Optimal Strategies of Power Generation Companies and Electricity Customers Participating in Electricity Retailing Trading

Abstract

To reform the electricity selling trading and standardize the electricity retail market, the optimal participating strategies of power generation companies and electricity customers in an electricity retail market under the spot electricity market mode are investigated. First, the influence of the external environment on power generation companies is considered, the dispatching sequence of power generation companies is optimized, and the profit models of power generation companies and power retailers, as well as the utility model of electricity customers are built. Second, an improved genetic algorithm (IGA) is applied to solve the formulated optimal participating strategies model for power generation companies and electricity customers, and the effect of IGA is compared with that of traditional genetic algorithm (GA), simulated annealing (SA) algorithm and particle swarm optimization (PSO) algorithm. The simulation results show that the IGA algorithm has the advantages of fast convergence and saving electricity consumption in this paper. Finally, two examples are employed to demonstrate the feasibility and efficiency of the developed strategies. Both example 1 for presented method in this paper and example 2 for multiple retailers competing, the simulation results show that the interests of market competing entities (participants) can be well balanced. Furthermore, the advantages of power retailers acted as a guider in electricity retail market are revealed, and the credibility and security of the electricity market management system are maintained.

Keywords

• Electricity retail market
• real-time pricing
• electricity transaction
• improved genetic algorithm
• optimal strategies