Containing Small Hydropower and Wind Power System Optimal Spinning Reserve

Abstract:

When larger scale of small hydropower and wind power exist in power system, the traditional reserve capacity algorithm is no longer applicable at the same time of reducing the carbon emission. Aiming at the volatility and non-regulatory of small hydropower and wind power, considering the forecast error of small hydropower, wind power and load,the unit outage rate and other factors, combined with the actual operation parameters of one regional power system in Southwest of China, the wind-hydro – thermal power coordinated operation of multiple objective function optimization calculation model of reserve capacity is established. Using the weighted coefficient method of unified objective method, it transforms the multi-objective optimization problem into a single objective optimization one. Applying the exterior penalty function method, the constrained optimization problem is changed into a non-constrained optimization one. The improved particle swarm optimization algorithm is got by introducing the particle concentration cognition into traditional particle swarm optimization algorithm. The simulation results verify the validity of the model. To Compare them under different strategies, this method can get less fuel expenses of thermal power units in the case of lower loss of load probability (L_OLP).With the small hydropower and wind power output size to optimize the spinning reserve capacity. The model and the algorithm are helpful for drawing up optimization strategies of the reserve capacity in those regions in which larger scale small hydropower and wind power exists.

• Periodical: Applied Mechanics and Materials (Volumes 672-674)
• Pages: 342-350
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.672-674.342
• Online since: October 2014
• Authors: Zhi Jian Liu, Ning Liang*, Dong Dong Wang
• Keywords: Coordination Optimization, Improved Particle Swarm Optimization, Small Hydro Group, Spinning Reserve, Wind Power

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