Development of energy management system for load centers with renewable energy resources and electric vehicles in post-disaster situations

With the increasing frequency and intensity of natural disasters, energy infrastructure faces significant challenges, leading to disruptions that adversely affect the well-being and safety of individuals. Although numerous studies in literature address grid resilience through tools such as demand response and load curtailment, few have investigated energy management at the household level. To address this gap, this study proposes novel energy management system (EMS) frameworks that integrate renewable energy systems (RES), electric vehicle batteries (EVB), and multi-level load classifications to optimize energy utilization and ensure continuity under adverse conditions. First, a home energy management system (HEMS) is introduced to dynamically control household loads based on their criticality and the predicted remaining energy (PRE) of EVBs. The proposed HEMS ensures uninterrupted power supply to critical loads during post-disaster conditions by periodically updating PRE values and adapting to real-time changes in energy generation and consumption. This system enhances occupant comfort and prevents unexpected interruptions by effectively managing available resources for 24-hour periods under the worst-case scenarios. The proposed system achieves a 19.5-hour extension in the energy supply for critical loads compared to conventional methods. Furthermore, the proposed HEMS ensures a minimum EVB energy reserve of 2.67 kWh, enabling post-disaster mobility of at least 14.35 km, which is unattainable with conventional systems that deplete the entire energy reserve. On average, the proposed HEMS improves the duration of uninterrupted energy supply by 241%, with a maximum improvement of 4.71 times in specific scenarios. Furthermore, a building energy management system (BEMS) is developed to enhance resilience in multi-unit residential buildings during post-disaster events. The proposed BEMS ensures a fair share of benefits among occupants by leveraging a hierarchical structure and optimizing energy distribution based on the unique characteristics of each household. The system integrates rooftop photovoltaic (PV) systems as shared energy sources and EVBs as individual energy reserves. Using a mixed-integer linear programming (MILP) framework, the study models household load profiles and schedules energy distribution to maximize occupant well-being while maintaining fairness. The system achieves a 26.44% reduction in the standard deviation of benefit index among occupants. This improvement ensures equitable energy distribution while extending uninterrupted power supply during post-disaster scenarios. On average, the proposed BEMS extends energy availability by 91.2%, equating to an additional 11 hours and 26 minutes of uninterrupted supply compared to conventional approaches. Moreover, EVBs maintain a minimum reserve of 2 kWh, supporting post-disaster mobility for distances of up to 10.75 km. Additionally, an adaptive HEMS (A-HEMS) is designed to address the challenges posed by variable power limitations and dynamic microgrid boundaries in islanded microgrids resulting from natural disasters. By employing a dynamic load control algorithm, A-HEMS improves the utilization of limited power resources while improving occupant well-being. Experimental validations confirm the system's ability to significantly extend the duration of energy supply and adapt to variable conditions, thereby ensuring continuity for critical loads and minimizing disruptions. In real-world conditions, the A-HEMS extends the duration of energy supply by 18 hours and 26 minutes compared to conventional methods. Experimental validation demonstrates exceptional accuracy, with deviations in EVB energy predictions ranging from just 0.01% to 1.03%. These findings underscore the robustness and reliability of the A-HEMS in ensuring continuous power supply and adapting to unforeseen events. This dissertation makes significant contributions to the field of energy management by introducing dynamic and adaptive systems that address key challenges in post-disaster scenarios. The proposed frameworks effectively extend the duration of energy supply, optimize the utilization of renewable energy resources, and ensure equitable energy distribution. By demonstrating both theoretical advancements and practical applicability, this study provides robust solutions for enhancing energy resilience at the household and building levels, offering a substantial step forward in mitigating the impact of disasters on residential energy systems.