Operating Strategies for a GB Integrated Gas and Electricity Network Considering the Uncertainty in Wind Power Forecasts

In many power systems, in particular in Great Britain (GB), significant wind generation is anticipated and gas-fired generation will continue to play an important role. Gas-fired generating units act as a link between the gas and electricity networks. The variability of wind power is, therefore, transferred to the gas network by influencing the gas demand for electricity generation. Operation of a GB integrated gas and electricity network considering the uncertainty in wind power forecast was investigated using three operational planning methods: deterministic, two-stage stochastic programming, and multistage stochastic programming. These methods were benchmarked against a perfect foresight model which has no uncertainty associated with the wind power forecast. In all the methods, thermal generators were controlled through an integrated unit commitment and economic dispatch algorithm that used mixed integer programming. The nonlinear characteristics of the gas network, including the gas flow along pipes and the operation of compressors, were taken into account and the resultant nonlinear problem was solved using successive linear programming. The operational strategies determined by the stochastic programming methods showed reductions of the operational costs compared to the solution of the deterministic method by almost 1%. Also, using the stochastic programming methods to schedule the thermal units was shown to make a better use of pumped storage plants to mitigate the variability and uncertainty of the net demand.

[1]  Dick Duffey,et al.  Power Generation , 1932, Transactions of the American Institute of Electrical Engineers.

[2]  W. Marsden I and J , 2012 .

[3]  K. Kiwiel,et al.  Power management in a hydro-thermal system under uncertainty by Lagrangian relaxation , 2002 .

[4]  Andrzej J. Osiadacz Osiadacz,et al.  Simulation and Analysis of Gas Networks , 1987 .

[5]  Anatoly A. Zhigljavsky,et al.  Singular Spectrum Analysis for Time Series , 2013, International Encyclopedia of Statistical Science.

[6]  M. O'Malley,et al.  Unit Commitment for Systems With Significant Wind Penetration , 2009, IEEE Transactions on Power Systems.

[7]  Smajo Bisanovic,et al.  Unit commitment problem in deregulated environment , 2012 .

[8]  Jianzhong Wu,et al.  Vulnerability analysis of the integrated energy infrastructure , 2009, 2009 44th International Universities Power Engineering Conference (UPEC).

[9]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[10]  Alexander Shapiro,et al.  Lectures on Stochastic Programming: Modeling and Theory , 2009 .

[11]  Tsung-Ying Lee Optimal Spinning Reserve for a Wind-Thermal Power System Using EIPSO , 2007, IEEE Transactions on Power Systems.

[12]  F. Bouffard,et al.  Stochastic security for operations planning with significant wind power generation , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[13]  P. Carpentier,et al.  Stochastic optimization of unit commitment: a new decomposition framework , 1996 .

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

[15]  T. W. Gedra,et al.  Natural gas and electricity optimal power flow , 2003, 2003 IEEE PES Transmission and Distribution Conference and Exposition (IEEE Cat. No.03CH37495).

[16]  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.

[17]  Nicholas Jenkins,et al.  Operation of the 2030 GB power generation system , 2011 .

[18]  X. Wang,et al.  Modern power system planning , 1994 .

[19]  I. Erlich,et al.  A Stochastic Model for the Optimal Operation of a Wind-Thermal Power System , 2009, IEEE Transactions on Power Systems.

[20]  Wei-Jen Lee,et al.  An Integration of ANN Wind Power Estimation Into Unit Commitment Considering the Forecasting Uncertainty , 2007, IEEE Transactions on Industry Applications.

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

[22]  Jianzhong Wu,et al.  Impact of wind variability on GB gas and electricity supply , 2010, 2010 IEEE International Conference on Sustainable Energy Technologies (ICSET).

[23]  Jianzhong Wu,et al.  Impact of a large penetration of wind generation on the GB gas network , 2010 .

[24]  Goran Strbac,et al.  Multi-time period combined gas and electricity network optimisation , 2008 .

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

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