Demand response in a renewable energy-based grid infrastructure

Abstract

In a renewable energy-based electricity grid infrastructure, distributed data analytics and artificial intelligence enable modeling and delivery of an appropriate, time-sensitive, dynamic demand response from multiple renewable energy resource components to an intelligent power distribution network. Distributed data analytics also enable the electricity grid infrastructure to virtually, optimally and adaptively make decisions about power production, distribution, and consumption so that a demand response is a dynamic reaction across the electricity grid infrastructure in a distributed energy generation from multiple renewable energy resources responsive to

1 . A method of providing power within a renewable energy-based electricity grid infrastructure, comprising:
 identifying a power requirement over a specified period of time for a power distribution network, and an operational capacity of a plurality of renewable energy components over the specified period of time at one or more offshore renewable energy installations each having the plurality of renewable energy components configured thereon;   predicting one or more of commodity pricing for power derived from the plurality of renewable energy components, meteorological conditions at the one or more offshore renewable energy installations, power usage patterns of the power distribution network, and an operational capacity of the plurality of renewable energy resource components, to forecast satisfaction of the power requirement over the specified period of time using the plurality of renewable energy components configured at the one or more offshore renewable energy installations; and   delivering a combined power output of the plurality of renewable energy components as a response to the power requirement from the one or more offshore renewable energy installations to the power distribution network,   wherein the one or more offshore renewable energy installations each include a wind component, a photovoltaic component, a hydrokinetic component, and a solar thermal component that together comprise the plurality of renewable energy components.   
     
     
         2 . The method of  claim 1 , wherein the specified period of time is at least one of a time within which power is to be consumed by the power distribution network and a time within which power is to be produced by the one or more offshore renewable energy installations. 
     
     
         3 . The method of  claim 1 , wherein the specified period of time is identified by at least one of the power distribution network and the one or more offshore renewable energy installations. 
     
     
         4 . The method of  claim 1 , wherein the delivering a combined power output further comprises transferring the combined power output over a power transmission system coupling the power distribution network to the one or more offshore renewable energy installations. 
     
     
         5 . The method of  claim 1 , wherein the one or more offshore renewable energy installations comprise a temporary power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         6 . The method of  claim 1 , wherein the one or more offshore renewable energy installations comprise a mobile power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         7 . The method of  claim 1 , wherein the wind component comprises at least one wind turbine, the photovoltaic component comprises at least one photovoltaic module, the hydrokinetic component comprises at least one of a surface wave turbine, an oscillating column, and an undersea wave turbine, and the solar thermal energy component comprises at least one high-temperature solar thermal collector. 
     
     
         8 . The method of  claim 1 , further comprising a shared, secure and privately-hosted computing environment that includes a plurality of computing resources comprising at least one artificial neural network trained to heuristically model the power requirement and the predicting the one or more of commodity pricing for power derived from the plurality of renewable energy components, the meteorological conditions at the one or more offshore renewable energy installations, the power usage patterns of the power distribution network, and the operational capacity of the plurality of renewable energy resource components. 
     
     
         9 . A system comprising:
 a power distribution network and one or more offshore renewable energy installations, the one or more offshore renewable energy installations each including a wind component, a photovoltaic component, a hydrokinetic component, and a solar thermal component that together comprise a plurality of renewable energy components, each of the one or more offshore renewable energy installations having the plurality of renewable energy components configured thereon;   a power realization component configured to identify a power requirement over a specified period of time identified from the power distribution network; and   an artificial intelligence component configured to continually predict one or more of commodity pricing for power derived from the plurality of renewable energy components, meteorological conditions at the one or more offshore renewable energy installations, power usage patterns of the power distribution network, and an operational capacity of the plurality of renewable energy resource components, to forecast satisfaction of the power requirement over the specified period of time using the plurality of renewable energy components configured at the one or more offshore renewable energy installations.   
     
     
         10 . The system of  claim 9 , further comprising a power transmission system configured to deliver a combined power output from the plurality of renewable energy components as a response to the power requirement from the one or more offshore renewable energy installations to the power distribution network. 
     
     
         11 . The system of  claim 9 , wherein the one or more offshore renewable energy installations comprise a temporary power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         12 . The system of  claim 9 , wherein the one or more offshore renewable energy installations comprise a mobile power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         13 . The system of  claim 9 , wherein the specified period of time is at least one of a time within which power is to be consumed by the power distribution network and a time within which power is to be produced by the one or more offshore renewable energy installations. 
     
     
         14 . The system of  claim 9 , wherein the wind component comprises at least one wind turbine, the photovoltaic component comprises at least one photovoltaic module, the hydrokinetic component comprises at least one of a surface wave turbine, an oscillating column, and an undersea wave turbine, and the solar thermal energy component comprises at least one high-temperature solar thermal collector. 
     
     
         15 . The system of  claim 9 , further comprising a shared, secure and privately-hosted computing environment that includes a plurality of computing resources comprising at least one artificial neural network trained to heuristically model the power requirement and the one or more of commodity pricing for power derived from the plurality of renewable energy components, the meteorological conditions at the one or more offshore renewable energy installations, the power usage patterns of the power distribution network, and the operational capacity of the plurality of renewable energy resource components. 
     
     
         16 . A method comprising:
 requesting a power requirement over a specified period of time from a power distribution network, and an operational availability for the specified period of time from each individual component in a plurality of renewable energy components configured at the one or more offshore renewable energy installations, each individual component having an independent and variably adjustable level of operation;   predicting one or more of commodity pricing for power derived from the plurality of renewable energy components, meteorological conditions at the one or more offshore renewable energy installations, power usage patterns of the power distribution network, and an operational capacity of the plurality of renewable energy resource components, to forecast satisfaction of the power requirement over the specified period of time using the plurality of renewable energy components configured at the one or more offshore renewable energy installations;   determining an appropriate power production from the operational capacity to satisfy the power requirement for the specified period of time, the appropriate power production comprised of a combined power output of the plurality of renewable energy components, wherein the determining the appropriate power production includes a enforcing a constraint that the combined power output be produced from at least two of a wind component, a photovoltaic component, a hydrokinetic component, and a solar thermal component that together comprise the plurality of renewable energy components configured at the one or more offshore renewable energy installations; and   initiating the appropriate power production from the one or more offshore renewable energy installations for the specified period of time.   
     
     
         17 . The method of  claim 16 , wherein the one or more offshore renewable energy installations comprise a temporary power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         18 . The method of  claim 16 , wherein the one or more offshore renewable energy installations comprise a mobile power production apparatus within a renewable energy-based electricity grid infrastructure. 
     
     
         19 . The method of  claim 16 , further comprising a shared, secure and privately-hosted computing environment that includes a plurality of computing resources comprising at least one artificial neural network trained to heuristically model the power requirement and the one or more of commodity pricing for power derived from the plurality of renewable energy components, the meteorological conditions at the one or more offshore renewable energy installations, the power usage patterns of the power distribution network, and the operational capacity of the plurality of renewable energy resource components.