Optimal Bidding Strategies of GENCOs in Day-Ahead Energy and Spinning Reserve Markets Based on Hybrid GA-Heuristic Optimization Algorithm

Subject Areas : International Journal of Smart Electrical Engineering

Mohammad Esmaeil Nazari ¹ , Morteza Mohammad Ardehali ²

1 - Energy System Laboratory, Center of Excellence on Power Systems, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
2 - Energy System Laboratory, Center of Excellence on Power Systems, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

Received: 2017-12-18 Accepted : 2018-01-05 Published : 2017-09-01

Keywords: Genetic Algorithm, bidding strategy, Energy market, Heuristic optimization, Spinning reserve market,

Abstract :

In an electricity market, every generation company (GENCO) attempts to maximize profit according to other participants bidding behaviors and power systems operating conditions. The goal of this study is to examine the optimal bidding strategy problem for GENCOs in energy and spinning reserve markets based on a hybrid GA-heuristic optimization algorithm. The heuristic optimization algorithm used in this study is successfully applied for validation and, it is determined that the heuristic optimization algorithm improves profits of a GENCO by 4.15-47.95% and 20.84-31.30% in single-sided and double-sided auctions, respectively.