A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response. (1st December 2022)

• Record Type: Journal Article
• Authors: Ju, Liwei; Lu, Xiaolong; Yang, Shenbo; Li, Gen; Fan, Wei; Pan, Yushu; Qiao, Huiting
• Is Part Of: Applied energy. Volume 327(2022)
• Publication Date: 2022-12-01
• Subjects: Micro energy grid -- Biomass waste energy -- Multi-time scale -- Demand response -- Dispatching model; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2022.120155
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Design a rural biomass waste energy conversion system-based micro-energy grid (BWs-MEG) Proposes a robust multi-time scale dispatching optimal model for the rural BWs-MEG. Converts the multi-time scale dispatching model into mixed integer linear programming model. Select a micro-energy grid in northern China for the effectiveness and applicability analysis. Discuss the influence of the multi-energy transform system and multi-energy demand response. Abstract: Aiming at utilizing straw, garbage, domestic sewage and other biomass waste resources in rural areas, this study designed a rural biomass wastes energy conversion system (BWs)-based micro energy grid (BWs-MEG), and the mathematical modeling of BWs-MEG is carried out including multi-energy transforms system (METS) and multi-energy demand response (MEDR). Then, a two-stage optimal framework for rural BWs-MEG multi-time scale dispatching is designed. In the day-ahead stage, a multi-objective dispatching optimal model was constructed with the objectives of minimum operating costs and maximum eco-environment benefits. In the intra-day stage, the robust optimization theory was utilized to characterize the uncertainties of wind power plant (WPP) and photovoltaic power generation (PV) and a rolling dispatching optimal model was constructed with the objective of minimum deviation costs. After that, the above dispatching model was fuzzified and linearized, and then converted into a mixed integer linear programming model. Finally, a micro-energy grid in northern China was selected as an example for case study. The results showed: (1) BWs can utilize rural biomass waste resources for pyrolysis power generation (PG) and gas production to achieve energy utilization and provide power, heating and gas output. In the islanded operation mode and grid-connected operation mode, when MEG is configured with BWs, the deviation costs decrease by 25.6 % and 26.33 %, while the operating costs increases only by 7.60 % and 13.52 %, respectively. The power output of WPP and PV increase by 1.03 % and 2.19 % in the grid-connected operation mode, indicating that BWs is conducive to realizing the multi-dimension supply and demand balance of power, heating and gas loads. (2) Multi-time scale dispatching model can give play to the regulation ability of BWs, METS and MEDR and connect the day-ahead dispatching plan with the intra-day dispatching strategy to formulate the optimal dispatching strategy. When there is deviation in the day-ahead dispatching strategy, METS and MEDR could maintain the supply and demand balance of power load. AHP can change the heating period and BWs could maintain the supply and balance of heating and gas loads. Compared with the day-ahead dispatching plan, the output of PG and power-to-gas device in intra-day dispatching strategy increase by 21.22 % and 9.78 %. (3) Robust stochastic optimization method can characterize the uncertainties of WPP and PV and formulate the dispatching decision schemes with different risk attitudes. With the robust coefficient Г increasing, MEG operating costs and eco-environment benefits increase and deviation adjustment costs decreases, but the robustness of the dispatching scheme is improved. When 0.25≤ Г ≤0.75, the increase of the uncertainty parameter will have a direct impact on the formulation of dispatching scheme. And the decision maker belongs to risk preference type, who is willing to take certain risks to win excess benefits. Besides, if MEG operates in the grid-connected mode, the uncertainty risks will be weakened and the operation mode shall be reasonably selected according to the demand for dispatching decision. Overall, the proposed optimization model can promote the energy utilization of rural biomass waste resources, which is conducive to the realization of a clean and low-carbon transformation of the overall energy structure.