Multi-agent power market simulation using EMCAS
Multi-agent power market simulation using EMCAS
复制标题
使用 EMCAS 的多主体电力市场模拟
DOI：
10.1109/pes.2005.1489271
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
T. Veselka
中科院分区：
文献类型：
--
作者：
G. Conzelmann;Gale A. Boyd;V. Koritarov;T. Veselka
世界各国继续调整其电力市场，向竞争和私人投资者开放，以追求经济效率和新的资本投资。然而，最近许多重组后的电力市场所表现出的波动性，加上几个突出的市场失灵，突出了需要更好地了解各种市场参与者和新兴的整体市场行为之间的复杂的相互作用。需要先进的建模方法来模拟电力市场随着时间的推移的行为，并模拟市场参与者如何对潜在的经济，金融和监管环境的变化采取行动和反应。这对于制定健全的市场规则，使这些市场能够正常运作特别有用。一种新的和有前途的方法是使用基于代理的建模和仿真方法，如在电力市场复杂自适应系统（EMCAS）软件中实现的复杂自适应系统建模电力市场。EMCAS提供了一个基于代理的框架来捕获和调查物理基础设施和市场参与者的经济行为之间的复杂相互作用，这是新兴市场的商标。本文描述了EMCAS代理，他们的相互作用，从基于代理的模型中获得的独特见解，并讨论了当前模型在几个美国，亚洲和欧洲市场。
Countries around the world continue to restructure their electricity markets and open them up to competition and private investors in pursuit of economic efficiency and new capital investment. However, the recent volatility exhibited by many restructured power markets, in combination with several prominent market failures, have highlighted the need for a better understanding of the complex interactions between the various market participants and the emerging overall market behavior. Advanced modeling approaches are needed that simulate the behavior of electricity markets over time and model how market participants may act and react to changes in the underlying economic, financial, and regulatory environments. This is particularly useful for developing sound market rules that will allow these markets to function properly. A new and promising approach is to model electricity markets as complex adaptive systems using an agent-based modeling and simulation approach, such as is implemented in the electricity market complex adaptive system (EMCAS) software. EMCAS provides an agent-based framework to capture and investigate the complex interactions between the physical infrastructures and the economic behavior of market participants that are a trademark of the newly emerging markets. This paper describes the EMCAS agents, their interactions, the unique insights obtained from agent-based models, and discusses current model applications in several U.S., Asian, and European markets.