A two-stage multi-objective optimal scheduling in the integrated energy system with We-Energy modeling. (15th January 2021)

• Record Type: Journal Article
• Authors: Zhang, Ning; Sun, Qiuye; Yang, Lingxiao
• Is Part Of: Energy. Volume 215(2021)Part B
• Publication Date: 2021-01-15
• Subjects: We-energy -- Two-stage strategy -- Optimal operation -- Renewable energy uncertainty -- Multi-objective scheduling; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119121
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper proposes a two-stage multi-objective optimal scheduling strategy (TMOS) based on the innovative mathematical model of We-Energy (WE) in the integrated energy system (IES). WE, as a new-style energy unit with full duplex and multi-energy carrier coupling interaction, is necessary to provide a mathematical model to solve the schema translation problem for the scheduling of the WE. Therefore, a WE mathematical model based on Hadamard Product is presented which can clearly show the dynamic properties of internal elements and the full duplex characteristic of the WE. Namely, the optimization model for the WE can be easily and compactly established by utilizing the proposed method. Furthermore, in order to reduce the unfavorable effects of the renewable energy (RE) uncertainty and realize the energy management of the WE, a TMOS on account of the proposed mathematical model is presented to dispatch the WE operation. The comprehensive impact of multiple significant operation indicators is considered in TMOS which conventional methods ignored. The economic benefit and customer satisfaction can be improved by the first-stage of TMOS according to the energy price and the day-ahead forecasting of RE generation. Meanwhile, the TMOS can reduce the impact of the RE prediction error to realize the real-time power balancing and ensure the security operation by regulating the components of the WE in the second-stage dispatch. The proposed strategy is demonstrated by two example cases, where the performance of the TMOS is observed. The consequences of the cases are analyzed in view of the energy exchanges with networks and the outputs of elements in the presented condition. Moreover, the contrast of the proposed optimal scheduling with another traditional optimal method is also discussed in the paper. As the results shown in the cases, the TMOS based on the innovative WE model balances the forecast error and has more benefits in networks influence, customer satisfaction and residual capacity indicator. Highlights: The schema translation problem for We-Energy scheduling is solved by the proposed model. The unfavorable effects of renewable energy uncertainty is reduced and We-Energy is managed. The comprehensive impact of multiple significant operation indicators is considered. Case study results for scenarios show that the method balances the forecast error. Case study results for scenarios show benefits of networks influence, customer satisfaction and RCI.