Power system dynamic economic dispatch with multi-type renewable energy
Power system dynamic economic dispatch with multi-type renewable energy
- Author(s): Jizhong Zhu ; Qiaobo Liu ; Ziyu Chen ; Shenglin Li ; Tengyan Luo
- DOI: 10.1049/cp.2019.0349
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- Author(s): Jizhong Zhu ; Qiaobo Liu ; Ziyu Chen ; Shenglin Li ; Tengyan Luo Source: 8th Renewable Power Generation Conference (RPG 2019), 2019 page (6 pp.)
- Conference: 8th Renewable Power Generation Conference (RPG 2019)
- DOI: 10.1049/cp.2019.0349
- ISBN: 978-1-83953-125-5
- Location: Shanghai, China
- Conference date: 24-25 Oct. 2019
- Format: PDF
This paper reports a dynamic economic dispatch approach for the power system with multi-type renewable energies. The renewable energy sources considered in the paper are wind, PV and hydro power, which are configured as a virtual power plant (VPP) according to their complementarities. To evaluate the ability of VPP power output tracking the load demand curve, three indices, that is, the fluctuation rate, the standard deviation, and the changing rate of the fluctuation of the VPP power output are proposed. Accordingly, a comprehensive performance index is defined to combine three individual indices with different weighting factors. A dynamic economic dispatch model for power system with multi type renewable energies is set up, which considers the complementarities of multi-type energy, as well as the optimization of VPP power output. The firefly algorithm and an improved particle swarm optimization are applied to solve the proposed model. A practical power system with multi type renewable energy sources, which is a real provincial integrated energy system in Southeast China, is used for simulation. The results and analysis are given in the paper.
Inspec keywords: particle swarm optimisation; power generation economics; power generation dispatch; photovoltaic power systems; demand side management; hydroelectric power; wind power
Subjects: Hydroelectric power stations and plants; Solar power stations and photovoltaic power systems; Power system management, operation and economics; Optimisation techniques; Wind power plants
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