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.

Highlights

  • The uncertainty and variability of the integration of wind power are presenting more and more challenges to the power system operations [1,2]

  • This paper aims to: (i) develop a chance-constrained economic dispatch (ED) model considering the W-energy storage system (ESS) and the analytical distribution functions of the final wind power generation; (ii) compare the impact of different distribution models on the scheduled wind power generation; and (iii) quantitatively calculate the impact of the ESS on the chance-constrained ED model

  • Line flow capacities of the IEEE 30-bus model test system are listed in Table 1, where the maximum line flow capacities are given by 110% of the corresponding standard value

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Summary

Introduction

The uncertainty and variability of the integration of wind power are presenting more and more challenges to the power system operations [1,2] It is difficult for the power system to retain secure, reliable and economic operations, especially at a high level of wind power penetrations. According to the actual situation of wind power integration, power system operators (PSOs) find that the large-scale wind power can increase or decrease in a very short time period with large and rapid fluctuations [3,4]. The ESS has been demonstrated to play a significant role in mitigating the fluctuations for both distributed power systems and the power system operations.

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