An optimal dispatching method and system for a wind power generation and energy storage combined system are provided. Uncertainty of a wind turbine output is characterized based on spatio-temporal coupling of the wind turbine output and an interval uncertainty set. Compared with a traditional symmetric interval uncertainty set, the uncertainty set that considers spatio-temporal effects effectively excludes some extreme scenarios with a very small probability of occurrence and reduces conservativeness of a model. A two-stage robust optimal dispatching model for the wind power generation and energy storage combined system is constructed, and a linearization technology and a nested column-and-constraint generation (C&CG) strategy are used to efficiently solve the model.

A graphical workflow definition and management tool enables administrators and other authorized users to implement a workflow process that can be used to evaluate project submissions or other applications that require step-by-step process completion. The steps required to navigate through the workflow are first defined. Inputs, outputs, and actions, including conditional criteria, can be specified for the steps. The flow of control between the individual steps in the workflow is mapped out; changes to the status of a project submission can cause a submission to migrate to a succeeding step in the workflow. A “sandbox” testing environment allows changes to any aspect of the workflow to be safely evaluated without affecting live data. Conflicts between production and test workflows are identified and intelligently resolved.

A power storage control system includes a storage battery and a controller. The storage battery supplies electric power to an electric power system in collaboration with a power generator in response to a command value. The controller outputs, to the power generator, a stop signal causing the power generator to stop power generation when a state of charge of the storage battery is larger than a given value. The controller outputs, to the power generator, an execution signal causing the power generator to execute power generation when the state of charge is not larger than the given value. The controller acquires an actual electric power value generated by the power generator. The controller outputs a control signal causing the storage battery to execute charging and discharging for satisfying the command value on the basis of a difference between the command value and the actual electric power value.

Provided is an information processing method performed by an information processing apparatus, the information processing method including: acquiring contract information on a contract related to a disaster prevention project to develop an infrastructure, the contract being an outcome-based contract in which payment is made on a basis of a disaster reduction outcome through the infrastructure (S102); acquiring fund data related to a fund set on a basis of the contract information (S110); and associating the fund data with discrimination information on the disaster prevention project (S116).

Various implementations power homes and businesses without needing to connect to electric utility company-provided power, i.e., they can operate off-grid. Generally the system includes solar panel racks (e.g., photovoltaic cells on sheets stabilized using ballasts, anchors, or mounting) that generate electrical power used to provide power to a building or that is stored on batteries. The system includes the solar panel racks and an enclosure to be installed at the premises and separate from the building. The enclosure includes the batteries and inverters that are electronically connected to the solar panel racks and batteries. The inverters are configured to convert direct current (DC) electricity from the solar power racks and batteries to alternating current (AC) electricity to provide power to the building via wires electrically connecting the inverters to the main panel of the building.

In some embodiments, the system is directed to an autonomous inspection system for electrical grid components. In some embodiments, the system collects electrical grid component data using an autonomous drone and then transmits the inspection data to one or more computers. In some embodiments, the system includes artificial intelligence that analysis the data and identifies electrical grid components defects and provides a model highlighting the defects to a user. In some embodiments, the system enables a user to train the artificial intelligence by providing feedback for models where defects or components are not properly identified.

An optimal dispatching method and system for a wind power generation and energy storage combined system are provided. Uncertainty of a wind turbine output is characterized based on spatio-temporal coupling of the wind turbine output and an interval uncertainty set. Compared with a traditional symmetric interval uncertainty set, the uncertainty set that considers spatio-temporal effects effectively excludes some extreme scenarios with a very small probability of occurrence and reduces conservativeness of a model. A two-stage robust optimal dispatching model for the wind power generation and energy storage combined system is constructed, and a linearization technology and a nested column-and-constraint generation (C&CG) strategy are used to efficiently solve the model.

A method, apparatus, system and computer program is provided for controlling an electric power system, including implementation of a voltage control and conservation (VCC) system used to optimally control the independent voltage and capacitor banks using a linear optimization methodology to minimize the losses in the EEDCS and the EUS. An energy validation process system (EVP) is provided which is used to document the savings of the VCC and an EPP is used to optimize improvements to the EEDCS for continuously improving the energy losses in the EEDS. The EVP system measures the improvement in the EEDS a result of operating the VCC system in the “ON” state determining the level of energy conservation achieved by the VCC system. In addition the VCC system monitors pattern recognition events and compares them to the report-by-exception data to detect HVL events. If one is detected the VCC optimizes the capacity of the EEDS to respond to the HVL events by centering the piecewise linear solution maximizing the ability of the EDDS to absorb the HVL event.

In a power control system a server maintains asset models that represent asset behaviour, each asset model being in real-time communication with its asset to dynamically inform the model of the status of the asset. A test is performed at the server by issuing a command to an asset requesting the asset to perform a function. Sensors at the asset measure physical parameters at the asset and report these to the server. The server determines whether the asset responded to the command and, if the asset responded, how it responded over time. The server establishes a model for the asset in terms of an energy capacitance and a time constant based on the measured response. An optimizer determines which assets are to participate in which service models. The server sends instructions to the selected assets to attempt to fulfill the services.

To ensure safety of people needing to service a low-voltage network of an electric power distribution system, dwellings being connected to this network may include autonomous units for producing electricity, thus generating voltage and endangering the people servicing the work. Data are obtained from consumption records from the meter of each dwelling, in regular time intervals, and meteorological data are also obtained in the geographical area of these dwellings, in order to identify at least some weather conditions conducive to the production of energy by autonomous units. A model is then applied for detecting, based on the first and second data, a coincidence between periods of lower consumption measured by a meter and weather conditions conducive to electricity production by autonomous units during these periods. Therefore, information on the presence of autonomous units in the dwelling can be deduced and given to people before their servicing.