Operational benefits from smart grid are to some extent the knowledge that's extracted from the big data arriving from smart meters to the meter data management system (MDMS). Smart grid cost is high and the development of ongoing operational benefits is a way to fund part of that cost, as well as to provide new sources of income to utility companies, transferring from a monopoly to liberalized market. From the research point of view, development of operational benefits involves serious scientific creative understanding, and electric algorithms development. Once identifying the potential, there's in addition a development of how to use existing electric knowledge for these applications. In this paper four algorithms are presented: the first are algorithms for remote reverse extraction of grid load structure as a black-box. The second is a non-intrusive load forecasting algorithm sensitive to weather and special days. The third is an algorithm for urban fault location and for low voltage grid real-time fault alert that is both national and urban wide and yet exploits existing infrastructure. The fourth and last is an algorithm for optimal energy management: national, district, and specialized niches such as PV to Grid, EV to Grid. Again identification of novel implementations combined with novel algorithm.