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Open AccessArticle

A Multi-Objective Scheduling Optimization Model for a Multi-Energy Complementary System Considering Different Operation Strategies

by 1,2,*, 3, 1,4, 3, 2,4, 2,4 and 5
1
School of Economic and management, North China Electric Power University, Beijing 102206, China
2
Beijing Energy Development Research Base, Beijing 102206, China
3
State Grid Henan Economic Research Institute, Zhengzhou 450052, China
4
Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China
5
State Grid Shanghai Urban Electric Power Supply Company, Shanghai 200056, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(11), 2293; https://doi.org/10.3390/app8112293
Received: 25 September 2018 / Revised: 30 October 2018 / Accepted: 30 October 2018 / Published: 19 November 2018
(This article belongs to the Special Issue Intelligent Energy Management of Electrical Power Systems)
In order to reduce the amount of abandoned clean energy, the complementary characterization of wind power plants (WPPs), photovoltaic power plants (PVs), hydropower stations (HSs), and thermal power plants (TPPs) combined with energy storage devices (ESDs) is considered, and they are integrated into a multi-energy complementary system (MECS). Firstly, a scenario-generating technique is proposed for uncertainty factors using the Wasserstein method and the improved K-medoids theory. Then, a multi-objective model and solution algorithm are constructed under the objectives of attaining the maximum operation revenue, the minimum abandoned energy cost, and the minimum output fluctuations. Meanwhile, the influence of different ESD operation modes on MECS operation is discussed, specifically, the longest life cycle (LLC) and the optimum economic efficiency (OEE). Thirdly, in order to solve the multi-objective model, a solution algorithm is proposed by using the rough set method to convert the multi-objective model into a single objective model based on the payoff table. Moreover, the complementary features of the MECS are evaluated in terms of the load tracking degree, HS secondary peaking capacity, and units of coal consumption. Finally, the improved IEEE 14-bus system is chosen for the simulation analysis. The results show that (1) the proposed uncertainty simulation method can efficiently generate the most representative scenarios; (2) MECSs can utilize complementary power sources, the OEE mode can better optimize MECS scheduling, and the LLC mode can ensure the ESDs’ life cycles; (3) the scheduling scheme of MECS operation reach the optimal level when the capacity ratio of ESD:WPP–PV iso [0.62, 0.77] in the OEE mode and [1, 1.08] in the LLC mode on a typical summer day, and the ratio is [0.92, 1] in the OEE mode and [1.23, 1.31] in the LLC mode on a typical winter day. Therefore, the proposed model provides effective decision-making support for designing the optimal plan for MECS operation. View Full-Text
Keywords: multi-energy; multi-objective; uncertainty; wind power; energy storage multi-energy; multi-objective; uncertainty; wind power; energy storage
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MDPI and ACS Style

Ju, L.; Li, P.; Tan, Q.; Wang, L.; Tan, Z.; Wang, W.; Qu, J. A Multi-Objective Scheduling Optimization Model for a Multi-Energy Complementary System Considering Different Operation Strategies. Appl. Sci. 2018, 8, 2293. https://doi.org/10.3390/app8112293

AMA Style

Ju L, Li P, Tan Q, Wang L, Tan Z, Wang W, Qu J. A Multi-Objective Scheduling Optimization Model for a Multi-Energy Complementary System Considering Different Operation Strategies. Applied Sciences. 2018; 8(11):2293. https://doi.org/10.3390/app8112293

Chicago/Turabian Style

Ju, Liwei; Li, Peng; Tan, Qinliang; Wang, Lili; Tan, Zhongfu; Wang, Wei; Qu, Jingyan. 2018. "A Multi-Objective Scheduling Optimization Model for a Multi-Energy Complementary System Considering Different Operation Strategies" Appl. Sci. 8, no. 11: 2293. https://doi.org/10.3390/app8112293

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