Issue |
E3S Web Conf.
Volume 416, 2023
3rd International Conference on Oil & Gas Engineering and Geological Sciences (OGEGS 2023)
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Article Number | 01031 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/e3sconf/202341601031 | |
Published online | 10 August 2023 |
Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs
1 Fujian Shuikou Power Generation Group Co., Ltd, Fuzhou 305004, China
2 North China Electric Power University, School of Economics and Management, Beijing 102206, China
The vigorous development of clean energy is an important way to achieve “Carbon peak, Carbon neutral”, but the inherent intermittent and uncontrollable power generation characteristics of clean energy such as scenery and other comprehensive factors make the energy consumption problem more prominent, and the multi-energy complementary can solve the energy consumption problem more effectively. However, the current study of multi-energy complementary operation only considers the fuel cost, load shedding and wind and solar abandonment cost, and does not consider enough the peaking cost of thermal power units and the life loss of batteries. To address these problems, a multi-energy complementary energy system operation optimization model considering multiple types of peaking costs is established, and the peaking costs of regulating units are modeled more finely and solved by a dynamic inertia weighted particle swarm algorithm. The results demonstrate that the addition of energy storage system can effectively reduce the total operating cost of the system under the condition of large-scale clean energy grid connection, and the addition of creeping cost and low load operating cost can reflect the cost of conventional units more realistically, which can better provide the dispatching strategy for the decision of multi-energy complementary operation of power system.
Key words: Multi-energy complementary / Integrated energy system / Peaking cost / Optimal operation / Particle swarm algorithm
© The Authors, published by EDP Sciences, 2023
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