The Optimal Dispatch of a Power System Containing Virtual Power Plants under Fog and Haze Weather

Yajing Gao, Huaxin Cheng, Jing Zhu, Haifeng Liang and Peng Li
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Yajing Gao: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Huaxin Cheng: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Jing Zhu: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Haifeng Liang: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Peng Li: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China

Sustainability, 2016, vol. 8, issue 1, 1-22

Abstract: With the growing influence of fog and haze (F-H) weather and the rapid development of distributed energy resources (DERs) and smart grids, the concept of the virtual power plant (VPP) employed in this study would help to solve the dispatch problem caused by multiple DERs connected to the power grid. The effects of F-H weather on photovoltaic output forecast, load forecast and power system dispatch are discussed according to real case data. The wavelet neural network (WNN) model was employed to predict photovoltaic output and load, considering F-H weather, based on the idea of “similar days of F-H”. The multi-objective optimal dispatch model of a power system adopted in this paper contains several VPPs and conventional power plants, under F-H weather, and the mixed integer linear programming (MILP) and the Yalmip toolbox of MATLAB were adopted to solve the dispatch model. The analysis of the results from a case study proves the validity and feasibility of the model and the algorithms.

Keywords: fog and haze; virtual power plant; forecast; wavelet neural network; optimal dispatch; mixed integer linear programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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