Abstract
Economic profit is the main incentive for PV‐integrated residential prosumers, so energy management algorithms play a key role in these systems. The main priority of conventional rule‐based energy management systems (REMS) is to supply the demand. As a result, the total amount of energy sold to the distribution network, and consequently the user profit in such systems, is not considerable. This study proposes a smart energy management system (SEMS) for optimal energy management in a grid‐connected residential photovoltaic (PV) system, including battery as an energy storage unit. The proposed method, which is simulated by MATLAB, using real values for load and PV characteristics, will result in achieving an economic plan for battery operation based on a discretised state of charge of the battery. Experimental tests, carried out to verify the simulation results, demonstrate a noticeable increase in the prosumer benefits as well as the load profile correction compared to the classic energy management algorithms.
Highlights
In recent years, distributed generation has been developed in large scales, most of which in the form of renewable resources due to the depletion of fossil fuel resources as well as environmental concerns [1]
The PV system includes four PV panels with a maximum power of 20 W, each connected to a boost DC/DC converter to assure that partial shading would not affect the system performance
An smart energy management system (SEMS) algorithm is proposed to optimise the economic profitability of the residential PV systems, through maximising the total amount of energy available for selling to the grid when the feed-in tariffs (FITs) scheme is applied
Summary
In recent years, distributed generation has been developed in large scales, most of which in the form of renewable resources due to the depletion of fossil fuel resources as well as environmental concerns [1]. In [6], the storage potential of battery-integrated PV systems and their ability to participate in demand response programs are compared in terms of the reduction of the electricity bill Another trending policy in some countries is to offer incentives such as electricity feed-in tariffs (FITs) [7] for small-scale grid-connected PVs to encourage customers and investors to generate green solar power and participate in electricity markets [8, 9]. According to the above-mentioned issues, this study proposes a smart energy management system (SEMS) algorithm for grid-connected PV systems to increase the residential PV system adaptability with different user’s dynamic demand patterns. An optimisation algorithm is proposed with the purpose of maximising prosumer’s economic benefits, based on the dayahead load demand forecast and PV generation estimation.
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