Short-term electricity planning with increase wind capacity

The variable electricity output of the RES (renewable energy sources) power plants, such as wind and hydropower, is an important challenge for the electricity system managers. This paper addresses the problem of an electricity system supported mainly on hydro, thermal, and wind power plants. A binary mixed integer non-linear optimization model with hourly time step is described. The model is applied to a system close to the Portuguese electricity case assuming demand forecasts for the year 2020. The main objective of this paper was to analyze the impact that different levels of installed wind power can have in the operation of this electricity system, taking into account the hourly and intra-annual variation of the renewable resources, the demand projections and also the technical restriction of thermal power plants. The results confirmed wind power as strategic technology to reduce both the marginal cost and CO2 emissions. According to the simulations run, wind power will not replace hydropower but a decrease of thermal power production is foreseen as more wind power is added to the system. Large wind power scenarios will particularly affect gas power plants performance, reducing both the load level and the number of operating hours.

[1]  Julio Usaola,et al.  Optimal operation of a pumped-storage hydro plant that compensates the imbalances of a wind power pr , 2011 .

[2]  Chao-Lung Chiang,et al.  Optimal economic emission dispatch of hydrothermal power systems , 2007 .

[3]  Belgin Emre Turkay,et al.  A novel differential evolution application to short-term electrical power generation scheduling , 2011 .

[4]  Claudia Kemfert,et al.  Gone with the Wind? Electricity Market Prices and Incentives to Invest in Thermal Power Plants under Increasing Wind Energy Supply , 2009 .

[5]  Benjamin F. Hobbs,et al.  Optimization methods for electric utility resource planning , 1995 .

[6]  A.J. Conejo,et al.  Modeling of start-up and shut-down power trajectories of thermal units , 2004, IEEE Transactions on Power Systems.

[7]  William D'haeseleer,et al.  The actual effect of wind power on overall electricity generation costs and CO2 emissions , 2009 .

[8]  Chongqing Kang,et al.  Thermal generation operating cost variations with wind power integration , 2011, 2011 IEEE Power and Energy Society General Meeting.

[9]  Mark O'Malley,et al.  Base-Load Cycling on a System With Significant Wind Penetration , 2010, IEEE Transactions on Power Systems.

[10]  Tomonobu Senjyu,et al.  A fast technique for unit commitment problem by extended priority list , 2003 .

[11]  B. Hobbs,et al.  Optimal Generation Mix With Short-Term Demand Response and Wind Penetration , 2012, IEEE Transactions on Power Systems.

[12]  A. Bakirtzis,et al.  Optimal Self-Scheduling of a Thermal Producer in Short-Term Electricity Markets by MILP , 2010, IEEE Transactions on Power Systems.

[13]  T. Westerlund,et al.  Solving Pseudo-Convex Mixed Integer Optimization Problems by Cutting Plane Techniques , 2002 .

[14]  Steven Clark,et al.  General Algebraic Modeling System , 2014 .

[15]  Maria Adelaide do Carmo Elias e Silva.  Redes energeticas nacionais , 2012 .

[16]  Mikael Amelin,et al.  The state-of-the-art of the short term hydro power planning with large amount of wind power in the system , 2011, 2011 8th International Conference on the European Energy Market (EEM).

[17]  Joao P. S. Catalao,et al.  Short‐term scheduling of thermal units: emission constraints and trade‐off curves , 2008 .

[18]  T. Niknam,et al.  A new decomposition approach for the thermal unit commitment problem , 2009 .