Abstract:The role of Demand Side Management (DSM) with Distributed Energy Storage (DES) has been gaining attention in recent studies due to the impact of the latter on energy management in the smart grid. In this work, an Energy Scheduling and Distributed Storage (ESDS) algorithm is proposed to be installed into the smart meters of Time-of-Use (TOU) pricing consumers possessing in-home energy storage devices. Source of energy supply to the smart home appliances was optimized between the utility grid and the DES device depending on energy tariff and consumer demand satisfaction information. This is to minimize consumer energy expenditure and maximize demand satisfaction simultaneously. The ESDS algorithm was found to offer consumer-friendly and utility-friendly enhancements to the DSM program such as energy, financial, and investment savings, reduced/eliminated consumer dissatisfaction even at peak periods, Peak-to-Average-Ratio (PAR) demand reduction, grid energy sustainability, socio-economic benefits, and other associated benefits such as environmental-friendliness.
The contributions of Distributed Energy Generation (DEG) and Distributed Energy Storage (DES) for Demand Side Management (DSM) purposes in a smart macrogrid or microgrid cannot be over-emphasised. However, standalone DEG and DES can lead to under-utilisation of energy generation by consumers and financial investments; in grid-connection mode, though, DEG and DES can offer arbitrage opportunities for consumers and utility provider(s). A grid-connected smart microgrid comprising heterogeneous (active and passive) smart consumers, electric vehicles and a large-scale centralised energy storage is considered in this paper. Efficient energy management by each smart entity is carried out by the proposed Microgrid Energy Management Distributed Optimisation Algorithm (MEM-DOA) installed distributively within the network according to consumer type. Each smart consumer optimises its energy consumption and trading for comfort (demand satisfaction) and profit. The proposed model was observed to yield better consumer satisfaction, higher financial savings, and reduced Peak-to-Average-Ratio (PAR) demand on the utility grid. Other associated benefits of the model include reduced investment on peaker plants, grid reliability and environmental benefits. The MEM-DOA also offered participating smart consumers energy and tariff incentives so that passive smart consumers do not benefit more than active smart consumers, as was the case with some previous energy management algorithms.
South Africa has about 2.5 million households without electricity access, most of which are located in rural areas and urban informal settlements. The nexus of energy poverty and gender is at play in the affected communities, as women and girls are culturally stereotyped with the task of collecting unclean fuels (e.g., firewood) and using these for their households’ energy demands. Therefore, this study prioritized rural women and girls as respondents in the provinces most affected by gendered energy poverty (GEP) in the country. The study was carried out in selected rural unelectrified areas of Limpopo, Mpumalanga, and KwaZulu-Natal provinces using structured interviews. The study revealed that GEP in the rural areas has exposed women and girls living there to security concerns, health hazards, premature death, domestic fire accidents, time poverty, income poverty, illiteracy, drudgery in households and farm tasks, etc., at different levels of severity. It also showed the effects of perceptions, age, income, and culture on the choice of energy use among the respondents. Mitigation strategies against GEP in rural South African communities through clean energy adoption are also proposed in this paper.
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