Peak Operation Problem Solving for Hydropower Reservoirs by Elite-Guide Sine Cosine Algorithm with Gaussian Local Search and Random Mutation

Abstract

In recent years, growing peak pressure is posing a huge challenge for the operators of electrical power systems. As the most important clean renewable energy, hydropower is often advised as a response to the peak loads in China. Thus, a novel hybrid sine cosine algorithm (HSCA) is proposed to deal with the complex peak operation problem of cascade hydropower reservoirs. In HSCA, the elite-guide evolution strategy is embedded into the standard sine cosine algorithm to improve the convergence rate of the swarm. The Gaussian local search strategy is used to increase the diversity of the population. The random mutation operator is adopted to enhance the search capability of the individuals in the evolutionary process. The proposed method is applied to solve the complex peak operation problem of two hydropower systems. The simulations indicate that in different cases, HSCA can generate the scheduling results with higher quality than several benchmark methods. Hence, this paper provides a feasible method for the complex peak operation problem of cascade hydropower reservoirs.

Economic load dispatch using memetic sine cosine algorithm

“… 2019 ; Liu et al. 2019 ; Tawhid and Savsani 2019 ), (ii) hybridized with other population-based algorithms (Nenavath and Jatoth 2018 ; Chegini et al. 2018 ), (iii) hybridized with other operators borrowed from other optimization algorithms (Liu et al.…”

“… 2018 ), (iii) hybridized with other operators borrowed from other optimization algorithms (Liu et al. 2019 ; Gupta and Deep 2019b ), and (iv) modified its operators to be in line with the problem nature (Gupta and Deep 2019a ; Sindhu et al. 2017 ; Long et al.…”

“…In particular, the SCA is integrated with gaussian local search and random mutation in order to enhance the diversity of the population (Liu et al. 2019 ). In Long et al.…”

Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection

“…Firstly, SCA operators have been modified to deal with particular problems [ 60 – 63 ]. Alternatively, SCA has been hybridized with i) local-based algorithms [ 52 , 64 , 65 ], ii) population-based algorithms [ 66 , 67 ], iii) operators from other optimization algorithms [ 65 , 68 ]. For instance, in [ 62 ] the SCA exploration and exploitation phases were managed by a nonlinear conversion parameter.…”

Multi-Objective Operation of Cascade Hydropower Reservoirs Using TOPSIS and Gravitational Search Algorithm with Opposition Learning and Mutation

“…With the merits of low pollution emission and high work efficiency, hydropower is seen as one of the most important renewable energy sources and usually shoulders many different kinds of management requirements, in practice [1][2][3]. For hydropower enterprises, it is preferred to make full use of the water resources to obtain the maximum economic benefit [4]; for power systems, the flexible hydropower generators are often asked to respond to the peak loads and smooth the energy demand curves [5]. Under such a background, the operation optimization of cascade hydropower reservoirs balancing a power generation and peak operation has become one of the most important tasks in both water resource systems and modern power systems [6].…”