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Multi-objective capacity optimization of a distributed energy system considering economy, environment and energy

机译：考虑经济，环境和能源的分布式能源系统多目标容量优化

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With the climate change and depletion of fossil energy, distributed energy systems (DESs) have attracted widespread attention. In this study, a DES driven by solar, geothermal, aerothermal, natural gas and power grid is constructed with energy conversion devices modeled based on part load performance. A novel operation strategy for the DES is presented considering the complementary characteristics of different energy sources. Besides, a multi-objective nonlinear optimization model for the device capacity is proposed with economic, environmental and energy objectives considered simultaneously. To solve the optimization model, an integrated solution method combining Non-dominated Sorting Genetic Algorithm-II, Technique for Order Preference by Similarity to an Ideal Solution and Shannon entropy approach is developed. A case study of an indoor swimming pool in Changsha city of China is undertaken. Optimal equipment capacity and corresponding energy management strategies of the case are obtained. The final number and capacity of air source heat pump (ASHP) are determined via improving its part load ratio. Additionally, three schemes are set to investigate the effects of constant efficiency/COP of energy conversion devices and operation strategies on the capacity optimization of DESs. Results indicate that constant efficiency/COP of equipment yields an 11.7% drop in annual total cost (ATC), a 10.4% increment in annual total CO2 emission (ATE) and a 12.5% reduction in coefficient of energy performance (CEP). ATC and ATE of the optimal solution acquired under a conventional operation strategy increase by 6.8% and 3.7%, while CEP decreases by 66.9%. This work provides a guidance for the future application of DESs.
机译：随着气候变化和化石能源的枯竭，分布式能源系统（DES）引起了广泛关注。在本研究中，构建了由太阳能，地热，航空热能，天然气和电网驱动的DES，并使用了基于部分负荷性能建模的能量转换设备。考虑到不同能源的互补特性，提出了一种新颖的DES运行策略。此外，提出了同时考虑经济，环境和能源目标的设备容量的多目标非线性优化模型。为了求解该优化模型，开发了一种综合解决方案方法，该方法结合了非支配排序遗传算法-II，与理想解相似的优先顺序排序技术和香农熵方法。以中国长沙市的室内游泳池为例。获得了该案例的最佳设备容量和相应的能源管理策略。空气源热泵（ASHP）的最终数量和容量是通过提高其部分负载比来确定的。此外，设置了三种方案来研究能量转换装置的恒定效率/ COP和操作策略对DES容量优化的影响。结果表明，恒定的设备效率/ COP可使年度总成本（ATC）下降11.7％，年度总CO2排放量（ATE）增长10.4％，而能源绩效系数（CEP）则下降12.5％。在常规操作策略下获得的最佳解决方案的ATC和ATE分别增长6.8％和3.7％，而CEP则下降66.9％。这项工作为DES的未来应用提供了指导。

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