Optimal energy management for cooperative microgrids with renewable energy resources

In this paper, we present an optimal energy management framework for a cooperative network of heterogeneous microgrids (MGs) where energy exchange among connected MGs is allowed to exploit the fluctuations of stochastic energy sources and demands. A multi-objective function is introduced that seeks to achieve an efficient tradeoff between low operation cost and good energy service for customers. The objective function captures the total cost of power exchange with the main grid, the startup and shutdown costs, the operating cost of distributed generators (DGs), the payment for demand response load, the penalty costs for involuntary load curtailment, and renewable energy spillage. We propose to employ the scenario-based two-stage stochastic optimization approach to deal with the uncertainties of renewable energy resources and load demand in the energy scheduling problem. The efficacy of the proposed energy management solution is demonstrated via numerical results.

[1]  H. B. Gooi,et al.  Sizing of Energy Storage for Microgrids , 2012, IEEE Transactions on Smart Grid.

[2]  M. Carrion,et al.  A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem , 2006, IEEE Transactions on Power Systems.

[3]  Rodrigo Palma-Behnke,et al.  A Microgrid Energy Management System Based on the Rolling Horizon Strategy , 2013, IEEE Transactions on Smart Grid.

[4]  Jitka Dupacová,et al.  Scenario reduction in stochastic programming , 2003, Math. Program..

[5]  M. Shahidehpour,et al.  Security-Constrained Unit Commitment With Volatile Wind Power Generation , 2008, IEEE Transactions on Power Systems.

[6]  J. Dupacová,et al.  Scenario reduction in stochastic programming: An approach using probability metrics , 2000 .

[7]  Qing-Shan Jia,et al.  Energy-Efficient Buildings Facilitated by Microgrid , 2010, IEEE Transactions on Smart Grid.

[8]  A. Conejo,et al.  Economic Valuation of Reserves in Power Systems With High Penetration of Wind Power , 2009 .

[9]  Suryanarayana Doolla,et al.  Demand Response in Smart Distribution System With Multiple Microgrids , 2012, IEEE Transactions on Smart Grid.

[10]  A.M. Gonzalez,et al.  Stochastic Joint Optimization of Wind Generation and Pumped-Storage Units in an Electricity Market , 2008, IEEE Transactions on Power Systems.

[11]  Mohammad Shahidehpour,et al.  Enhancing the Dispatchability of Variable Wind Generation by Coordination With Pumped-Storage Hydro Units in Stochastic Power Systems , 2013, IEEE Transactions on Power Systems.

[12]  M. Shahidehpour,et al.  Stochastic Security-Constrained Unit Commitment , 2007, IEEE Transactions on Power Systems.

[13]  Yongpei Guan,et al.  A Chance-Constrained Two-Stage Stochastic Program for Unit Commitment With Uncertain Wind Power Output , 2012 .

[14]  Shaghayegh Bahramirad,et al.  Reliability-Constrained Optimal Sizing of Energy Storage System in a Microgrid , 2012, IEEE Transactions on Smart Grid.

[15]  Soon-Ryul Nam,et al.  Power Scheduling of Distributed Generators for Economic and Stable Operation of a Microgrid , 2013, IEEE Transactions on Smart Grid.

[16]  Qing-Shan Jia,et al.  Energy efficient buildings facilitated by micro grid , 2010, PES 2010.