Local multi-energy systems (LMES) have been recently recognized as a promising alternative to centralized energy supply systems to meet local energy needs, since they promote efficient use of the available energy thanks to the coordination of heat and power technologies, storage, flexible demand and plug-in electric vehicles (PEVs). In this framework, PEVs represent loads to satisfy in the grid-to-vehicle (G2V) mode, while also serving as distributed storage when equipped with vehicle-to-grid (V2G) technology, and can provide both economic and environmental benefits if properly managed. The contribution of this paper is to present a comprehensive multi-objective optimization model for the energy management of an LMES in the presence of PEVs, with the aim to combine maximization of LMES operator’s profit with the minimization of CO₂ emissions. The LMES supplies electricity, heat and cooling to a building cluster with PEVs, which can operate in both G2V and V2G modes. The problem consists of dispatching technologies in the LMES and finding the optimized charging/discharging strategies of PEVs in order to maximize the operator’s profit while also reducing CO₂ emissions, and it is addressed by formulating a multi-objective linear programming problem with the detailed modeling of interdependencies among energy carriers. The weighted sum method is used to represent the eco-environmental optimization problem, and it is solved by using CPLEX solver and considering a cluster of office buildings located in Italy as end-user of the LMES with PEVs owned by the offices’ employees. Testing results demonstrate the effectiveness of the optimization framework to maximize the operator’s profit while also reducing the CO₂ emissions, thanks to the optimal coordination of the multiple energy carriers in the LMES and the effective management of the flexibility collected at both supply and demand sides. Moreover, it is found that through the optimized charging and discharging strategies, the PEVs, acting as distributed energy storage, allow the provision of demand response services by also complementing renewable power to improve energy efficiency. In detail, under the economic optimization, most of flexibility collected from PEVs is sold into the wholesale market in order to maximize the operator’s profit, whereas, under the environmental optimization, the power discharged from PEVs is exploited for self-use in the LMES to minimize environmental impacts by using a carbon-free source.

本地多能源系统（LMES）最近被公认为是满足本地能源需求的集中式能源供应系统的有前途的替代方案，因为借助热电技术，存储和灵活需求的协调，它们可促进有效利用可用能源和插电式电动车（PEV）。在此框架中，PEV代表的是电网到车辆（G2V）模式下要满足的负载，而当配备了车辆到电网（V2G）技术时，PEV也可以用作分布式存储，并且如果适当地提供经济和环境效益管理。本文的目的是为存在PEV的LMES的能源管理提供一个综合的多目标优化模型，以将LMES运营商利润的最大化与CO的最小化相结合。₂排放。LMES为带有PEV的建筑群提供电，热和制冷，PEV可以在G2V和V2G模式下运行。问题包括LMES中的调度技术，以及寻找PEV的优化充电/放电策略，以最大程度地提高运营商的利润，同时减少CO _2。排放，并通过制定多目标线性规划问题以及能量载体之间相互依赖性的详细模型来解决。加权总和法用于表示生态环境优化问题，可通过使用CPLEX求解器并考虑位于意大利的一组办公楼作为LMES的最终用户来解决，而LMES的最终用户是办公室员工拥有的PEV。测试结果证明了优化框架在最大化运营商利润的同时还减少了CO ₂的有效性。由于LMES中多个能源载体的最佳协调以及对供需双方收集到的灵活性的有效管理，因此产生了碳排放。此外，发现通过优化的充电和放电策略，充当分布式能量存储的PEV还可通过补充可再生能源来提高能源效率，从而提供需求响应服务。详细地说，在经济优化的情况下，从电动汽车获得的大部分灵活性被出售给批发市场以最大化运营商的利润，而在环境优化的情况下，从电动汽车释放的电力可在LMES中用于自用。通过使用无碳源将对环境的影响降至最低。