Electricity Market Complex Adaptive System

From Open Energy Information

The Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) has been developing EMCAS, the Electricity Market Complex Adaptive System model, in which the diverse participants in the electricity market are represented as “agents.” All agents have their own set of objectives, decision-making rules, and behavioral patterns. Further, agents can draw on an array of historical information (e.g., past power prices) and projected data (e.g., next-day load) to support their unique decision process.

The Electricity Market Complex Adaptive System (EMCAS) is a software tool for energy analysis from Argonne National Laboratory. EMCAS model uses advanced complexity theory and an agent-based modeling and simulation framework to simulate the most advanced auction-style power markets. EMCAS goes far beyond conventional simulation and optimization techniques with their implicit assumption of a single decision-maker, social welfare optimization, and perfect foresight. These assumptions fail to adequately capture the complex interactions of the various market players that drive today’s advanced electricity markets. Rather, EMCAS allows the representation of diverse market participants or “agents.” All agents have their own set of objectives they try to maximize, decision-making rules, risk preferences, and behavioral patterns. Furthermore, as the simulation progresses, EMCAS agents learn from the success or failure of previous efforts and adapt their behavior when future opportunities arise. [1]


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