Mini-grids powered by photovoltaic generators or other renewable energy sources have the potential to bring electricity to the 17% of the world's population, mainly in rural areas, that are currently un-served. However, designing and managing a mini-grid so that it is reliable and economically sustainable is difficult because of the high variability of demand that arises from the small population of consumers. We describe an integrated set of four tools to assist mini-grid operators to predict and manage demand. These comprise a decision support tool to predict peak and average demand from a consumer population, a demand disaggregation tool that allows the key statistical properties of connected electricity-consuming appliances to be identified, a battery condition modeling tool which allows the impact on battery life of a planned operating regime to be predicted and a demand control sub-system which limits the operating time of high demand appliances to intervals when they can be supported. Results from application of the tool set to mini-grids in Kenya and The Gambia are presented. We conclude that accessible, usable and low cost tools of this form can improve mini-grid sustainability.
Abstract-Stand-alone mini-grids provide vital energy access to rural communities across the Developing World where economic constraints necessitate optimal cost-effectiveness without compromising reliability or quality of service. Managing electricity demand to match supply availability -for example, by incentivizing consumers to operate loads at specific timescan contribute to this aim. This paper addresses a method to achieve this, whereby timeslots are sold in which additional power is made available to participating consumers with highpowered, commercial loads, such as grain mills. Using a low-cost microprocessor to control remotely-switchable power sockets by wireless communications, circuits are activated according to the timeslots purchased without interruption of low-power (e.g. lighting and phone-charging) circuits. Informed by site survey data, laboratory tests demonstrated the system to be reliable and effective in maintaining demand closer to supply availability while avoiding overloads. This reduces losses and the need for storage while increasing energy access and return on investment.
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