Marketecture: A Simulation-Based Framework for Studying Experimental Deregulated Power Markets

In this paper, we present MARKETECTURE, an agent-based, microeconomic, scalable model for studying deregulated power markets. Features that distinguish it from previously studied models include: the ability to generate individualistic, demographics based, elastic demand profiles; a highly configurable system that supports different matching algorithms for buyers and sellers, different market clearing mechanisms; ability to aggregate individuals to different classes; an electrical grid to physically clear the economic contracts etc. This paper describes the model and its various features in detail. A case study is done for the city of Portland, Oregon, to evaluate the performance and efficiency of the market under different market clearing algorithms and sellers’ strategies. We analyze the structural properties of the market under different scenarios to validate our model. Our results show that if Vickrey auction clearing mechanism can induce the sellers to reveal their true production costs and bid at competitive level, the market performance can be almost pareto-efficient. The weighted average clearing method in the poolco market results in the lowest market clearing price (MCP). However, the market clearing quantity (MCQ) is also low which results in deadweight loss to the society. Our findings also show that the different orders of market execution (bilateral and poolco) can significantly affect the performance of the markets.