Stochastic Unit Commitment and Optimal Allocation of Reserves: A Hybrid Decomposition Approach

The unit commitment is still a widely studied problem, especially when more renewable energy of stochastic character is being added to power systems. This paper proposes a model for weekly planning of systems involving hydro, wind, and thermal energy under a stochastic perspective. The proposed model follows the endogenous reserve determination criterion to achieve a simultaneous optimization of energy and reserves considering wind uncertainty, forced outages of equipment, a dc Flow model of the network, and cascaded head sensitive hydro systems, among others. The paper also develops a practical solution methodology based on outer approximation and benders decomposition. Testing has been conducted over four systems, and computational results demonstrate that the proposed model and solution are useful and effective.

[1]  C. Floudas Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications , 1995 .

[2]  Long Zhao,et al.  Robust unit commitment problem with demand response and wind energy , 2012, 2012 IEEE Power and Energy Society General Meeting.

[3]  Xu Andy Sun,et al.  Adaptive Robust Optimization for the Security Constrained Unit Commitment Problem , 2013, IEEE Transactions on Power Systems.

[4]  Chuanwen Jiang,et al.  Coordination of Hydro Units With Wind Power Generation Using Interval Optimization , 2015, IEEE Transactions on Sustainable Energy.

[5]  M.E.P. Maceira,et al.  A Four-Dimensional Model of Hydro Generation for the Short-Term Hydrothermal Dispatch Problem Considering Head and Spillage Effects , 2008, IEEE Transactions on Power Systems.

[6]  A. Vargas,et al.  Short-term hydrothermal coordination considering an AC network modeling , 2007 .

[7]  A. Conejo,et al.  Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures , 2013, IEEE Transactions on Power Systems.

[8]  S. Faias,et al.  Assessment and Optimization of Wind Energy Integration Into the Power Systems: Application to the Portuguese System , 2012, IEEE Transactions on Sustainable Energy.

[9]  Sven Leyffer,et al.  Generalized Outer Approximation , 2009, Encyclopedia of Optimization.

[10]  R. Chakrabarti,et al.  An improved PSO technique for short-term optimal hydrothermal scheduling , 2009 .

[11]  J. Garcia-Gonzalez,et al.  Short-term hydro scheduling with cascaded and head-dependent reservoirs based on mixed-integer linear programming , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[12]  A. Sharaf,et al.  Short term multi-objective hydrothermal scheduling , 2015 .

[13]  Antonio J. Conejo,et al.  Network-Constrained AC Unit Commitment Under Uncertainty: A Benders’ Decomposition Approach , 2016, IEEE Transactions on Power Systems.

[14]  Francisco Alberto Campos Fernández,et al.  Joint energy and reserve markets: current implementations and modeling trends , 2014 .

[15]  Hugh Rudnick,et al.  Short-term hydrothermal generation scheduling model using a genetic algorithm , 2003 .

[16]  Adel M. Sharaf,et al.  Robust hydrothermal scheduling under load uncertainty using information gap decision theory , 2016 .

[17]  A. Conejo,et al.  Market-clearing with stochastic security - part II: case studies , 2006, 2006 IEEE Power Engineering Society General Meeting.

[18]  François Bouffard,et al.  Scheduling and Pricing of Coupled Energy and Primary, Secondary, and Tertiary Reserves , 2005, Proceedings of the IEEE.

[19]  Ignacio E. Grossmann,et al.  An outer-approximation algorithm for a class of mixed-integer nonlinear programs , 1987, Math. Program..

[20]  Nima Amjady,et al.  Hydrothermal unit commitment with AC constraints by a new solution method based on benders decomposition , 2013 .

[21]  Mohammad Shahidehpour,et al.  Optimal reserve allocation and pricing , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[22]  Ruiwei Jiang,et al.  Weekly Two-Stage Robust Generation Scheduling for Hydrothermal Power Systems , 2016, IEEE Transactions on Power Systems.

[23]  Arild Helseth,et al.  A model for optimal scheduling of hydro thermal systems including pumped-storage and wind power , 2013 .

[24]  A. Helseth,et al.  A linear optimal power flow model considering nodal distribution of losses , 2012, 2012 9th International Conference on the European Energy Market.

[25]  Nima Amjady,et al.  Stochastic security-constrained hydrothermal unit commitment considering uncertainty of load forecast, inflows to reservoirs and unavailability of units by a new hybrid decomposition strategy , 2014 .

[26]  Istvan Erlich,et al.  Application of hybrid heuristic optimization algorithms for solving optimal hydrothermal system operation , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[27]  A. Borghetti,et al.  An MILP Approach for Short-Term Hydro Scheduling and Unit Commitment With Head-Dependent Reservoir , 2008, IEEE Transactions on Power Systems.

[28]  Brian W. Kernighan,et al.  AMPL: A Modeling Language for Mathematical Programming , 1993 .

[29]  V.M.F. Mendes,et al.  Scheduling of Head-Sensitive Cascaded Hydro Systems: A Nonlinear Approach , 2009, IEEE Transactions on Power Systems.

[30]  A. Conejo,et al.  Market-clearing with stochastic security-part I: formulation , 2005, IEEE Transactions on Power Systems.

[31]  Danny Pudjianto,et al.  Optimising the scheduling of spinning reserve considering the cost of interruptions , 2006 .

[32]  Antonio J. Conejo,et al.  Self-Scheduling of a Hydro Producer in a Pool-Based Electricity Market , 2002, IEEE Power Engineering Review.