This paper proposes a novel framework for Home Energy Management System based on the combination of integer programming and Reinforcement Learning (RL) for achieving efficient home-based Demand Response (DR). In particular, RL is exploited to ...

• Reinforcement Learning is exploited for Battery Energy Storage System management.
• The problem decoupling allowed to ease of Reinforcement Learning training.
• 11.4% increase in self-consumption and 4.51% decrease in energy drawn from ...

This comprehensive study aims to assess the technical, financial, and policy implications of integrating solar power systems with battery storage in India. The research focuses on the commercial and industrial segments, investigating the viability ...

• Reducing load shedding by considering different DG and battery storage for peers, and central battery storage for the local grid.
• Dealing with uncertainty of energy generation and demand of peers by cardinality constrained robust ...

Peer-to-peer energy trading is one of the greatest systems that helps to increase the use of renewable energy, such as photovoltaics and wind turbines, in households due to the escalating environmental issues. This study designs a peer-to-peer ...

The proliferation of variable renewable energy increases the significance of reserve markets, which provide energy flexibility to compensate for supply–demand mismatches on short notice. Accordingly, market regulators in different ...

• Battery systems can considerably benefit from asymmetric bidding in reserve markets.

Fluctuations in the output power of photovoltaic (PV) under climate changes such as variations in temperature and radiation is an important challenge for these resources. Therefore, it is very important to keep the output power of solar systems ...

This paper evaluates the performance and suitability of four different metaheuristic algorithms for optimal sizing of standalone microgrids in remote area. The studied metaheuristic algorithms are particle swarm optimization, differential ...

We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure ...

This paper comprises of an effective Local Energy Management System (LEMS) implementing the Generalized Power Prediction Model (GPPM) for the uncertain performance of various Distributed Generations of a microgrid. The primary DGs ...

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• A novel local Energy management system for PV–Wind–Battery microgrid is proposed.