Abstract
In this paper, we proposed a home energy management system (HEMS) that includes photovoltaic (PV), electric vehicle (EV), and energy storage systems (ESS). The proposed HEMS fully utilizes the PV power in operating domestic appliances and charging EV/ESS. The surplus power is fed back to the grid to achieve economic benefits. A novel charging and discharging scheme of EV/ESS is presented to minimize the energy cost, control the maximum load demand, increase the battery life, and satisfy the user’s-traveling needs. The EV/ESS charges during low pricing periods and discharges in high pricing periods. In the proposed method, a multi-objective problem is formulated, which simultaneously minimizes the energy cost, peak to average ratio (PAR), and customer dissatisfaction. The multi-objective optimization is solved using binary particle swarm optimization (BPSO). The results clearly show that it minimizes the operating cost from 402.89 cents to 191.46 cents, so that a reduction of 52.47% is obtained. Moreover, it reduces the PAR and discomfort index by 15.11% and 16.67%, respectively, in a 24 h time span. Furthermore, the home has home to grid (H2G) capability as it sells the surplus energy, and the total cost is further reduced by 29.41%.
Highlights
Energy demand increases very sharply day by day
To achieve the benefits of DR programs, a home energy management system (HEMS) is required at home
Nj is the number of time slots that are required to complete the operation of each ST appliance, which is shown in the following constraints
Summary
Energy demand increases very sharply day by day. To overcome this problem and optimize the power generated, researchers have proposed an effective strategy called. In [5], a HEMS system has been proposed to schedule domestic appliances in response to RTP They formulate a multi-objective optimization problem that considers bill minimization and user comfort as system objectives. Their study combines RTP with the IBR model Using this integrated pricing model, the suggested power scheduling strategy reduces both energy costs and PAR, improving the overall system stability. They employ a GA to address optimization problems. In [12], the integration of RES with HEMS was presented to reduce the peak demand and increase the stability of the power grid They utilized the RES and scheduled domestic appliances to reduce the PAR, power purchased, and electricity bill.
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