A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

Yanzhe Hu, Yang Li, Mengjie Xu, Li Zhou and Mingjian Cui
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Yanzhe Hu: Institute of Water Resources and Hydro-electric Engineering, Xi’an University of Technology, Xi’an 710048, China
Yang Li: Institute of Water Resources and Hydro-electric Engineering, Xi’an University of Technology, Xi’an 710048, China
Mengjie Xu: State Grid Shaanxi Economic Research Institue, Xi’an 710065, China
Li Zhou: State Grid Hubei Electric Economics and Technology Research Institute, Wuhan 430077, China
Mingjian Cui: Department of Mechanical Engineering, University of Texas at Dallas, Richardson, TX 75080, USA

Energies, 2017, vol. 10, issue 3, 1-21

Abstract: As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs) to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED) model for the wind-thermal-energy storage system (WTESS) is developed in this paper. An optimization model with the wind power and the energy storage system (ESS) is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG). A Gaussian mixture model (GMM) distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS) is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.

Keywords: economic dispatch; energy storage system; Gaussian mixture model; power system operations; wind power (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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