A Joint Optimal Dispatching Method Of Wind-Photovoltaic-Hydro-Gas Generation System

Wind power and solar power generation, as the first choices among new energy resources, are becoming an increasing concern for their contribution to mitigating the problem of fossil fuel crisis and environmental pollution. However, the inherent instability and intermittence of their output become bottle-neck problem of their large-scale development. In power systems including wind power and solar power generation, traditional energy are generally needed to balance the fluctuation of renewable energy. In this paper, cascade hydropower station and gas power station are used to complement wind power and solar power generation because of their characteristics such as stable output and quick response to load change. A combined power generation model including wind power generation, photovoltaic generation, cascade hydropower station and gas power station is built and differential evolution (DE) algorithm is used to work out a scheduling scheme. Main research contents and contributions of this paper are represented as follows:(1) Respective generating characteristics and output models of wind power generation, photovoltaic generation, cascade hydropower station and gas power station are studied, then principle and procedure of standard differential evolution algorithm are presented, making preparation for the following research.(2) A multi-energy power generation energy-saving scheduling model is built, including wind power, photovoltaic generation, hydropower and gas energy. Particularly, wind power and photovoltaic generation are given priority in scheduling. Objectives include minimum gas heat consumption of gas power station and minimum generating flow of hydropower station. Constraints include output constraint, ramping constraint and startup and shutdown frequency constraint of gas power station, storage capacity constraint and generating flow constraint of hydropower station. Pareto optimal solution set is provided by multi-objective differential evolution algorithm and scheduling scheme is obtained using information entropy weight based TOPSIS method. It is proved by the practical example that the proposed scheduling scheme achieves the purpose of saving fuel and decreasing water flow. Meanwhile, hydropower station and gas power station jointly undertake the task of complementing the random output of wind power and photovoltaic generation in this scheduling system.(3) A multi-energy power generation economic dispatch model is built, including wind power, photovoltaic generation, hydropower and gas energy. Considering correlation between wind energy and solar energy, appropriately abandon one or the other. The objective function is to minimize power generation cost which includes fuel costs and fluctuating punishment costs. Clay-Copula function is chosen as the joint probability distribution function of wind power and photovoltaic generation and Spearman correlation coefficient is used to describe their correlation. The energies given priority in scheduling are determined according to the correlation between wind power, photovoltaic power generation and load. Differential evolution algorithm is used to obtain the ultimate scheduling result. It is concluded by comparison that the economics of a system with the consideration of correlation between wind power and photovoltaic generation is better than the economics of a system without this consideration. And the economic advantage of the system is becoming more apparent along with the increase of penalty coefficient.