Modelling of electricity spot price and load forecast based new energy management system for households

The aim was to determine probable profit by using electric energy storage (EES) device in a typical household. Focus is on theoretical and practical studies of an energy management system (EMS) based on VRLA battery storage. Use of a battery charge-discharge-schedule (BCDS) enables an optimal operation of EES taking advantage of the low price periods by importing more energy and storing it, while reducing the imported power during high price periods by supporting the load with the stored energy. Forecasted price and load are used to optimize the BCDS of EES, at the same time ensuring load demand supply. In the day-ahead market, the management system uses the mathematical functions to calculate the price of imported energy in each period of time with the day-ahead forecasted price and typical load in the household. The recursion loops in the optimization algorithm search for the best BCDS to reach the highest profit for the end consumer. All the calculations will be tested on the EMS to confirm the theoretical part.