Day Dispatch Strategy for Integrated System Based on Time-frequency Scales of PWP

Abstract A day dispatch strategy for the integrated system (IS) of wind/photovoltaic/pumped-storage/gas-turbine-power/energy-storage plant is proposed in this paper based on the time-frequency scales of power of wind/photovoltaic (PWP). Based on the day-ahead dispatch strategy, the day dispatch optimization model of the IS is first established, and then according to the patulous short-time prediction (PSP) and ultra-short-time prediction (UP) of PWP, the day rolling and real-time scheduling strategies are put forward based on the time-frequency scales of PWP. Finally, the cone programming method is applied to optimize the day dispatch schedule. Simulation results show that the proposed strategy can compensate for the error in the day-ahead dispatch strategy based on short-time prediction (SP) of PWP. Thus, as an important supplement to the day-ahead dispatch strategy, this method is proved to be an effective solution to the power fluctuation problem in large-scale wind/photovoltaic integration, realizing a smooth power output, as well as guaranteeing the economical, efficient, and environmentally friendly operation of the system.

[1]  Lisa Turner,et al.  Applications of Second Order Cone Programming , 2012 .

[2]  Lu Zhang,et al.  Optimal sizing study of hybrid wind/PV/diesel power generation unit , 2011 .

[3]  T. Sasaki,et al.  Study on load frequency control using redox flow batteries , 2004, IEEE Transactions on Power Systems.

[4]  T. Kulworawanichpong,et al.  Impact of energy storage in micro-grid systems with DGs , 2010, 2010 International Conference on Power System Technology.

[5]  Yong,et al.  Composition Modeling and Equivalence of an Integrated Power Generation System of Wind, Photovoltaic and Energy Storage Unit , 2011 .

[6]  A. J. Urdaneta,et al.  A Hybrid Particle Swarm Optimization for Distribution State Estimation , 2002, IEEE Power Engineering Review.

[7]  Donald Goldfarb,et al.  Second-order cone programming , 2003, Math. Program..

[8]  Yang Xu-sheng Research Status and Development Trend of Smart Grid , 2009 .

[9]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[10]  R. P. Kumudini Devi,et al.  Fast computation evolutionary programming algorithm for the economic dispatch problem , 2006 .

[11]  Liu Shun-gui EXTENDED SHORT-TERM LOAD FORECASTING PRINCIPLE AND METHOD , 2003 .

[12]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[13]  Erling D. Andersen,et al.  On implementing a primal-dual interior-point method for conic quadratic optimization , 2003, Math. Program..

[14]  Taher Niknam,et al.  A new particle swarm optimization for non-convex economic dispatch , 2011 .

[15]  J. A. Carta,et al.  Technical–economic analysis of wind-powered pumped hydrostorage systems. Part I: model development , 2005 .

[16]  Djamila Diaf,et al.  A methodology for optimal sizing of autonomous hybrid PV/wind system , 2007 .

[17]  Lu Hua-yong Research on Energy Shifting Benefits of Hybrid Wind Power and Pumped Hydro Storage System Considering Peak-Valley Electricity Price , 2009 .

[18]  J. A. Carta,et al.  Technical-economic analysis of wind-powered pumped hydrostorage systems. Part II: Model application to the island of El Hierro , 2005 .

[19]  Ying-Yi Hong,et al.  Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm , 2012, IEEE Transactions on Power Delivery.

[20]  Chao-Lung Chiang,et al.  New approach with a genetic algorithm framework to multi-objective generation dispatch problems , 2005 .

[21]  Lu Jun-jie Research on Optimal Operation Mode of Power Generation System Doubly Driven by Wind Power and Hydraulic Power Based on Equal Incremental Rate Criterion , 2008 .