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A novel coordinated optimization strategy for high utilization of renewable energy sources and reduction of coal costs and emissions in hybrid hydro-thermal-wind power systems

风力发电 火力发电站 发电 粒子群优化 可再生能源 调峰发电厂 工程类 汽车工程 功率(物理) 分布式发电 工艺工程 计算机科学 废物管理 电气工程 物理 机器学习 量子力学
作者
Huanhuan Li,Runfan Zhang,M. A. Mahmud,Branislav Hredzak
出处
期刊:Applied Energy [Elsevier]
卷期号:320: 119019-119019 被引量:9
标识
DOI:10.1016/j.apenergy.2022.119019
摘要

• A coordinated optimization strategy for hydro-thermal-wind power systems is proposed. • The strategy prioritizes hydro unit commitment to respond to fluctuations in wind power. • A daily complementary operation principle of hydro, thermal and wind generation units to achieve efficient operation is presented. • Wind curtailment and coal costs are greatly reduced by management of hydro units. • Cleaner operation of hybrid power systems with coal-combusted power plants can be achieved. In multi-source-based energy systems, the ultimate target of optimal operation of the generation units is to create an efficient power system with cleaner production. In this paper, a novel coordinated operation strategy optimizing the commitment of hydro, thermal and wind generation units is proposed. The strategy consists of two hierarchical optimization goals. In the primary goal, utilization of wind and hydro energy units is optimized, and the objective functions involve maximizing hydro energy utilization and minimizing wind curtailment. In the secondary goal, coal costs and carbon emissions are minimized after meeting the utilization goal. The overall execution of the strategy is governed by three power production decisions including peak-load shaving, valley-load filling and generation. The first two decisions suppress the fluctuation in wind power while the generation decision makes full use of the hydro units to replace the working thermal units. The presented operation strategy is applied to an improved IEEE 118-node power system. The optimization ensures the highest utilization of wind energy while coping with the day-ahead wind power forecasting error. Moreover, a particle swarm optimization method is applied to optimize the coal costs and carbon emissions. The presented results demonstrate the capability of the proposed strategy to configure the operation of the multi-source-based energy system with high efficiency and low emissions. Finally, several recommendations to amend the existing management of multi-source-based energy systems are presented.
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