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<p>In the proposed system, a strategy for the control of energy consumption by home appliances is provided. The statistics of previous energy production and consumption of a case study city are used in providing the strategy. In the design of the proposed system, home appliances are categorized into three levels of priority, even though it can be more than three. In this article the control of energy consumption is achieved using a real time energy consumption manager (ECM) based on stored data without the need for real time communication. The system which is proposed here is affordable and simple. Also, it does not require grid upgrade or power line communication through the grid. </p>

Solar photovoltaic (PV) farm output power is highly related to the panel conditions. Soiling causes faults in the PV panels leading to a dras-tic reduction in the system efficiency. In vast solar PV farms, the detection of faults in an individual PV panel is a difficult task since it is usually done manually. In this research, a new design is proposed to detect the production of individual PV panel automatically and periodically to evaluate the condition of each panel in the farm no matter how it is connected in the array. The proposed design allows the user to measure the open circuit voltage (VOC), the short circuit current (ISC) and the delivered power for each PV panel in the farm. It is also capable of controlling each panel to work at the maximum power point using a built in Maximum Power Point Tracking (MPPT) sub-circuit on each solar panel. The presented system depicts a complete wireless sensor network, which does not need any extra wiring and is character-ized by being of low cost, reliable and efficient.

While decreasing their cost, lithium-ion batteries began to enter a vast domain for energy storage field, including solar systems and electric vehicles, due to their high energy density compared to other types. Besides, li-ion batteries require a safe and secure ground to reach the best performance and decrease the explosion risk. The safe operation of the battery is based on the main protection features and balancing the cells. This study offers a battery BMS design that protects li-ion batteries from overcharging, over-discharging and overheating. It is also offering passive cell balancing, an uninterrupted power source to load, and monitoring data. The used controller is Arduino mega 2560, which manages all the hardware and software protection features. Software features that include 1) variable charging speed according to the batteries charging status, 2) measuring the batteries state of health and state of charge, 3) controlling the uninterrupted driver, 4) regulating the charge and discharge voltage, and 5) measure and display all readings.