Over 17% of the world’s population lack access to electricity, the majority being in rural areas of sub-Saharan Africa and South Asia. Microgrid technologies are a promising solution towards rural and remote area electrification; however, ever-increasing electricity demand remains a big challenge leading to pronounced power outages. Demand-side management is an indispensable tool towards addressing the challenges. This paper employs a mathematical model based on incentives and time-of-use rates to simulate daily power usage pattern of residential customers using data collected from an isolated village Ngurdoto solar microgrid, Arusha, Tanzania. Customer responsiveness on the increase in price was evaluated based on the concept of price elasticity of demand. Using two demand response strategies, namely, load shifting (LS) and scheduled load reduction (SLR), the results reveal that LS can achieve up to 4.87% energy-saving, 19.23% cost-saving, and about 31% and 19% peak reduction and power factor improvement, respectively. SLR method resulted in about 19% energy-saving, 49% cost-saving, and 24% power factor improvement. Thus, the results presented in this study may lead to a more efficient and stable system than the current state in developing countries’ utility.
Trade-offs between the quality of service, computational cost and cooling complexity in interference-dominated multi-user SDMA systems
