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Flexible distributed multienergy generation system expansion planning under uncertainty

机译:不确定条件下的灵活分布式多能源发电系统扩展计划

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Summary form only given. A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems.
机译:摘要表格仅给出。智能电网的关键特征是使用需求侧资源来为能量系统提供灵活性,从而提高其效率。多energy系统,其中不同的能量向量,例如气体,电和热量被优化,同时证明是一种有价值的需求侧柔性。然而,这些系统的规划可能非常具有挑战性,特别是在存在潜在的能量向量中的长期价格不确定性。本文提出了一种统一的经营和规划优化方法,用于分布式多念代(DMG)系统,目的是评估嵌入在经营和投资阶段的灵活性,这在经过长期的不确定性。该拟议的方法反映了从金融借来的真实选择,并作为随机混合整数线性计划铸造。该方法是通过基于现实的U.K.的DMG案例研究来说明地区能量系统,包括热量和发电厂,电热泵和热能储存。结果表明,该方法允许预期成本和风险相对于其他更少灵活的规划方法降低,从而潜在增强灵活的DMG系统的业务情况。

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