A method for distributed intelligence of power tracking and power allocation, the method executable by at least one computer including at least one processor and memory, the method comprising: receiving data, by the at least one computer, from a plurality of identified charging stations and electric vehicles of customers at distributed locations throughout a power grid, wherein the received data comprises selections from the customers to enable scheduling charging times, scheduling charging locations, and scheduling charging durations to charge the electric vehicles; receiving a plurality of system and charging infrastructure parameters from power grid assets; analyzing, with the at least one processor, the data with respect to available power for those locations and customer historical usage and profiles, where analyzing further comprises determining, from the parameters, whether there is sufficient power availability within the power grid to support charging the electric vehicles at locations of the charging stations within the power grid; and sending commands, with the at least one processor, to reallocate power to the assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on the analysis, wherein each asset of the power grid is one of: * an electric vehicle; * a charging station; * a renewable energy source; * a substation; * a transformer; and characterised in that the method further comprises * simulating actual conditions in the power grid, * tracking individual smart meters within charging stations and within identified electrical vehicles such that scheduling can be coordinated or suggested to customers, * dealing with intermittent supplies of power, * controlling through sensing, analytics and automation virtual generators using forms of dynamic voltage and capacitance, wherein voltage profiles are flattened or tightened by adding additional voltage regulators to the distribution system, and the voltage profile is moved up or down within operational voltage bounds, * managing power flow requirements to and from assets in the power grid, and * executing loss minimization to reduce power losses inherent in lines and loads of the power grid. receiving data, by the at least one computer, from a plurality of identified charging stations and electric vehicles of customers at distributed locations throughout a power grid, wherein the received data comprises selections from the customers to enable scheduling charging times, scheduling charging locations, and scheduling charging durations to charge the electric vehicles; receiving a plurality of system and charging infrastructure parameters from power grid assets; analyzing, with the at least one processor, the data with respect to available power for those locations and customer historical usage and profiles, where analyzing further comprises determining, from the parameters, whether there is sufficient power availability within the power grid to support charging the electric vehicles at locations of the charging stations within the power grid; and sending commands, with the at least one processor, to reallocate power to the assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on the analysis, wherein each asset of the power grid is one of: * an electric vehicle; * a charging station; * a renewable energy source; * a substation; * a transformer; and characterised in that the method further comprises * simulating actual conditions in the power grid, * tracking individual smart meters within charging stations and within identified electrical vehicles such that scheduling can be coordinated or suggested to customers, * dealing with intermittent supplies of power, * controlling through sensing, analytics and automation virtual generators using forms of dynamic voltage and capacitance, wherein voltage profiles are flattened or tightened by adding additional voltage regulators to the distribution system, and the voltage profile is moved up or down within operational voltage bounds, * managing power flow requirements to and from assets in the power grid, and * executing loss minimization to reduce power losses inherent in lines and loads of the power grid. * an electric vehicle; * a charging station; * a renewable energy source; * a substation; * a transformer; and characterised in that the method further comprises * simulating actual conditions in the power grid, * tracking individual smart meters within charging stations and within identified electrical vehicles such that scheduling can be coordinated or suggested to customers, * dealing with intermittent supplies of power, * controlling through sensing, analytics and automation virtual generators using forms of dynamic voltage and capacitance, wherein voltage profiles are flattened or tightened by adding additional voltage regulators to the distribution system, and the voltage profile is moved up or down within operational voltage bounds, * managing power flow requirements to and from assets in the power grid, and * executing loss minimization to reduce power losses inherent in lines and loads of the power grid.