Scheduling strategy design for unit commitment with energy storage system and solar energy resource

• Main Author: Qin, Lingzi
• Other Authors: Hu Guoqiang
• Format: Theses and Dissertations
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Electric power
• Online Access: http://hdl.handle.net/10356/74435
• Institution: Nanyang Technological University

Unit commitment means the pre-setting scheduling and arrangement of the electrical generator operation. It plays a critical role in the power system optimization problem which aims to utilize power resources rationally and enhance the efficiency of operational economy under the condition of safe operation of power system. With the high penetration of renewable energy, which increases deregulation when renewable energy is fed into the traditional power system and attention of safety operation in power system, there is a growing focus on optimization with uncertainties. This thesis proposes a unit commitment model to minimize the impact of uncertainty. The scheduling strategy is composed of two main cases which correspond to the two intervals of the probability distribution of the solar power output. The energy storage system is coordinated to guarantee the power system security when the margin of error is beyond the confidence interval of solar power probability. In order to deal with both volatile load demand and the solar power, we apply a normal probability distribution to define net load demand. The scheduling strategy is divided into two intervals based on its confidence interval, and interval optimization is adopted to reduce the complexity of this optimization problem in the confidence interval. Energy storage system is flexible to maintain the power balance with an acceptable cost and maximize the utilization of the renewable energy in the non-confidence interval. The numerical results of 14-bus and 30-bus power systems demonstrate the effectiveness of the proposed scheduling strategy which could provide economical, adaptive and calculation time-saving features.