NOVELTY - The method involves defining energy tolerance value for energy generation data for first energy resource. The energy generation data is monitored (312) and compared with historical energy generation data value. The alarm is raised, when energy generation data is not within range of historical data value and energy tolerance value. The determination is made whether second energy resource is in preset geographical area with current energy generation data which is not within range of historical data value and tolerance value for second energy resource in response to alarm.    USE - Method for managing distributed energy resources such as wind, fossil fuel, nuclear, solar, hydro, photovoltaic, battery, and geo-thermal based energy resource to predict or track weather parameter such as wind, temperature, solar irradiance, pressure, humidity and cloud coverage and weather conditions such as amount of sunlight, sky clarity, cloud, rain, and snow based on geographical location.    ADVANTAGE - The alarm is generated by the aggregator to a network operation center (NOC) such that the distributed energy resources is monitored to track an effect of weather conditions, and pattern of the effect based on the alarm, such that changes in energy generation can be predicted efficiently. The energy forecasting tool helps utilities and power system operators to predict the amount of generated energy when clouds and other weather-related factors reduces the intensity of incoming sunlight or wind at renewable energy facilities. Hence the utilities and operators are allowed to anticipate changes in renewable power production more accurately and take actions to ensure the stability of the national power grid. The administrators can detect slight performance degradation in the renewable energy source, such as system aging. The NOC can also predict the arrival of a certain wind speeds in a geographical area based on tracking of the pattern of the amount of the energy generated by the wind mills in a certain direction. The faulty, misplaced, or badly installed renewable energy resources can be identified in a faster and economical way. The large deployment of distributed energy resources can be scanned easily in less time and in a more efficient way. The algorithms can provide early warning to any sudden loss in the produced energy for solar and wind farms. Accurate forecasting of weather conditions are enabled, that help utilities and grid operators boost the reliability of their systems and reduce the cost of integrating renewable power plants into the grid.    DETAILED DESCRIPTION - INDEPENDENT CLAIMS are included for the following:    (1) a system for managing distributed energy resources; and    (2) a non-transitory computer readable storage medium storing program for managing distributed energy resources.    DESCRIPTION OF DRAWING(S) - The drawing shows a flowchart illustrating the method for managing distributed energy resources.    Step for collecting energy generation data from renewable energy sources (302)    Step for organizing energy generation data in database based on pre-defined categories (304)    Step for filtering energy generation data (306)    Step for storing filtered data in groups (308)    Step for monitoring energy generation value (312)