SYSTEMS AND METHODS FOR MODEL-BASED SOLAR POWER MANAGEMENT
Systems and methods for predicting power output from photo-voltaic power generation resources are disclosed. An analytics server is communicatively connected to a data acquisition component and a virtual system model database. The analytics server is operable to receive real-time data via the data acquisition component from an electrical system comprising photo-voltaic power generation resources; generate predicted data based on a virtual model of the electrical system provided by the virtual system model database; continuously and automatically synchronize the virtual model with the electrical system based on a difference between the real-time data and the predicted data; receive solar irradiance forecast data; and forecast a power output of the photo-voltaic power generation resources based on the virtual model and the solar irradiance forecast data. The photo-voltaic power generation resources include at least one photo-voltaic inverter.
1 . A system for predicting power output from photo-voltaic power generation resources comprising:
an analytics server constructed and configured for communication with a data acquisition component and a database; and
an electrical system having at least one photo-voltaic (PV) power generation resource;
wherein the at least one PV power generation resource includes at least one PV inverter;
wherein the analytics server:
receives real-time data from the electrical system, the real-time data communicated by the data acquisition component;
generates predicted data based on a virtual model of the electrical system from the database;
synchronizes the virtual model with the electrical system real-time data based upon a difference between the real-time data and the predicted data;
receives solar irradiance forecast data; and
forecasts a power output of the at least one PV power generation resource based on the synchronized virtual model and the solar irradiance forecast data; and
communicates ramp-up and/or ramp-down control messages to the at least one PV inverter.
2 . The system of claim 1 , wherein the analytics server communicates Volt/VAR targets to the at least one PV inverter.
3 . The system of claim 1 , wherein the analytics server communicates frequency targets to the at least one PV inverter.
4 . The system of claim 1 , wherein the analytics server and the at least one PV generation resource are in two-way network-based communication with each other.
5 . The system of claim 1 , wherein the analytics server receives information from the at least one PV power generation resource.
6 . The system of claim 1 , wherein the analytics server communicates information about the at least one PV power generation resource to an energy market.
7 . The system of claim 1 , wherein the analytics server receives real-time power output data from the at least one PV power generation resource.
8 . The system of claim 1 , wherein the analytics server updates the virtual model when the difference between the real-time data and the predicted data exceeds a threshold.
9 . The system of claim 1 , wherein synchronizing of the virtual model with the real-time data of the electrical system is continuous and automatic.
10 . A method for predicting power output from photo-voltaic power generation resources comprising:
an analytics server receiving real-time data from an electrical system including at least one PV power generation resource, wherein the at least one PV power generation resource includes at least one PV inverter;
generating predicted data based upon a virtual model of the electrical system;
synchronizing the virtual model with the real-time data of the electrical system based upon a difference between the real-time data and the predicted data;
receiving solar irradiance forecast data;
forecasting a power output of the at least one PV power generation resource based on the virtual model and the solar irradiance forecast data; and
communicating ramp-up and/or ramp-down control messages to the at least one PV inverter.
11 . The method of claim 10 , further including sending Volt/VAR target messages to the at least one PV inverter.
12 . The method of claim 10 , further including sending frequency target messages to the at least one PV inverter.
13 . The method of claim 10 , further including the analytics server receiving messages from the at least one PV generation resource.
14 . The method of claim 13 , wherein the messages include real-time power output data from the at least one PV power generation resource.
15 . The method of claim 10 , further comprising updating the virtual model when the difference exceeds a threshold value.
16 . The method of claim 10 , wherein synchronizing the virtual model with the real-time data of the electrical system is continuous and automatic.
17 . A system for predicting power output from photo-voltaic power generation resources comprising:
an analytics server constructed and configured for communication with a data acquisition component and a database; and
an electrical system having at least one photo-voltaic (PV) power generation resource;
wherein the at least one PV power generation resource includes at least one PV inverter;
wherein the analytics server:
receives real-time data from the electrical system, the real-time data communicated by the data acquisition component;
generates predicted data based on a virtual model of the electrical system from the database;
synchronizes the virtual model with the electrical system real-time data based upon a difference between the real-time data and the predicted data;
receives solar irradiance forecast data; and
forecasts a power output of the at least one PV power generation resource based on the synchronized virtual model and the solar irradiance forecast data;
communicates ramp-up and/or ramp-down control messages to the at least one PV inverter;
wherein the analytics server communicates Volt/VAR targets to the at least one PV inverter; and
wherein the analytics server communicates frequency targets to the at least one PV inverter.
18 . The system of claim 17 , wherein the analytics server receives real-time power output data from the at least one PV power generation resource.
19 . The system of claim 17 , wherein the analytics server updates the virtual model when the difference between the real-time data and the predicted data exceeds a threshold.
20 . The system of claim 17 , wherein synchronizing of the virtual model with the real-time data of the electrical system is continuous and automatic.