A Review on the Complementarity Modelling in Competitive Electricity Markets

Abstract

In recent years, the ever-increasing research interest in various aspects of the electricity pool-based markets has generated a plethora of complementarity-based approaches to determine participating agents’ optimal offering/bidding strategies and model players’ interactions. In particular, the integration of multiple and diversified market agents, such as conventional generation companies, renewable energy sources, electricity storage facilities and agents with a mixed generation portfolio has instigated significant competition, as each player attempts to establish their market dominance and realize substantial financial benefits. The employment of complementarity modelling approaches can also prove beneficial for the optimal coordination of the electricity and natural gas market coupling. Linear and nonlinear programming as well as complementarity modelling, mainly in the form of mathematical programs with equilibrium constraints (MPECs), equilibrium programs with equilibrium constraints (EPECs) and conjectural variations models (CV) have been widely employed to provide effective market clearing mechanisms, enhance agents’ decision-making process and allow them to exert market power, under perfect and imperfect competition and various market settlements. This work first introduces the theoretical concepts that regulate the majority of contemporary competitive electricity markets. It then presents a comprehensive review of recent advances related to complementarity-based modelling methodologies and their implementation in current competitive electricity pool-based markets applications.

A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies

“…Game-theoretic approaches formulate the competing interests of sellers and buyers as a game and aim to achieve an equilibrium point where both seller and buyer utilities are maximised [15]. A commonly used game-theoretic model is the Stackelberg game, where a prosumer acts like the leader and sets up the prices, while others become followers [16]. Since P2P energy trading problems are associated with maximising the utilities of the prosumers either in terms of profit or cost savings, different optimisation approaches have been undertaken in many existing research studies in P2P energy trading.…”