Abstract
In prosumers’ communities, the use of storage batteries (SBs) as support for photovoltaic (PV) sources combined with coordination in household appliances usage guarantees several gains. Although these technologies increase the reliability of the electricity supply, the large-scale use of home appliances in periods of lower solar radiation and low electricity tariff can impair the performance of the electrical system. The appearance of new consumption peaks can lead to disturbances. Moreover, the repetition of these events in the short term can cause rapid fatigue of the assets. To address these concerns, this research proposes a mixed-integer linear programming (MILP) model aiming at the optimal operation of the SBs and the appliance usage of each prosumer, as well as a PV plant within a community to achieve the maximum load factor (LF) increase. Constraints related to the household appliances, including the electric vehicle (EV), shared PV plant, and the SBs, are considered. Uncertainties in consumption habits are simulated using a Monte Carlo algorithm. The proposed model was solved using the CPLEX solver. The effectiveness of our proposed model is evaluated with/without the LF improvement. Results corroborate the efficient performance of the proposed tool. Financial benefits are obtained for both prosumers and the energy company.
Highlights
The proposed mixed-integer linear programming (MILP) model is executed based on the information mentioned above to obtain the optimal consumption profile, Oucp,a,t, result in efficient scheduling of household appliances a, as well as the optimal performance of energy generation and storage technologies, i.e., shared PV plant and SBs
A MILP model has been proposed to address the problem of intelligent energy management in a community of prosumers by improving the load factor (LF)
Constraints related to energy production by a shared PV plant, surplus energy, and community energy balance are taken into account
Summary
The need for efficient electricity management in large cities worldwide has led electric utilities to implement the Smart Grid (SG) concept in their electrical distribution networks (EDNs) [1]. A system of SBs combined with a shared PV plant fulfills the energy needs of the prosumer community, and, in the case of generating surpluses of power, these are directed to the grid These objectives are achieved in a coordinated manner to obtain a wide distribution of consumption during the day, which is represented by improving the LF. By increasing the LF, this work seeks to mitigate the appearance of new peaks in periods with cheap energy tariffs (due to the coincident usage of appliances with higher average power) via intelligent operation of PV-based technology and energy storage, ensuring continuity of supply. Proposing a computationally efficient MILP model to improve the value of LF related to the consumption profile of prosumers while taking into account the efficient scheduling of technologies such as SBs and shared PV generation. Contributing to reducing the dependence on fossil fuels to meet the energy of domestic customers aiming at a sustainability context
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call