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Network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm

delete2019-12-01
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李超顺 cover
李超顺 (Chaoshun Li) *
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Wenxiao Wang
王金文 cover
王金文 (Jinwen Wang)
DOI:10.1016/j.energy.2019.116203delete
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Abstract

Abstract

En 中文
With increasing share of renewable energy (RE) in power system, the unit commitment of hybrid power system have become more complicated due to network security demand and integration of pumped hydro energy storage (PHES). In this paper, a network-constrained unit commitment (NCUC) problem considering RE uncertainty and modulation of PHES has been raised. The NCUC model, with AC network security constraints and environmental constraints as well as traditional terms of constraints, is complicated to be solved. A novel Binary Artificial Sheep Algorithm (BASA) is used to solve the NCUC model. In the frame of BASA, the NCUC problem is decomposed as a master UC problem to determine start/stop status and economic load dispatch and a sub problem to check the AC network constraints. Based on the NCUC model and the solving method, the joint impacts of RE uncertainty and PHES have been studied. Test systems with different size have been adopted to verify the feasibility and effectiveness of the BASA. It is seen that the BASA has achieve an overall competitive performance on terms of operation cost and convergence speed by comparing it with existing methods. A modified IEEE 30-bus system with wind and photovoltaic power stations has been designed to reveal the impacts of RE and PHES. The results demonstrate that uncertainty of RE affects operation cost and security of the hybrid power system, and the adverse impact would aggravate as the RE forecasting error increase. The results also confirm the significant effect of PHES in restraining the negative influence of RE uncertainty. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Network-constrained unit commitment
Renewable energy
Binary artificial sheep algorithm
Scenario analysis
Pumped hydro energy system
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Energy cover
Energy
IF:
9.4
Papers:
4.2W
Citations:
20.2W

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