Abstract
The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reduction.
Highlights
Over the last decade, residential rooftop photovoltaic (PV) systems have gained popularity in many countries [1]
This paper focuses on low voltage (LV) network integration with solar PV and a battery energy storage system (BESS) system
The capacity of the PV system installed for each house was assigned randomly based on the statistics obtained from the Sustainable Energy Development Authority (SEDA) Malaysia
Summary
Residential rooftop photovoltaic (PV) systems have gained popularity in many countries [1]. It is worth noting that none of these papers consider the concept of battery-autonomy days in determining the optimal BESS capacity This is important as the solar PV generation varies in consecutive days. Each house is assigned with an individual load profile with actual annual solar generation profiles This allows the PV–BESS studies to be carried out more realistically, as compared to the abovementioned papers, which only consider a simplistic network model with daily or weekly profiles. An optimal operation of centralized control of battery energy storage in low voltage networks with a few hundred nodes is computationally infeasible [19] This is because the optimization problem becomes too complex to be solved efficiently.
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