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.

工业园区是分布式发电发展的重要方案之一。本文提出了一种基于工业园区供电系统规划的分布式发电和储能系统最优分配方法，该方法考虑了基于日前实时定价（DARTP）的需求响应。为了克服传统模型的缺点，如能量转移不平衡和需求响应过度，本文开发了一种改进的需求响应模型，该模型具有提前实时定价功能。此外，建立了以最小总成本为优化目标的工业园区多能源供电系统的优化分配方法，并通过混合遗传算法和模式搜索算法进行求解。此外，还有两个重要的指标，即 利用能量的分布式发电不足比例和小时的分布式发电不足比例，定量分析了多能源互补特征与规划成本之间的关系。最后，以某工业园区的典型供电系统为例，验证了该方法的有效性。结果表明，与传统的DARTP需求响应模型和无需求响应模型相比，该方法的总成本分别降低了3％和16.7％。用来定量分析多能源互补特征与规划成本之间的关系。最后，以某工业园区的典型供电系统为例，验证了该方法的有效性。结果表明，与传统的DARTP需求响应模型和无需求响应模型相比，该方法的总成本分别降低了3％和16.7％。用来定量分析多能源互补特征与规划成本之间的关系。最后，以某工业园区的典型供电系统为例，验证了该方法的有效性。结果表明，与传统的DARTP需求响应模型和无需求响应模型相比，该方法的总成本分别降低了3％和16.7％。