Electricity Market Manipulation: How Behavioral Modeling Can Help Market Design
Electricity Market Manipulation: How Behavioral Modeling Can Help Market Design

Author:

Publisher:

Published: 2015

Total Pages: 0

ISBN-13:

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The question of how to best design electricity markets to integrate variable and uncertain renewable energy resources is becoming increasingly important as more renewable energy is added to electric power systems. Current markets were designed based on a set of assumptions that are not always valid in scenarios of high penetrations of renewables. In a future where renewables might have a larger impact on market mechanisms as well as financial outcomes, there is a need for modeling tools and power system modeling software that can provide policy makers and industry actors with more realistic representations of wholesale markets. One option includes using agent-based modeling frameworks. This paper discusses how key elements of current and future wholesale power markets can be modeled using an agent-based approach and how this approach may become a useful paradigm that researchers can employ when studying and planning for power systems of the future.

Fit for Purpose: Modeling Wholesale Electricity Markets Realistically with Multi-agent Deep Reinforcement Learning
Fit for Purpose: Modeling Wholesale Electricity Markets Realistically with Multi-agent Deep Reinforcement Learning

Author: Nick Harder

Publisher:

Published: 2023

Total Pages: 0

ISBN-13:

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Abstract: Electricity markets need to continuously evolve to address the growing complexity of a predominantly renewable energy-driven, highly interconnected, and sector-integrated energy system. Simulation models allow testing market designs before implementation, which offers advantages for market robustness and efficiency. This work presents a novel approach to simulate the electricity market by using multi-agent deep reinforcement learning for representing revenue-maximizing market participants. The learning capability makes the agents highly adaptive, thereby facilitating a rigorous performance evaluation of market mechanisms under challenging yet practical conditions. Through distinct test cases that vary the number and size of learning agents in an energy-only market, we demonstrate the ability of the proposed method to diagnose market manipulation and reflect market liquidity. Our method is highly scalable, as demonstrated by a case study of the German wholesale energy market with 145 learning agents. This makes the model well-suited for analyzing large and complex electricity markets. The capability of the presented simulation approach facilitates market design analysis, thereby contributing to the establishment future-proof electricity markets to support the energy transition

Strategic Behavior Analysis in Electricity Markets
Strategic Behavior Analysis in Electricity Markets

Author: You Seok Son

Publisher:

Published: 2003

Total Pages: 208

ISBN-13:

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Strategic behaviors in electricity markets are analyzed. Three related topics are investigated. The first topic is a research about the NE search algorithm for complex non-cooperative games in electricity markets with transmission constraints. Hybrid co-evolutionary programming is suggested and simulated for complex examples. The second topic is an analysis about the competing pricing mechanisms of uniform and pay-as-bid pricing in an electricity market. We prove that for a two-player static game the Nash Equilibrium under pay-as-bid pricing will yield less total revenue in expectation than under uniform pricing when demand is inelastic. The third topic is to address a market power mitigation issue of the current Texas electricity market by limiting Transmission Congestion Right (TCR) ownership. The strategic coordination of inter zonal scheduling and balancing market manipulation is analyzed. A market power measurement algorithm useful to determine the proper level of TCR ownership limitation is suggested.

Computational Intelligence Assisted Design
Computational Intelligence Assisted Design

Author: Yi Chen

Publisher: CRC Press

Published: 2018-06-19

Total Pages: 527

ISBN-13: 1498760678

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Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

Building a Better Delivery System
Building a Better Delivery System

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2005-10-20

Total Pages: 277

ISBN-13: 030909643X

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In a joint effort between the National Academy of Engineering and the Institute of Medicine, this books attempts to bridge the knowledge/awareness divide separating health care professionals from their potential partners in systems engineering and related disciplines. The goal of this partnership is to transform the U.S. health care sector from an underperforming conglomerate of independent entities (individual practitioners, small group practices, clinics, hospitals, pharmacies, community health centers et. al.) into a high performance "system" in which every participating unit recognizes its dependence and influence on every other unit. By providing both a framework and action plan for a systems approach to health care delivery based on a partnership between engineers and health care professionals, Building a Better Delivery System describes opportunities and challenges to harness the power of systems-engineering tools, information technologies and complementary knowledge in social sciences, cognitive sciences and business/management to advance the U.S. health care system.