2011, Calgary, Alberta, CA, July 26-30, 2009 (electronic). Last Updated: February 2011.
- Abstract: Power systems have distinctive features that greatly complicate the development of auction designs. This study reviews the theory and practice of auction design as it relates specifically to U.S. restructured wholesale power markets, i.e., centrally-administered wholesale power markets with congestion managed by locational marginal prices. Basic auction concepts such as reservation value, net seller surplus, net buyer surplus, competitive market clearing, market efficiency, market pricing rules, supply offers, demand bids, strategic capacity withholding, and market power are explained and illustrated. Complicating factors specific to wholesale power markets are clarified, and recent advances in computational tools designed to address these complications are briefly noted.
- Quynh Chi Trinh, Marcelo Saguan, and Leonardo Meeus, "Experience with Electricity Market Test Suite: Students Versus Computational Agents"
IEEE Transactions on Power Systems, Vol. 28, No. 1, Feb. 2013, 112-120.
- Abstract: This paper applies two experimental economics methods (i.e., agent-based modeling and laboratory experiment) to a market test suite that is based on a fictional European wholesale electricity market. Quantitative results of generators’ strategic behavior in this market context are separated between generators played by human subjects (i.e., master students) in a laboratory experiment and generators represented by computational agents in an agent-based model. The behavior is measured through offers that students or agents make when participating in the electricity trading auction and the market outcomes under both methods are discussed in order to illustrate the difference between the behavior of human and computational agents (and to attempt to explain why the computational agents outperform the human subjects). The paper also identifies the improvements that would need to be made to the market test suite to allow for a more conclusive comparison in future experiments.
- Anke Weidlich and Daniel Veit, "A Critical Survey of Agent-Based Wholesale Electricity Market Models"
Energy Economics, 30(4), July 2008, 1728-1759.
- Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."
- Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments"
Proceedings of the IEEE Power Engineering Society General Meeting 2006, Montreal, June 2006 (electronic).
- Abstract: "Power industry restructuring continues
to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These
policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based
computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."
- Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research"
Proceedings of the 7th International Power Engineering Conference (IPEC) 2005.
- Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."
- Zhi Zhou, Wai Kin Chan, and Joe H. Chow, "Agent-Based Simulation of Electricity Markets: A Survey of Tools"
Artificial Intelligence Review, Volume 28, 2007, 305-342.
- Abstract: "Agent-based simulation has been a popular technique in modeling and analyzing electricity markets in recent years. Themain objective of this paper is to study existing agentbased simulation packages for electricity markets.We first provide an overview of electricity markets and briefly introduce the agent-based simulation technique.We then investigate several general-purpose agent-based simulation tools. Next, we review four popular agent-based
simulation packages developed for electricity markets and several agent-based simulation models reported in the literature. We compare all the reviewed packages and models and identify their common features and design issues. Based on the study, we describe an agentbased
simulation framework for electricity markets to facilitate the development of future models for electricity markets."
- Anthony J. Bagnall and George D. Smith, "A Multi-Agent Model of the UK Market in Electricity Generation"
IEEE Transactions on Evolutionary Computation 9(5), 2005, 522-536.
- Abstract: This paper describes an agent-based computational economics approach for studying the effect of alternative structures and mechanisms on behavior in a simulated model of the pre-NETA England and Wales electricity market. Agents learn using hierarchical learning classifier systems. The authors test to see whether the agents: (a) are able to learn optimal strategies when competing against non-adaptive agents; (b) are able to learn strategies observable in the real world when competing against other adaptive agents; and (c) are able to evolve cooperative behaviors without explicit communication.
- Swathi Battula, Leigh Tesfatsion, and Thomas E. McDermott, "An ERCOT Test System for Market Design Studies"
Applied Energy, Vol. 275, October, 2020. DOI:10.1016/j.apenergy.2020.115182/
An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over high-voltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unfirmed wind and solar power. Users can configure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modified or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multiple seamed energy regions or integrated transmission and distribution systems. Detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.
- John Bower and Derek Bunn, "Experimental Analysis of the Efficiency of Uniform-Price versus Discriminatory Auctions in the England and Wales Electricity Market", Journal of Economic Dynamics and Control Volume 25, March 2001, 561-592.
- Abstract: The authors develop an agent-based
computational model of the wholesale market for electricity in England and Wales that allows them to compare market prices and the bidding strategies of individual generators under different trading arrangements. The authors use this framework to address several restructing issues under debate for the England and Wales market -- in particular, the efficacy of using a uniform-price versus a discriminatory-price auction format.
- Derek W. Bunn and Fernando S. Oliveira, "Agent-Based Simulation: An Application to the New Electricity Trading Arrangements of England and Wales", IEEE Transactions on Evolutionary Computation, Volume 5, Number 5, October 2001, 493-503.
- Abstract: This paper presents a large-scale application of a multi-agent evolutonary model of the proposed New Electricity Trading Arrangements (NETA) in the United Kingdom. The model is a detailed plant-by-plant model with an active specification of the demand side of the market. The model was able to provide pricing and strategic insights into the workings of the NETA prior to its actual introduction.
- Derek W. Bunn and Fernando S. Oliveira, "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation"
Annals of Operations Research Volume 121, Numbers 1-4, 2003,
- Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.
Chengrui Cai, Pedram Jahangiri, Auswin George Thomas, Huan Zhao, Dionysios C. Aliprantis, and Leigh Tesfatsion, "Agent-Based Simulation of Distribution Systems with High Penetration of Photovoltaic Generation"
Proceedings of the IEEE Power and Energy Society General Meeting 2011, Detroit, MI, 2011 (electronic).
This paper discusses the development of an agent-based test bed
permitting the integrated study of retail and wholesale power markets operating over realistically rendered transmission and distribution systems. A key issue to be addressed using this test bed is the dynamic effect of increased penetration of consumer-owned distributed energy resources, such as PV generation, particularly when coupled with increased price-sensitivity of demand as realized through demand response, demand dispatch, and/or price-sensitive demand bidding.
- H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation
IEEE Transactions on Power Systems, 21(1), February 2006, 143-152.
- Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation for oligopoly electricity markets
modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle
by conventional methods.
- Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure"
Proceedings of the 38th Hawaii International Conference on System Sciences 2005.
- Abstract: This paper describes experiments using
computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Other work by the same two authors using agent-based tools includes
EPRI Report 1007733 on automatic mitigation procedures
and EPRI Report 1007755 on available capacity market designs
both reports focusing on the California electricity market.
- Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers"
IEEE preprint, downloaded 5/11/05.
- Abstract: The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.
Eric Guerci and Mohammad Ali Rastegar, "From Uniform Auction to Discriminatory Auction: Assessment of the Restructuring Proposal for the Italian Electricity Day-Ahead Market"
EUI RSCAS working paper (RSCAS_2009_69), 2009.
"In the context of the 2009 debate on reforming the Italian market, a realistic agent-based computational model of the day-ahead market session of the Italian wholesale electricity market is simulated to compare market performances between uniform-price and pay-as-bid clearing mechanisms. An empirical validation of computational results at a macro-level is performed to test for accuracy of simulated outcomes with historical ones. The level of prices are accurately reproduced except for few peak hours. As far as concerns pay-as-bid auction, the computational experiments point out that it results in higher market prices than the uniform-price auction. In the pay-as-bid mechanism, sellers’ endeavours to maximize their profits are more costly thus leading to higher price levels."
Pedram Jahangiri, Di Wu, Wanning Li, Dionysios C. Aliprantis, and Leigh Tesfatsion, Development of an Agent-Based Distribution Test Feeder with Smart-Grid Functionality
Proceedings of the IEEE Power and Energy Society General Meeting 2012, San Diego, CA, July 22-26, 2012 (electronic).
This paper reports on the development of an agent-based distribution test feeder with smart-grid functionality. The
test feeder is based on an actual distribution feeder with various
additional features incorporated, including rooftop photovoltaic
generation and price-responsive loads (e.g., plug-in electric vehicles
and intelligent air-conditioning systems). This work aims
to enable the integrated study of wholesale electric power
markets coupled with detailed representations of the retail-side
- Koen Kok, Martin Scheepers, and René Kamphuis, "Intelligence in Electricity Networks for Embedding Renewables and Distributed Generation"
in R.R. Negenborn, Z. Lukszo, and J. Hellendoom, editors, Intelligent Infrastructures, Springer, 2009.
- Abstract: This paper provides a general introduction to
a smart-grid agent-based technology developed by ECN in cooperation with industry and research partners. PowerMatcher permits the intelligent, multi-goal, coordinated management of electrical power systems consisting of commodity markets operating over physical infrastructure.
- Koen Kok et al., "Dynamic Pricing by Scalable Energy Management Systems: Field Experiences and Simulation Results using PowerMatcher"
Proceedings of the IEEE Power and Energy Society General Meeting 2012, San Diego, CA, July 22-27, 2012 (electronic).
In this paper, we describe a smart grid technology that integrates demand and supply flexibility in the operation of the electricity system through the use of dynamic pricing. Over the last few years, this technology has been researched and developed into a market-ready system, and has been deployed in a number of successful field trials. Recent field experiences and simulation studies show the potential of the technology for network operations (e.g. congestion management and black-start support), for market operations (e.g. virtual power plant operations), and integration of large-scale wind power generation.
Dheepak Krishnamurthy, Wanning Li, and Leigh Tesfatsion, "An 8-Zone Test System based on ISO New England Data: Development and Application,"
IEEE Transactions on Power Systems, Vol. 31, Issue 1, January 2016, 234-246.
This study develops an open-source 8-zone test system for teaching, training, and research purposes that is based on ISO New England structural attributes and data. The test system models an ISO-managed wholesale power market populated by a mix of generating companies and load-serving entities that operates through time over an 8-zone AC transmission grid. The modular extensible architecture of the test system permits a wide range of sensitivity studies to be conducted. To illustrate the capabilities of the test system, we report energy cost-savings outcomes for a comparative study of stochastic versus deterministic DAM Security Constrained Unit Commitment (SCUC) formulations under systematically varied reserve requirement levels for the deterministic formulation.
Wanning Li and Leigh Tesfatsion, "An 8-Zone ISO-NE Test System with Physically-Based Wind Power,"
Economics Working Paper No. 17017, Department of Economics, Iowa State University, January 2017.
This study extends the agent-based 8-Zone ISO-NE
Test System to include wind turbine agents, each characterized
by location, physical type, and an output curve mapping local
wind speed into wind power output. Increases in wind power
penetration (WPP) are modeled as build-outs of investment
queues for planned wind turbine installations. The extended
system is used to study the effects of increasing WPP under
both stochastic and deterministic day-ahead market (DAM)
formulations for security-constrained unit commitment (SCUC).
For each tested WPP, the expected cost saving resulting from a
switch from deterministic to stochastic DAM SCUC is found
to display a U-shaped variation as the reserve requirement
(RR) for deterministic DAM SCUC is successively increased.
Moreover, the RR level resulting in the lowest expected cost
saving systematically increases with increases in WPP.
Hongyan Li and Leigh Tesfatsion, "Co-Learning Patterns as Emergent Market Phenomena: An Electricity Market Illustration"
Journal of Economic Behavior and Organization, Vol. 82, Issues 2-3, 2012, 395-419. The published article is available
The definition of emergence remains problematic, particularly for systems with purposeful human interactions. This study explores the practical import of this concept within a specific market context: namely, a double-auction market for wholesale electric power that operates over a transmission grid with spatially located buyers and sellers. Each profit-seeking seller is a learning agent that attempts to adjust its daily supply offers to its best advantage. The sellers are co-learners in the sense that their supply offer adjustments are in response to past market outcomes that reflect the past supply offer choices of all sellers. Attention is focused on the emergence of
co-learning patterns, that is, global market patterns that arise and persist over time as a result of seller co-learning. Examples of co-learning patterns include correlated seller supply offer behaviors and correlated seller net earnings outcomes. Heat maps are used to display and interpret co-learning pattern findings. One key finding is that co-learning strongly matters in this auction market environment. Sellers that behave as Gode-Sunder budget-constrained zero-intelligence agents, randomly selecting their supply offers subject only to a break-even constraint, tend to realize substantially lower net earnings than sellers that tacitly co-learn to correlate their supply offers for market power advantages.
Hongyan Li and Leigh Tesfatsion, "ISO Net Surplus Collection and Allocation in Wholesale Power Markets Under Locational Marginal Pricing"
IEEE Transactions on Power Systems, Vol. 26, Issue 2, 2011, 627-641.
This study uses 5-bus and 30-bus test cases to explore
ISO net surplus (congestion rent) collections and allocations
in wholesale power markets with grid congestion managed by
locational marginal prices (LMPs). Price-sensitivity of demand
and generator learning capabilities are taken as experimental
treatment factors. A key finding is that conditions resulting in
greater generator capacity withholding, hence higher and more
volatile LMPs, also result in greater ISO net surplus collections
that can be substantial in size. A key conclusion is that ISO net
surplus collections should be used pro-actively to mitigate the
conditions encouraging generator capacity withholding and hence
high and volatile LMPs rather than to provide ex post support
for LMP payment offsets and LMP volatility risk hedging as is
currently the norm.
Hongyan Li and Leigh Tesfatsion, "The AMES Wholesale Power Market Test Bed: A Computational Laboratory for Research, Teaching, and Training"
Proceedings of the IEEE Power and Energy Society General Meeting 2009, Calgary, Alberta, CA, July 26-30, 2009 (electronic).
This study reports on the AMES Wholesale Power Market Test Bed (Version 2.02). AMES is an open-source agent-based computational laboratory designed for the systematic study of restructured wholesale power markets operating over AC transmission grids subject to congestion. The AMES traders have learning capabilities permitting them to evolve their trading strategies over time. The potential usefulness of AMES for research, teaching, and training purposes is discussed and illustrated.
- Hongyan Li, Junjie Sun, and Leigh Tesfatsion,
"Testing Institutional Arrangements via Agent-Based Modeling: A U.S. Electricity Markert Example"
pp. 135-158 in H. Dawid and W. Semmler (eds.), Computational Methods in Economic Dynamics, Dynamic Modeling and Econometrics in Economics and Finance 13, Springer-Verlag, Berlin Heidelberg, 2011.
"Many critical goods and services in modern-day economies are produced and distributed through complex institutional arrangements. Agent-based computational economics (ACE) modeling tools are capable of handling this degree of complexity. In concrete support of this claim, this study presents an ACE test bed designed to permit the exploratory study of restructured U.S. wholesale power markets with transmission grid congestion managed by locational marginal prices (LMPs). Illustrative findings are presented showing how spatial LMP
cross-correlation patterns vary systematically in response to changes in the price responsiveness of wholesale power demand when wholesale power sellers have learning capabilities. These findings highlight several distinctive features of ACE modeling: namely, an emphasis on process rather than on equilibrium; an ability to capture complicated structural, institutional, and behavioural real-world aspects (miccro-validation); and an ability to study the effects of changes in these aspects on spatial and temporal outcome distributions."
- Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets"
ISU Economics Working Paper #09009, June 2009.
This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.
- Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets"
presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
- Abstract: EMCAS (Electricity Market Complex Adaptive Systems) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.
- Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding"
IEEE Transactions on Power Systems 22(1), February 2007, 85-95.
- Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes
like Herfindahl–Hirschmann index and Lerner index and two
new indices, quantity modulated price index (QMPI) and revenue-
based market power index (RMPI), which are developed in
this paper. The proposed RL-based methodology is tested on a
- James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing"
IEEE Transactions on Evolutionary
Computation, Vol. 5, No. 5, October 2001, pp. 504-523.
(pdf with colored figures,162KB),
- Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of
buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.
- Hyungna Oh and Timothy D. Mount, "Using Software Agents to Supplement Tests Conducted by Human Subjects", pp. 29-56 in H. Dawid and W. Semmler (eds.), Computational Methods in Economic Dynamics, Dynamic Modeling and Econometrics in Economics and Finance 13, Springer-Verlag, Berlin Heidelberg, 2011.
"The objective of this paper is to test whether or not software agents can match the observed behavior of human subjects in laboratory tests of markets. For this purpose, one set of tests uses four software agents and two human subjects to represent six suppliers in three different market situations: no forward contracts; fixed price forward contracts; and renewable forward contracts. An identical set of tests is conducted using software agents to represent all suppliers. The results show that software agents were able to replicate the behavior of human subjects effectively in the experiments, and have the potential to be used effectively in testing electricity auctions, doing additional sensitivity tests, and supplementing results obtained using human subjects."
- Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents"
a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2002.
- Abstract: This paper develops an agent-based
computational model to investigate the bidding behavior of generating
companies in a short-term bilateral market. Each generating company is
modelled with specific strategic and operational objectives and bounded
reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).
- Morteza Rahimiyan and Habib Rajabi Mashhadi, "Evaluating the efficiency of divestiture policy in promoting competitiveness using an analytical method and agent-based computational economics"
Energy Policy, Volume 38, 2010, 1588-1595.
Choosing a desired policy for divestiture of dominant firms’ generation assets has been a challenging task and open question for regulatory authority. To deal with this problem, in this paper, an analytical method and agent-based computational economics (ACE) approach are used for ex-ante analysis of divestiture policy in reducing market power.
- Morteza Rahimiyan and Habib Rajabi Mashhadi, "An Adaptive Q-Learning Algorithm Developed for Agent-Based Computational Modeling of Electricity Market" , IEEE Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews, Vol. 40, No. 5 (2010), 547-556.
This study develops a fuzzy Q-learning (FQL) method to model
a power supplier’s strategic bidding behavior in a computational
electricity market. In the simulation framework, the power supplier uses FQL to select its bidding strategy conditional on the supplier's past experiences, risk preferences, and QL learning parameters that are adaptively changing to reflect the supplier's current market power opportunities. The application of the proposed FQL methodology for a power supplier in a multi-area power system shows the performance improvement in comparison to QL with fixed parameters.
- Stephen J. Rassenti, Vernon L. Smith, and
Bart J. Wilson,
"Using Experiments to Inform the Privatization/Deregulation
Movement in Electricity",
The Cato Journal 21 (3), Winter 2002, 515-544.
- Stephen J. Rassenti, Vernon L. Smith, and
Bart J. Wilson,
"Discriminatory Price Auctions in Electricity Markets: Low Volatility at
the Expense of High Price Levels", Journal of Regulatory Economics
23(2), 2003, 109-123.
- Stephen J. Rassenti, Vernon L. Smith, and
Bart J. Wilson,
"Controlling Market Power and Price Spikes in Electricity Networks:
Demand-Side Bidding", Proceedings of the National Academy of
Sciences 100(5), March 4, 2003, 2998-3003.
Gabriel Santos, Tiago Pinto, Hugo Morais, Tiago M. Sousa, Ivo F. Pereira, Ricardo Fernandes, Isabel Praca, Zita Vale, Multi-Agent Simulation of Competitive Electricity Markets: Autonomous Systems Cooperation for European Modeling
Energy Conversion and Management 99, 2015, 387--399.
The authors develop a high-level multi-agent systems (MAS) framework for the simulation of power systems and electricity markets. They also review three specific MAS platforms they have developed for the study of electricity markets: namely, MASCEM (Multi-Agent System for Competitive Electricity Markets); ALBidS (Adaptive Learning strategic Bidding System); and MASGriP (Multi-Agent Smart Grid simulation Platform).
- Steve Silberman, "The Energy Web"
Wired, July 2001.
- Abstract: Silberman provides ideas on how to use
multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."
Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures"
IEEE Computational Intelligence Magazine, 3(4), November 2008, 56-72.
- Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.
- Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework"
Computational Economics, 30(3), 2007, 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
- Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.
Auswin G. Thomas and Leigh Tesfatsion, "Braided Cobwebs: Cautionary Tales for Dynamic Pricing in Retail Electric Power Markets"
IEEE Transactions on Power Systems, 2018, to appear.
Digital Object Identifier: 10.1109/TPWRS.2018.2832471
This study investigates the effects of dynamic-price retail contracting on integrated retail and wholesale (IRW) power market operations. Performance is evaluated by means of carefully defined metrics for system stability and market participant welfare. The study is carried out for an IRW Test Case for which 500 households have price-responsive air-conditioning systems. It is shown that dynamic-price retail contracting can give rise to braided cobweb dynamics consisting of two interwoven cycles for power and price levels exhibiting either stability or instability depending on system conditions. Moreover, even in stable cases, dynamic-price retail contracts generally result in worse welfare outcomes for households than flat-rate retail contracts.
- Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach"
International Journal of Management Science and Engineering Management, 1(2), 2006, 83-97.
- Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition
in the spot market. We develop an agent-based model for simulating the outcomes of such markets.
Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the
suppliers in the spot market, and thus to lower spot energy prices.
Phillip Wild, Paul Bell, and John Foster,
"The Impact of Carbon Pricing on Wholesale Electricity Prices, Carbon Pass-Through Rates and Retail Electricity Tariffs in Australia"
Working Paper, Department of Economics, University of Queensland, April 2012.
- Abstract: "The purpose of this article is to investigate the impact that the introduction of a carbon price signal will have on wholesale electricity prices, carbon-pass-through rates and retail electricity rates in the states making up the Australian National Electricity Market (NEM). In order to assess this, we employ an agent based model of the NEM called the ANEM model which contains many of the salient features of the NEM: intra-state and inter-state transmission branches, regional location of generators and load centres and accommodation of unit commitment features. A DC OPF algorithm is used to determine optimal dispatch of generation plant and wholesale prices within the ANEM model. We utilise ANEM model scenario runs to examine the impact of carbon prices on wholesale prices and carbon passthrough rates. This information is then used to assess the impact on retail electricity tariff rates and shares of cost components making up residential retail tariff rate structures for different states in the NEM."
David Young, Stephen Poletti, Oliver Browne, "Can Agent-Based Models Forecast Spot Prices in Electricity markets?: Evidence from the New Zealand Electricity Market"
Working Paper, Electric Power Research Institute (EPRI), Palo Alto, CA, January 2012.
- Abstract: "Modelling price formation in electricity markets is a notoriously difficult process, due to physical constraints on electricity generation and flow. This difficulty has inspired the recent development of bottom-up agent-based models of electricity markets. While these have proven quite successful in small models, few authors have attempted any validation of their model against real-world data in a more realistic model. In this paper, we take one of the most promising algorithms, the modified Roth and Erev algorithm, and apply it to a 19-node simplification of the New Zealand electricity market. Once key variables such as water storage are accounted for, we show that our model can mimic short-run (weekly) electricity prices at these 19 key nodes quite closely."
- Tao Zhang and William J. Nuggall,
"Evaluating Government's Policies on Promoting Smart
Metering Diffusion in Retail Electricity Markets via
Journal of Production Innovation Management, 28, 2011, 169-186.
"In this paper, we develop an agent-based model of a market game in order to evaluate the effectiveness of the U.K.
government's 2008-2010 policy on promoting smart metering in the U.K. retail electricity market. We break down the
policy into four possible policy options. With the model, we study the impact of the four policy options on the dynamics
of smart metering diffusion and suggest policy implications. The context of the paper is a practical application of agent-based
simulation to the retail electricity market in the United Kingdom. The contributions of the paper are both in the
areas of policymaking for the promotion of innovation diffusion in the electricity market and in methodological use of
agent-based simulation for studying the impact of policies on the dynamics of innovation diffusion."
Software, Toolkits, and Demos
- The following two sites include annotated listings of software for electric power systems research, both commercial and OSS, that could be useful for agent-based electric power market simulations:
ACEGES: Agent-Based Computational Economics of the Global Energy System (Java, Open Source)
- Developed by Vlasios Voudouris, ACEGES is a decision-support tool for energy policy by means of controlled computational experiments. The ACEGES tool is designed to be the foundation for large custom-purpose simulations of the global energy system. The ACEGES tool is written in Java and runs on Windows, Mac OS, and Linux platforms. It is based on a discrete-event multiagent simulation library (MASON), an evolutionary computation toolkit (ECJ), the R project for statistical computing, the GAMLSS framework for statistical modeling of agent behavioral rules, and (in certain specific cases) the Mathematica kernel.
AMES Wholesale Power Market Test Bed (Java/Python, Open Source)
The AMES Wholesale Power Market Test Bed, developed entirely in Java by an interdisciplinary team of researchers at Iowa State University, is a modular and extensible agent-based computational laboratory for studying the dynamic efficiency and reliability of wholesale power markets restructured in accordance with guidelines issued by the U.S. Federal Energy Regulatory Commission.
AMES is an acronym for Agent-based Modeling of Electricity Systems.
AMES models traders with learning capabilities interacting over time in an ISO-managed wholesale power market operating over a transmission grid subject to congestion effects. Congestion on the grid is managed by means of locational marginal prices derived from bid/offer-based optimal power flow solutions.
- AMES is a free open-source tool suitable for research, teaching, and training applications. It is designed for the intensive experimental study of small to medium-sized systems
(2-500 nodes). A graphical user interface permits the creation, modification, analysis and storage of scenarios,
parameter initialization and editing, specification of behavioral rules (e.g. learning methods) for market participants, and output reports through table and chart displays.
Eight-Zone ISO-NE Test System (Java/Python, Open Source)
- A team of researchers at Iowa State University has developed an open source 8-Zone ISO-NE Test System based on structural attributes and data from the ISO New England (ISO-NE). A detailed description of this test system, together with an illustrative test case and a pointer to a code/data repository site, can be found in the following article:
Dheepak Krishnamurthy, Wanning Li, and Leigh Tesfatsion, "An 8-Zone Test System based on ISO New England Data: Development and Application"
IEEE Transactions on Power Systems, Vol. 31, Issue 1, January 2016, 234-246.
EMCAS: Electricity Market Complex
Adaptive System (RePastJ, Commercial)
- The Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) at Argonne National Laboratory has developed the EMCAS (Electricity Market Complex Adaptive System) platform as commercially available software. Diverse decision-making participants in a wholesale electricity market are represented as "agents." Each agent has its own objectives, decision-making rules, and behavioral patterns. Moreover, each agent can draw on an array of historical information (e.g., past power prices) and projected data (e.g., next-day load) to support its own unique decision-making process. EMCAS
is implemented by means of the Recursive Porus Agent Simulation Toolkit (RePast), a Java-based class library designed to facilitate agent-based simulations.
ERCOT Test System (Java/Python, Open Source)
- The ERCOT Test System is an open source test system developed by Iowa State University (ISU) and Pacific Northwest National Laboratory (PNNL) researchers. The test system permits the dynamic modeling of centrally-managed wholesale power markets operating over high-voltage transmission grids.
In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unfirmed wind and solar power. Users can configure a broad variety of parameters to study basic market and grid features under alternative system conditions.
Users can also easily extend the test system's Java/Python software classes to study modified or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems.
Detailed descriptions of this test system together with illustrative 8-bus and 200-bus test cases are provided in the following article, along with a pointer to a code/data repository site:
- Swathi Battula, Leigh Tesfatsion, and Thomas E. McDermott, "An ERCOT Test System for Market Design Studies"
Applied Energy, 2020, to appear.
MASCEM: Multiagent Simulator of Competitive
- Zita Vale and her collaborators at the Polytechnic Institute of Porto, Portugal, have developed MASCEM,
a multi-agent platform for the simulation of
competitive electricity markets.
Abstract from above site: "The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short and medium term simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly."
MATREM: An Agent-Based Simulation Tool
for Electricity Markets (JADE/Jadex)
MATREM (Multi-Agent TRading in Electricity Markets) is an agent-based system that permits users to analyze the behavior and outcomes of electricity markets. MATREM supports a day-ahead market, an intra-day market, and a real-time market. The pricing mechanism is founded on marginal pricing theory; both system marginal pricing and locational marginal pricing are supported. MATREM also supports a bilateral marketplace for negotiating the details of long-term bilateral contracts.
The primary objective of the PowerACE project
(Augsburg University, Germany, 2003-2008) led by Daniel Veit, with key contributions from Anke Weidlich, was to investigate the effects of Europe-wide CO2 emissions trading introduced in 2005. For this purpose, the project participants developed an Agent-based Computational Economics (ACE) simulation platform referred to as PowerACE. The PowerACE platform was implemented using the Recursive Porus Agent Simulation Toolkit (RePast), a Java-based class library designed to facilitate agent-based simulations.
- PowerMatcher is a smart-grid agent-based technology developed by ECN in cooperation with industry and research partners. PowerMatcher permits the intelligent, multi-goal, coordinated management of electrical power systems consisting of commodity markets operating over physical infrastructure.
Annotated list of pointers to
ACE/CAS General Software and Toolkits
Annotated list of pointers to
ACE/CAS Computational Laboratories and Demonstration Software
Related Resource Sites and Groups
General Resources on Electricity Restructuring
An Iowa State University (ISU) research team under the direction of Leigh Tesfatsion and Zhaoyu Wang is undertaking a project titled the
Integrated Transmission and Distribution (ITD) Project.
The primary goal of this ITD project is the development and study of integrated T&D system architectures based on transactive energy system (TES) principles. An agent-based ITD TES Platform has been developed for this purpose.
A group of researchers at the London Metropolitan Business School under the direction of Dr. Vlasios Voudouris has embarked on a project titled the
ACEGES refers to "Agent-based Computational Economics of the Global Energy System." The overall aim of this project is to develop, test, and disseminate an agent-based computational laboratory for the systematic experimental study of the global energy system.
- Steve Widergren and collaborators at the
Pacific Northwest National Laboratory
are using agent-based modeling tools to develop and study transactive energy system (TES) architectures for power systems. TES architectures are decentralized market-based mechanisms that permit electric power systems to operate more fully in accordance with core economic principles while ensuring system reliability.
- A group of researchers at
Sandia National Laboratories
has developed an agent-based simulation laboratory
Next-Generation Agent-Based Economic Laboratory (NABLE) (pdf,170KB)
for analyzing the economic factors, feedbacks, and downstream effects of
infrastructure interdependencies, including (e.g.,) the effects of electric
power outages. NABLE is a revised and restructured version of an earlier
framework developed at Sandia, the Aspen Electricity Enhancement Model
- Raimo P. Hämäläinen (Systems
Analysis Lab, Helsinki University, Finland) has used agent-based modeling tools to explore
energy, natural resources, and environmental issues.
Stress is placed on the use of agent-based modeling tools
as part of a larger process of
among stakeholders and researchers.
Some Early Individual Researchers
(CSIRO Agent-Based Modeling Working Group, Australia): Agent-based
modelling of social, economic, and (bio)physical phenomena; Urban, regional,
and evolutionary economics; Industrial ecology (energy, water, waste, and
(Decision Sciences, London Business School): Business forecasting, decision technology, electricity and energy economics.
(Department of Biophysical and Electronic Engineering, U of Genoa): Development of an agent-based computational framework for the study of electricity markets; Computational market design.
(Department of Industrial and Management Systems, U of South Florida,Tampa): Modeling and Design of Deregulated Electric Power Markets; Impact of Auction Based Pricing in Energy and Financial Transmission Rights (FTR) Markets.
(Department of Electrical and Computer Engineering, Carnegie Mellon
University, Pittsburgh): Agent-based modeling of electricity spot markets;
Large-scale systems modeling and simulation; Power systems control and
pricing algorithms; Critical infrastructures and interdependencies.
(Engineering and Applied Science, U of Wisconsin-Milwaukee): Stochastic optimization; Simulation-based optimization, and game-theoretic modeling.
Augusto Rupérez Micola
(Universitat Pompeu Fabra, Barcelona): Simulation methods; Applied econometrics; Energy markets; European
Gerald B. Sheblé
(EPMT, Inc., Portland, OR): Agent-based
computational modelling of electric power markets; Electric power auction market training simulator; Electric power strategy selector via genetic algorithms; Electric power futures contract market simulator.
(Department of Economics, Iowa State University, Ames, Iowa): Market power
and efficiency in computational electricity markets with auction pricing
mechanisms; Role of learning v. structure in determining outcomes in
restructured electricity markets; Agent-based computational economics.
(Business Administration and Information Systems, University of Mannheim, Germany): Economic and technical coordination
and cooperation in markets for non-storable goods;
E-Business (design of mechanisms for electronic markets); Electricity market design (PowerACE project).
(SAP AG, Germany): Restructured electricity markets; Two-settlement systems; C02 emissions trading systems; German electricity industry; PowerACE; Agent-based computational economics.
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