Optimum day-ahead clearing of energy and reserve markets with wind power generation using anticipated real-time adjustment costs

Abstract

Abstract This paper proposes the market clearing mechanism for a wind–thermal power system, which explicitly, takes into account, the impact of uncertainties in wind power generation in a transparent and realistic manner. The impact of wind power volatility on the energy and spinning reserve market is taken into account. The paper proposes two different market models for the energy and spinning reserve market clearing. One model includes reserve offers from the conventional thermal generators, and another includes reserve offers from both conventional thermal generators and demands. Here, an optimum scheduling strategy is proposed which provides a best-fit day-ahead schedule, which minimizes the both day-ahead and real time adjustment costs, under all possible scenarios in real time. This strategy consists of a genetic algorithm (GA) based scheduling, and a two-point estimate method (2PEM) based probabilistic real time optimal power flow. The simulation for IEEE 30 bus system with GA and 2PEM; and GA and Monte Carlo Simulation (MCS) have been obtained to test the effectiveness of the proposed optimal scheduling strategy.