Title: Multi-objective evaluation of wind power acceptable capacity based on statistical characterisation
Authors: Shuangxin Wang; Yinan Zhao; Meng Li
Addresses: School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China ' School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China ' School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China
Abstract: The contribution of wind power to the availability of generating capacity becomes more important with increasing wind penetration. This paper presents a multi-objective evaluation of the acceptable capacity of wind power. A partitioning method which can adaptively divide the forecast power range into various regions according to its historical data is firstly proposed. Then, the multi-objective optimisation model of power system integrated with wind is constructed with objectives of minimum generating cost, minimum pollutant emission and maximum wind power acceptable capacity. By amending the NDX (normal distribution crossover) operator into the binary crossover operator of NSGA2, the improved NSGA2 (named INSGA2) is tested by a benchmark for typical high-dimensional functions, and the simulation results confirmed the feasibility of the developed algorithm. Finally, a case study of IEEE 118 bus system is carried out to verify that the approach is beneficial to deal with the problems of evaluation of stochastic wind acceptance.
Keywords: wind power forecasting; multi-objective optimisation; Pareto solutions; wind power acceptable capacity; statistical characterisation.
International Journal of Computer Applications in Technology, 2018 Vol.58 No.3, pp.184 - 197
Received: 06 Jun 2017
Accepted: 15 Sep 2017
Published online: 18 Oct 2018 *