The increase in energy demand, including peak power demand for electricity is one of the most important aspects to be considered in the electricity sector, as it has a negative impact on the flexibility of the power supply and the power balance in the electricity networks. Usually, some distribution system operators impose an additional cost on electricity consumption during peak hours, on other hand, they reducing the electricity price during off-peak periods to encourage householders to reschedule the use of electricity consumption. The work presented in this paper aims to propose an optimal strategy for scheduling energy consumption to help householders for reducing the cost of energy, as well as for saving energy in a residential house connected to a microgrid (Power grid system, PV, and battery storage system). The results presented are obtained using a particle swarm optimization algorithm (PSO) using Matlab. Two optimization scenarios are considered and compared to a base model to prove the efficiency and performance of the proposed optimization model. The results show that the scheduling strategy for energy consumption reduces the daily operating cost by 45% and that about 22% of energy is saved in the system.

Efficient energy scheduling considering cost reduction and energy saving in hybrid energy system with energy storage

M. L. Ferrari
2021-01-01

Abstract

The increase in energy demand, including peak power demand for electricity is one of the most important aspects to be considered in the electricity sector, as it has a negative impact on the flexibility of the power supply and the power balance in the electricity networks. Usually, some distribution system operators impose an additional cost on electricity consumption during peak hours, on other hand, they reducing the electricity price during off-peak periods to encourage householders to reschedule the use of electricity consumption. The work presented in this paper aims to propose an optimal strategy for scheduling energy consumption to help householders for reducing the cost of energy, as well as for saving energy in a residential house connected to a microgrid (Power grid system, PV, and battery storage system). The results presented are obtained using a particle swarm optimization algorithm (PSO) using Matlab. Two optimization scenarios are considered and compared to a base model to prove the efficiency and performance of the proposed optimization model. The results show that the scheduling strategy for energy consumption reduces the daily operating cost by 45% and that about 22% of energy is saved in the system.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1024016
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