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This work aims to develop a methodology to perform the active demand side management for households in smart grids, which contain distributed solar photovoltaic generation and energy storage. Such methodology outcomes a decision-making system that manages the battery aiming to reduce the consumer electricity cost. It also contributes to postpone the investments in expansion of the electricity grid if the higher loading period coincides with the higher electricity tariff of the day. The decision-making system is a validated neural network, trained with optimized data, which can be used in any household meeting certain conditions – specific location and electricity tariff, and consumption profile like to the standard verified by the local electricity utility. To validate this methodology, it was created three consumption and three solar generation profiles, which were combined to each other. The results show that the ANN-based decision-making system operates the battery efficiently to achieve the minimum electricity bill. [ABSTRACT FROM AUTHOR]

Predicting the peak load contributes to the enhancement of energy management. This paper presents some models to forecast the peak load of a campus of the University of São Paulo, aiming to choose the best one for generalization. The developed models were linear and non-linear, respectively, linear regression and Artificial Neural Networks and Adaptive Neural Networks Inference Systems. The data used was power demand, weather variables and calendar data, which were treated and normalized. For non-linear models, differentially of other researches, the goal of this work is the used of only one network for forecast model from the introduction of a new variable that differentiates the type of day, if is weekday or not. The results obtained reports a good coincidence between the predicted and real peak load for all developed models, however the accuracy is better for non-linear models, mainly for Adaptive Neural Networks Inference Systems. [ABSTRACT FROM AUTHOR]

The paper presents a literature review on smart grid concepts, considering generation, transmission and distribution of electricity besides smart consumption, including smart home, Demand-Side Response Programs, and Active Demand-Side Management. An analysis of the smart grid development in Brazil is performed, presenting the policy and regulation efforts beyond investments. This analysis takes account a pattern for smart grid development, and one may observe that Brazil is going towards a smart grid full implementation; however it could take decades and requires adjusts from govern, regulatory agency, utilities and consumers, and more investments. Moreover, some of the major smart grid projects in Brazil are presented, and their characteristics are compared considering the technologies used, location and electric utility goals. Depending on the electric utilities objectives, one may observe similarities and differences between concepts adopted and location of the Brazilian smart grid pilot projects. The first objective is the validation and replicability of the pilot project implemented; once, the project location is a sample of the utility׳s energy market or it is a particular area of interest, like an off-grid powered island with high environmental restrictions, for instance. The second objective is creating a model of sustainable smart grid with national visibility, once the project location is a touristic place. The conception of smart grid is aligned with sustainability, and it is a tendency in Brazil a massive entry of smart grid technologies in the next years. [ABSTRACT FROM AUTHOR]