Optimal dispatch of dynamic power and heat considering load management, water pump system, and renewable resources by grasshopper optimization algorithm. (January 2023)

• Record Type: Journal Article
• Authors: Zhang, Liyuan; Guo, Quanxi; Liu, Mengyuan; Yang, Na; Gao, Ruize; Sobhani, Behrouz
• Is Part Of: Journal of energy storage. Volume 57(2023)
• Publication Date: 2023-01
• Subjects: Optimization -- Economic load dispatch -- Nonlinear constraints -- Heating system; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.106166
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: Nowadays, one of the most important issues in a country's power system is to meet the demand for electrical energy. However, an essential aspect of this goal is to minimize production costs. It also must be taken into account that this is a very complicated problem, considering nonlinear constraints and uneven cost function. It should be solved by an optimization method with high reliability that could be implemented easily. Given the non-convex nature of this problem, it will be solved by difficult mathematical methods and a high computational load. In this paper, the economic power dispatch during 24 h/day becomes an optimization problem. In order to create a real problem, load dispatch is modeled considering the heat, renewable, and water resources for demand-side management. Since the proposed model is very complicated, we used the grasshopper optimization algorithm. This algorithm belongs to the group of collective intelligence algorithms and is inspired by the social behavior of grasshoppers and the impact of the environment on each grasshopper. In this algorithm, updating the position of each grasshopper depends on the distance of each grasshopper from the entire population of grasshoppers in the current generation and the position of the best grasshopper. Features of this algorithm include simplicity and having only one adjustable parameter. The simulation results indicated the appropriate effectiveness of load management in a cost. Highlights: Presenting a completed model of economic-emission dispatch by water pump and heating Probabilistic modeling of renewable resources through the dynamic load dispatch Considering demand side management to increase profits and improve load profiles Presenting a modified grasshopper optimization algorithm with a local operator Evaluating the proposed model in different conditions based on numerical criteria