Аннотация
Nomadic communities often reside in remote regions requiring extensive transmission infrastructure, which is costly and contributes to higher greenhouse gas emissions. This study proposes a hybrid microgrid (MG) for the Shell Yurt Center, a representative nomadic dwelling in Kazakhstan. The system integrates renewable energy sources (RESs), including photovoltaic (PV), wind turbines (WT), and battery energy storage systems (BESS), to deliver a reliable and cost-effective energy supply. An analysis of a home energy management system (HEMS) is conducted using real-time data of the Yurt to support efficient demand-side management (DSM). The HEMS is designed to enhance energy efficiency and reduce overall energy costs through the smart scheduling of household appliances. Dynamic Programming (DP) and Genetic Algorithm (GA) are applied to manage energy usage under an unscheduled electricity pricing rate of $0.583/kWh. Three scenarios are examined: Case 1 (minimal appliance usage with RESs), Case 2 (average demand with maximum appliance usage), and Case 3 (extreme demand conditions, with and without hardware optimization). GA consistently outperforms DP in Case 1, reducing the net present cost (NPC) by 1.1% ($44,319 vs. $43,832), levelized cost of electricity (LOCE) by 1.2% ($0.418/kWh vs. $0.413/kWh), and maintenance costs by 2.2%. In Case 2, DP has a slight edge in NPC and LOCE, but GA maintains favorable maintenance costs. For Case 3, GA with hardware optimization achieves the lowest NPC ($41,671), LOCE ($0.393/kWh), and maintenance costs ($456/year). Overall, the study established an optimal scheduling framework for renewable energy utilization for nomadic dwellers using a fully functioning MG complex.