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Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand

机译:考虑电力,供热和制冷需求的基于场景的独立多能源微电网投资计划

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Multi-energy microgrids provide a flexible solution for the utilization of the distributed energy resources in order to meet the electrical, heating and cooling energy demands in the off-grid communities. However, the planning of the multi-energy microgrids is a non-trivial problem due to the complex energy flows between the sources and the loads pertaining to the electrical, heating and cooling energy, along with the intermittency of the renewable distributed generation. This work proposes a scenario-based stochastic multi-energy microgrid investment planning model that aims to minimize the investment and operation costs as well as the Carbon dioxide emissions by determining the optimal distributed energy resource mix, siting and sizing in the isolated microgrids. The proposed planning model employs the power flow and heat transfer equations to explicitly model the energy flows between electrical, heating and cooling energy sources and loads. Moreover, an uncertainty matrix is employed to tackle the operational uncertainties associated with the wind and photovoltaic generation, and the electrical, heating and cooling loads. The uncertainty matrix is modeled using the heuristic moment matching method that effectively captures the stochastic moments and correlation among the historical scenarios. The numerical results obtained from the case-study in the 19-bus microgrid test system confirm that the proposed methodology provides significant reductions in the investment and operation costs as well as the Carbon dioxide emissions. Finally, the superiority of the proposed planning solution is also validated using the deterministic planning solution as the comparison benchmark.
机译:多能源微电网为分布式能源的利用提供了灵活的解决方案,以满足离网社区的电力,供热和制冷能源需求。但是,由于能源与能源,热能和冷却能之间的复杂能量流动以及可再生分布式发电的间歇性,多能量微电网的规划并不是一个简单的问题。这项工作提出了一种基于场景的随机多能源微电网投资计划模型,该模型旨在通过确定最佳的分布式能源资源组合,在孤立的微电网中选址和确定规模,将投资和运营成本以及二氧化碳排放降至最低。拟议的计划模型使用功率流和热传递方程式来明确建模电,热和冷却能源与负载之间的能量流。此外,采用不确定性矩阵来解决与风能和光伏发电以及电,热和冷负荷相关的运行不确定性。使用启发式矩匹配方法对不确定性矩阵进行建模,该方法可以有效地捕获历史情景之间的随机矩和相关性。从19总线微电网测试系统的案例研究获得的数值结果证实,所提出的方法可显着降低投资和运营成本以及二氧化碳排放量。最后,还使用确定性计划解决方案作为比较基准来验证所提出计划解决方案的优越性。

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