Building-owned micro energy hubs (EHs) usually focus on optimal energy consumption cost and emission, whereas, macro energy hubs (MEHs) mainly concentrate on utility’s interest termed as network load deviation. Therefore, a bi-level MEH control capable of simultaneously attaining bilateral stakes is required. However, in real life energy distribution systems, MEH structure operates under uncertainties such as unpredictable solar photovoltaic (PV) irradiance and unplanned electric and natural gas (NG) network outages. Such uncertain conditions may affect the MEH’s performance (energy cost, emission and network load deviation) and resilience (capability of recovering quickly from disturbances) undesirably. Objective of this paper is to attain an optimal compromise between the performance and the resilience of a bi-level residential MEH, under uncertain conditions. In first step, risk neutral bi-level MEH is proposed to optimally reduce the network load deviation, while obeying the customer specified comfort, emission and cost constraints. However, this strategy disregards the risk introduced by the uncertainties. In second step, risk averse strategy is devised by incorporating conditional value at risk (CVaR) in the objective function, for improvement in resilience. Proposed linear bi-level risk averse MEH is mapped in conventional flower pollination algorithm (FPA). Resilience of the MEH is measured in terms of energy stored in the plug-in hybrid electric vehicle (PHEV) and thermal energy storage (TES). Third step concentrates on the development of an efficient solution technique for energy management system to obtain better solution. For this, an improved version of FPA, termed as 2-cored FPA is proposed and employed to solve the model. Proposed technique has a filtration layer (termed as core-1) that consists of random walk, local pollination and global pollination to obtain improved pollinators. Subsequently, these pollinators are injected into conventional FPA layer (termed as core-2) to obtain better solution. Comparison of results demonstrates that under risk averse approach with two cores, the energy retaining capability of the PHEV and the TES increases by 31.66% and 57.66%, respectively.

中文翻译：

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使用能源枢纽的住宅建筑能源管理

建筑物拥有的微型能源枢纽（EH）通常关注最佳的能源消耗成本和排放，而宏观能源枢纽（MEH）主要关注公用事业的利益，即网络负载偏差。因此，需要一种能够同时获得双边权益的双层MEH控制。但是，在现实生活中的能源分配系统中，MEH结构在不确定性下运行，例如不可预测的太阳能光伏（PV）辐照度以及计划外的电力和天然气（NG）网络中断。这种不确定的条件可能会不希望地影响MEH的性能（能源成本，排放和网络负载偏差）和弹性（从干扰中快速恢复的能力）。本文的目的是在双层住宅MEH的性能和弹性之间取得最佳折衷，在不确定的条件下。第一步，提出了风险中性的二级MEH，以最佳方式降低网络负载偏差，同时遵守客户指定的舒适性，排放和成本约束。但是，该策略忽略了不确定性带来的风险。第二步，通过将条件风险价值（CVaR）纳入目标函数来设计风险规避策略，以提高抵御能力。在传统的花授粉算法（FPA）中映射了拟议的线性二级风险规避MEH。根据插电式混合动力汽车（PHEV）和热能存储（TES）中存储的能量来衡量MEH的弹性。第三步集中于开发一种有效的能源管理系统解决方案技术，以获得更好的解决方案。为此，FPA的改进版本 提出并称为2芯FPA，并对其进行求解。提议的技术有一个过滤层（称为核心1），该层由随机游走，局部授粉和整体授粉组成，以获得改进的授粉媒介。随后，将这些授粉剂注入常规FPA层（称为core-2）中，以获得更好的溶液。结果比较表明，在具有两个核心的风险规避方法下，PHEV和TES的能量保持能力分别提高了31.66％和57.66％。将这些授粉剂注入常规FPA层（称为core-2）中，以获得更好的溶液。结果比较表明，在具有两个核心的风险规避方法下，PHEV和TES的能量保持能力分别提高了31.66％和57.66％。将这些授粉剂注入常规FPA层（称为core-2）中，以获得更好的溶液。结果比较表明，在具有两个核心的风险规避方法下，PHEV和TES的能量保持能力分别提高了31.66％和57.66％。