Efficient Archietecture for Effective Utilization of Harvested Power in Microscale Energy Harvesting

Recent developments in combining sensors, microprocessors, and radio frequency (RF) communications holds the potential to revolutionize the way we monitor and maintain critical systems. In the future, literally billions of wireless sensors may become deeply embedded within machines, structures, and the environment. Sensed information will be automatically collected, compressed, and forwarded for condition based maintenance. Energy Harvesting comprises a promising solution to one of the key problems faced by battery-powered Wireless Sensor Networks, namely the limited nature of the energy supply (finite battery capacity). By harvesting energy from the surrounding environment, the sensors can have a continuous lifetime without any needs for battery recharge or replacement

Solar energy management system with supercapacitors for rural application

Growing energy demands are expected to exceed the supply from current energy resources. Therefore, renewable energy and energy management systems will become more crucial for increasing supply and efficiency of energy usage. The novelty of this research is an energy management system (EMS) based on fuzzy logic for a solar house to ensure the maximum utilisation of renewable sources, protect components from being damaged due to overloading, and manage energy storage devices to increase stability in the power system. There is no published analysis of hybrid energy storage between battery and supercapacitor using fuzzy logic as EMS. The energy management system is implemented in a solar cabin system developed by IBC Solar to mimic a typical rural house. The solar cabin is equipped with solar photovoltaic panels, solar charger, battery and inverter. Supercapacitors and a custom made DC to DC converter were added to the system to support the batteries during high current load demand and manage energy flow. Three sets of experiments were conducted in the solar cabin system with the new energy management system. Power consumption usage of a typical rural household was studied to create two load profiles that were used as load for the experiments. The results show an efficiency of 95.9% by using the new energy management system and supercapacitors to the solar cabin, which is higher than recent research (95.2% and 84.4%). The result is on par with the Malaysian and International Standard in energy efficiency of around 95%. The energy management system controlled the charging and discharging of the battery and supercapacitor using fuzzy logic. The novelty of this thesis is use of supercapacitors to reduce stress on the battery and an energy management system to control and manage the system for efficient energy usage

Solar energy management system with supercapacitors for rural application

Growing energy demands are expected to exceed the supply from current energy resources. Therefore, renewable energy and energy management systems will become more crucial for increasing supply and efficiency of energy usage. The novelty of this research is an energy management system (EMS) based on fuzzy logic for a solar house to ensure the maximum utilisation of renewable sources, protect components from being damaged due to overloading, and manage energy storage devices to increase stability in the power system. There is no published analysis of hybrid energy storage between battery and supercapacitor using fuzzy logic as EMS. The energy management system is implemented in a solar cabin system developed by IBC Solar to mimic a typical rural house. The solar cabin is equipped with solar photovoltaic panels, solar charger, battery and inverter. Supercapacitors and a custom made DC to DC converter were added to the system to support the batteries during high current load demand and manage energy flow. Three sets of experiments were conducted in the solar cabin system with the new energy management system. Power consumption usage of a typical rural household was studied to create two load profiles that were used as load for the experiments. The results show an efficiency of 95.9% by using the new energy management system and supercapacitors to the solar cabin, which is higher than recent research (95.2% and 84.4%). The result is on par with the Malaysian and International Standard in energy efficiency of around 95%. The energy management system controlled the charging and discharging of the battery and supercapacitor using fuzzy logic. The novelty of this thesis is use of supercapacitors to reduce stress on the battery and an energy management system to control and manage the system for efficient energy usage

Zonal Energy Management and Optimization System (ZEMOS) for Smart Grid Applications

In the context of implementing the smart grid, electric energy consumption, generation resources, should be managed and optimized in a way that saves energy, improves efficiency, enhances reliability and maintains security while meeting the increasing demand at minimum operating cost. In order to achieve these objectives, there is a need to implement an efficient Zonal Energy Management and Optimization Systems (ZEMOS) that address both existing and future challenges possibly imposed by the use of renewable energy generators that lead to bi-directional power flow instead of unidirectional as in the traditional grids while operate in a coordinated way for the benefit of the whole electric grid. The proposed ZEMOS contains custom defined built-in functions in modular form, which could easily be integrated with other existing energy monitoring systems in the zone of interest (i.e. industrial facility, commercial centers, testing facility, sub-system of the utility service area, educational institutions, power plant, etc.). The proposed ZEMOS provides functions that ensure energy saving, improved reliability, increased efficiency and enhanced utilization of distributed resources: generation energy storage and loads without compromising the tasks carried within that zone. Those module-based systems are characterized by their scalability and flexibility, since more functions can be added down the road as needed. This is necessary in order to accommodate the constant changes imposed by the smart grid and avoid the need to change the whole infrastructure. The proposed ZEMOS performance was investigated for study zones that involve single and multi-objective operations. Besides, study zones with more than single decision makers were also considered in this thesis. Accordingly, the implementation of ZEMOS satisfies the outlined objectives for specific study zone which leads to a reduction in greenhouse gas emission, the improvement of the energy generation portfolio, a reliance on the optimized renewable energy source and a reduction in the energy losses while ensuring high power quality. Furthermore, managing the energy consumption and optimizing the operation of such sizable zones (at Mega Watts scale) ensures significant economic benefits in terms of energy saving, better utilization of available resources, improving the efficiency of energy systems, and exporting novel smart grid technologies, which will lay the foundation to meet future challenges using existing infrastructure