An intelligent energy management system for optimum design and real-time operation

<span lang="EN-US">Planning and management of distribution networks has become a very difficult task, especially with the strong expansion renewable energy sources (RES) which are intermittent in nature. Maintaining fluidity reliability real-time decisions while taking into consideration uncertainties related to production increasing profit network operators is objective system proposed this work. It an intelligent dedicated grid-integrated RES battery storage systems (BESS), composed of: i) control data acquisition model, ii) model for forecasting parameters based on neural networks, iii) long-term planning optimal placement size BESS, iv) hourly scheduling between sources. The non-dominated sorting genetic algorithm entropy-TOPSIS method (technique order preference by similarity ideal solution) form basic block model. To evaluate it, modified IEEE 33 bus was used testing results, short-term scheduling, proved that succeeds maximizing profits significantly minimizing CO<sub>2</sub> emissions, addition power losses voltage drops.</span>