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.

Managing plug-in electric vehicles in eco-environmental operation optimization of local multi-energy systems

Di Somma M.;Graditi G.
2020

Abstract

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.
Eco-environmental operation optimization
Flexibility management
Local multi-energy system
Mixed-integer linear programming
Plug-in electric vehicles
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/57175
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