Computer-based smart energy management system for rural health centers

Access to reliable source of electricity remains a challenge for rural areas in developing and under-developed countries. To address this challenge, health centers in underserved communities adopted off-grid photo-voltaic (PV) systems. Standalone PV systems were identified to be relatively cost effective compared to grid extension. To reduce the cost of solar systems the size of batteries must be minimized. Currently, most of the PV powered health centers serve patients as they come. This first come first served model does not allow the centers to harness the power generated by PV systems at maximum level. With minimum sizing of the battery in the systems some energy is left unused when there are a small number of patients who need electricity dependent services. There are also shortages of energy when the power required by the services exceeds the generation capacity of the PV systems. Although PV systems might be considered as an adequate solution to shortage of reliable source of energy, its maximum exploitation requires an efficient management of services using it. To alleviate the logistic management and to maximize the number of services provided by PV powered health centers in underserved community, the Smart Energy Management for Health Centers (SEMHC) model was developed. This paper shows the design and implementation of SEMHC computer system. The system is comprised of a computer server and access terminals. The server uses the developed scheduling algorithm to allocate a time for each of electricity dependent health services based on its electric power requirement, its time duration and the expected PV generated power. The access terminals, which could be smart phones or laptop computers, are used by healthcare providers to input the services and get the schedule from the server. The data about energy consumption and services being provided by centers are collected over time. The collected data allows learning the energy consumption behaviors of health centers and provides insight on correlation of the delivered health services and the sizing of the PV-battery systems. It can also be used as reference for planning for new PV systems or upgrading existing one.