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Optimal placement of heterogeneous distributed generators in a grid-connected multi-energy microgrid under uncertainties

机译:不确定性下并网多能源微电网中异构分布式发电机的最优布置

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摘要

The multi-energy microgrid (MEMG) comprises heterogeneous distributed generators (DGs) such as wind turbines, diesel generators, combined cooling, heat and power plants etc. Proper placement of these DGs is critical for the system energy efficiency and network reliability performance. This study proposes a two-stage coordinated method for optimally placing heterogeneous DGs in an MEMG project considering the uncertainties from renewable energy sources (RESs). Apart from optimising the traditional DG size and location, this method considers the optimal DG type and investment year simultaneously by maximising the project net present value (NPV), which consists of investment costs and operation costs. The whole problem is modelled as a two-stage coordinated stochastic optimisation model, where the long-term DG investment is determined at the first stage and operation decisions are determined at the second stage. The proposed method is verified on a test MEMG system. The simulation results show that its NPV is positive, which means the method is effective and should be implemented. Compared with the conventional DG placement approaches, the proposed method is more robust against the RES uncertainties and can better coordinate the heterogeneous energies with higher dispatch flexibility and economic profits.
机译:多能源微电网(MEMG)包括异构分布式发电机(DG),例如风力涡轮机,柴油发电机,联合冷却,热力发电厂等。这些DG的正确放置对于系统能效和网络可靠性性能至关重要。这项研究提出了一种两阶段协调的方法,该方法考虑了可再生能源(RES)的不确定性,从而在MEMG项目中优化了非均质DG的放置。除了优化传统DG的大小和位置之外,该方法还通过最大化由投资成本和运营成本组成的项目净现值(NPV)来同时考虑最佳DG类型和投资年份。整个问题被建模为两阶段协调随机优化模型,其中在第一阶段确定长期DG投资,在第二阶段确定操作决策。所提出的方法在测试的MEMG系统上得到了验证。仿真结果表明,该方法的NPV为正,说明该方法有效,值得推广。与传统的DG布置方法相比,该方法对RES不确定性具有更强的鲁棒性,可以更好地协调异构能源,具有更高的调度灵活性和经济效益。

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