Optimal allocation of power supply systems in industrial parks considering multi-energy complementarity and demand response

Industrial Park is one of the important scenarios of distributed generation development. This paper proposes an optimal allocation method of distributed generations and energy storage systems in the planning of power supply systems in industrial parks, considering demand response based on day-ahead real-time pricing (DARTP). In order to overcome the disadvantages of the traditional model such as imbalance of energy shifting and over demand response, this paper develops an improved demand response model with day-ahead real-time pricing. Furthermore, an optimal allocation method of a multi-energy power supply system in industrial park is established, taking minimum total cost as the optimization objective, which is then solved by the hybrid genetic algorithm and pattern search algorithm. Additionally, two important indexes, i.e., the ratio of distributed generation deficiency of energy and the ratio of distributed generation deficiency of hours, are employed to quantitatively analyze the relationship between the complementary characteristic of multi-energy sources and the planning cost. Finally, a case study of one typical power supply system in an industrial park is given to validate the effectiveness of the proposed method. The results show that the total cost of the proposed method is reduced by 3% and 16.7%, compared to the method with the traditional DARTP demand response model and the one without demand response model respectively.