Optimizing demand-side energy management for stand-alone wind-solar microgrids in rural settlements: A case study for nomadic Yurt in Kazakhstan

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 turbine (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 as a baseline without using any optimization. Three scenarios are examined: Case 1 (minimal appliances with normal usage), Case 2 (maximum appliances with average usage), and Case 3 (maximum appliances with extreme usage). GA consistently outperforms DP in Case 1, resulting in reduced net present costs (NPC), levelized cost of electricity (LCOE), and lower maintenance costs. In Case 2, DP has a slight edge in NPC and LCOE, but GA maintains favorable maintenance costs. Case 3 shows that GA achieves the lowest NPC ($42,028), LCOE ($0.396/kWh), and maintenance costs ($466/year). Overall, the study establishes an optimal scheduling framework for renewable energy (RE) utilization for nomadic dwellers using a fully functioning MG complex.