A smart algorithm to optimally manage the charging strategy of the Home to Vehicle (H2V) and Vehicle to Home (V2H) technologies in an off-grid home powered by renewable sources

Abstract

European directives promote activities aimed at developing a sustainable and decarbonised energy system, with a greater share of electricity production from renewable sources, within a framework of greater e ciency. In the energy of nZEB buildings, the reduction of energy needs is accompanied by the use of hybrid renewable energy systems (HRES) for the production of energy on-site to be used for appliances and lighting and also for mobility through the electric vehicle (EV) charging.With reference to this framework, the paper studied the integration of Vehicle to Home (V2H) technology in HRES for residential users. The HRES consists of a photovoltaic (PV) generator, a wind generator, an electrical storage system and a charging station for an EV, in a stand-alone context. V2H technology provides for the use of the EV as an emergency energy source if the generation and storage systems are unable to guarantee the satisfaction of the residential load. For this purpose, an algorithm is proposed that can manage and optimize the dissipated energy produced in excess, providing that this is sent, when possible, to the EV for extra charging compared to the residential charging expected in the load determination. This extra charging process does not affect the load required by the residential user being carried out directly by the generation system with the excess energy produced. With reference to an isolated single-family user not connected to the network and to the use of an EV (which ensures mobility), two energy scenarios were considered, in the absence and the presence of V2H technology. The possibility of EV charging at night and an additional extra charge during the day were considered. The load required for nocturnal EV charging rests on the residential load of the home, while the extra charge is directly borne by the generation system. To reduce excess energy, which in the considered context must be dissipated, two charging strategies were considered that differ in the choice of whether or not to carry out nocturnal charging depending on the EV state of charge. The different system con gurations and use of the generated energy make the energy analysis complete to identify the performance of these systems.The dynamic simulations of the HRES operation were carried out through TRNSYS, for the dynamic simulation of the PV and wind systems, which is coupled with MATLAB to dynamically simulate the residential battery and the H2V and V2H technologies. Starting from the hourly results obtained, an yearly energy analysis was carried out.

Challenges and Barriers of Wireless Charging Technologies for Electric Vehicles

“…The hybrid recharging system, which also used two types of internal power sources for the automobile, received additional consideration [284]. Additionally, PV systems have been integrated into vehicles to supply power from several sources, including blended power sources [285][286][287][288][289]. The main goals of the problems, addressed in the models above regarding shading impact, charging remedies, and vehicles' extra structures, included PV recharging and hybrid techniques and their remedies [290].…”

Finding the Best Station to Use Buildings Integrated Photovoltaics (BIPVs) in Eight Different Climates of Iran: Effect of Wind Speed and Photovoltaic Modules Type

“…In continuation of the present work, various aspects can be examined, such as the impact of weather changes on the performance of diferent solar cells [44], the use of artifcial intelligence in selecting more suitable solar cells [45], the amount of green hydrogen production by each type of solarcell technology [46], supplying electricity for electric vehicles [47], combining solar cells with heat pumps [48], and investigating emerging energy sources and comparing them to the actual state [49].…”

V2X integration in self-consumption energy management system

“…A common example is the use of the EV battery as a means of flexibility tool to shift the load from periods of low consumption (during the night) to peak hours in residential areas. Numerous algorithms for smart charging and discharging schemes have been developed that focus on distributed generation [3], [4] aiming to minimize costs [5], [6]. Moreover, bidirectional power between EVs and the grid could further boost the network support services (e.g.…”