Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework

Abstract

Wholesale power market restructuring, Empirical input validation, Market design, Behavioral economics, Learning, Market power, Agent-based modeling, AMES wholesale power market framework, Java, RepastJ, L1, D8, L9, C6,

Reduction of Market Power and Stabilisation of Outcomes in a Novel and Simplified Two-Settlement Electricity Market

“…First, we define an oligopolistic market scenario with realistic settings from a wholesale power market simulation study by Sun & Tesfatsion (2007) [14]. In [14], several generators and a generic buyer profile are described for 24 hours of a day on an electricity wholesale market.…”

“…In [14], several generators and a generic buyer profile are described for 24 hours of a day on an electricity wholesale market. In particular, the oligopolistic scenario corresponds to hour 8 in that study (we chose hour 8 as it is similar to most other hours and not an outlier).…”

“…We parametrise g as a typical generator, according to [14]. We set c g = 18.8, R g = 0.008 and Q U g = 300.…”

“…The sum of the demand of all buyers in [14] is 900, [8] of several demand responsiveness studies. All studies in [8] measured the price elasticity of demand, which denotes the percentage change in quantity demanded in response to a one percent change in price.…”

“…[6], [1], [14]) mathematical model of bids in electricity markets are supply functions, based on a quadratic representation of total production costs: f (Q) = cQ + RQ n . This makes the assumption that there are no fixed costs.…”