An optimal approach for smart grid economic dispatch

Smart grid economic dispatch (SGED) is more complicated than the traditional economic dispatch since it involves the operation of the uncertain renewable energy resources, as well as chargeable and dischargeable storage. This paper presents an approach to solve the smart grid economic dispatch problem using a two-stage optimization method. The proposed SGED model contains wind power generation and the storage provider. The first stage involves the fixed wind power generation, which is estimated and also cannot be adjustable. The second stage involves smart grid economic dispatch considering network loss and security constraints, as well as adjustable wind energy, where the wind power generations are variable at some range. Three objectives may be used for the second stage. They are the minimization of the generation cost, the minimization of system loss, and the minimization of the movement of generator output from the first stage generation plans. A modified IEEE 30-bus system, which contains the wind farm and storage device, is used for testing. The test results show the effectiveness of the proposed two stage smart grid economic dispatch approach.

[1]  Jizhong Zhu,et al.  Optimization of Power System Operation , 2009 .

[2]  James A. Momoh,et al.  Improved interior point method for OPF problems , 1999 .

[3]  Ramachandra Kota,et al.  An Agent-Based Approach to Virtual Power Plants of Wind Power Generators and Electric Vehicles , 2013, IEEE Transactions on Smart Grid.

[4]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[5]  R. Piwko,et al.  Wind energy delivery issues [transmission planning and competitive electricity market operation] , 2005, IEEE Power and Energy Magazine.

[6]  T. Lee,et al.  A Transportation Method for Economic Dispatching - Application and Comparison , 1980, IEEE Transactions on Power Apparatus and Systems.

[7]  J. Yuryevich,et al.  Evolutionary-programming-based algorithm for environmentally-constrained economic dispatch , 1998 .

[8]  O. Alsac,et al.  Optimal Load Flow with Steady-State Security , 1974 .

[9]  D. Devaraj,et al.  Optimal Power Flow for Steady state security enhancement using Genetic Algorithm with FACTS devices , 2008, 2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems.

[10]  L. K. Kirchmayer,et al.  Economic Operation of Power Systems , 1958 .

[11]  M. R. Irving,et al.  Economic dispatch of active power with constraint relaxation , 1983 .

[12]  William F. Tinney,et al.  Optimal Power Flow Solutions , 1968 .

[13]  Olle I. Elgerd,et al.  Electric Energy Systems Theory: An Introduction , 1972 .

[14]  Mo-Yuen Chow,et al.  Decentralizing the economic dispatch problem using a two-level incremental cost consensus algorithm in a smart grid environment , 2011, 2011 North American Power Symposium.

[15]  Jong-Bae Park,et al.  An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems , 2010 .

[16]  Jong-Bae Park,et al.  An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems , 2010, IEEE Transactions on Power Systems.

[17]  Jizhong Zhu,et al.  Optimal generation scheduling based on AHP/ANP , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[18]  M. R. Irving,et al.  Combined active and reactive dispatch with multiple objectives using an analytic hierarchical process , 1996 .

[19]  Goran Andersson,et al.  Model Predictive Control of Energy Storage including Uncertain Forecasts , 2011 .

[20]  Zhu Jizhong,et al.  A new economic power dispatch method with security , 1992 .

[21]  Jizhong Zhu Renewable Energy Applications in Power Systems , 2012 .