Search

Integrating electric vehicles (EVs) into the electric power system poses significant challenges to grid operation and planning due to the potential constraints on the power system. To minimize grid congestion, the best option is to increase the production of photovoltaic (PV) energy for domestic use and EV charging stations. This paper addresses the nexus of technical, financial, and environmental effects of customer involvement in economic development and load management. In this paper, a new model design of solar-powered EV charging stations is proposed and implemented in HOMER Grid, and a case study has explored how economic, technical, and energy management benefits can be achieved through customer energy involvement and the integration of PV-based charging stations. The proposed PV-based charging stations contribute toward the energy management of the region, and the study observes the real-time optimal charging and discharging strategy of PV-based grid-connected charging stations. The case study results show that the investigated area can produce 1,070,804.096 MWh/year of energy through maximum customer involvement, consequently reducing overall energy costs. Moreover, the study demonstrates that the selected region can produce 86,961,688 kWh/year through the PV system, achieving 363,899 charging sessions per year, offering maximum advantages and facilitation for EV charging. The proposed model applicability shows that large-scale customer involvement can bring significant techno-economic benefits and attract regional investments. • This paper proposes a new design of a grid-tied renewable energy system. • It investigates the energy economics and environmental effects for a practical location. • The research examines energy management including PV systems and electric vehicles. • The results of proposed model are compared with other models. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a significantly improved optimization model for the planning of the charging infrastructure for electric-drive vehicles, where the optimization objective function is the minimization of overall (installation, maintenance, operation) placement costs of charging stations with regards to a charging technology. The constraints involve the electric power system reliability check, ensuring charging reliability and the required quality of service of the charging infrastructure. In ensuring the charging reliability, at least one candidate location must be selected within the driving range of electric vehicles and suitable charging technologies placed to accommodate the disposable charging times of electric vehicle users for the requested quality of service. The proposed optimization model presents an upgrade of an existing optimization formulation since it includes a power system reliability check based on a DC power flow model. To show the general applicability and significance of the model, a test 10 × 10 grid road network and a standard six-bus test power system are considered. Numeric results illustrate the optimal charging stations placement layout and overall costs placement for different driving ranges and the required quality of service level by including a power system reliability check, to serve both the charging infrastructure investors and electric power system operators. Highlights • Including the electric power system reliability check, to derive an optimal charging stations placement solution. • New constraints in the charging stations placement optimization model, to serve both the investors and network operators. • Lines outage criticality ranking, to provide network operators valuable information for the network expansion planning. [ABSTRACT FROM AUTHOR]