The invention relates to a method for controlling power generation from a power plant which comprises a plurality of power generating units. The method involves setting a maximal allowed power production for each power generating unit in a selection of one or more power generating units of second priority to a non-zero value, where the maximal allowed power production is determined dependent on whether a first power production gap is greater or less than zero and dependent on a comparison of the first power production gap with a second available power production capability of the selection of the one or more power generating units of the second priority.

A Dielectric Energy Storage System (DESS), a Dielectric Energy Storage System Management System (DESS-MS), and method that stores energy for a wide variety of applications.

A method and system for controlling voltage and reactive power for electrical grids includes monitoring the output of the energy generation facilities at the point of interconnection (POI) of each energy generation facility to the power transmission system of the electrical grid. In addition, the voltage at a point of utilization (POU) is monitored to determine when the output voltage of the energy generation facilities must be adjusted to maintain voltage at the POU. In addition, when it is determined that energy generation facilities are exchanging reactive power, the voltage set points of the energy generation facilities are adjusted to reduce the exchanged power.

A power management system, comprises a power generating unit, a power output unit to distribute the electrical power generated by the power generating unit to a household and to a receiving unit, different from the household, wherein the receiving unit is a battery and/or a power grid, a grid power output unit to output electrical power supplied from a power grid to the household and/or to the receiving unit, a condition requirement setting unit to receive condition requirement data and a time period after which the receiving unit has to satisfy the required condition, a prediction data input unit to receive prediction data that indicates a prediction of the electrical power generated by the power generating unit over the time period, a control unit that is adapted to receive the condition requirement data from the condition requirement setting unit and the prediction data from the prediction data input unit.

The present disclosure provides systems and methods for flexible renewable energy power generation. The present disclosure also provides systems and methods for firming power generation from multiple renewable energy sources.

Protection system for limiting the impact of disruptions of an external urban or industrial electrical network on a local electrical network of a site which is connected to the external network and which includes at least one local electric power source, referred to as “local source” connected to the local network and capable of injecting the surplus electric power into the external network, with the protection system including a synchronous machine connected to the local network which is itself connected to the external network by way of a choke, referred to as “network choke.” The protection system includes at least a local choke which is associated with the local source and which is connected to the local network between this local source and the synchronous machine.

Fluctuations in the battery life of a plurality of storage batteries are reduced. A DC power supplying system includes power conditioners that supply generated power of power generators to a DC bus, converters that perform voltage conversion on a bus voltage and supply load power to load appliances, bidirectional converters that execute charging operations that charge storage batteries and discharging operations that discharge the storage batteries, and an energy management system that causes the converters to execute a charging operation when the generated power exceeds the load power and to execute a discharging operation when the generated power is below the load power. During a charging operation, the energy management system applies a first voltage-current characteristic that linearly increases the charging current in keeping with an increase in the bus voltage to each bidirectional DC/DC converter with a slope in keeping with the SOC of a storage battery.

A power management module and method for controlling power consumption of consumers in a wind turbine system. Each power management module in the wind turbine system is configured to determine a voltage level of a power supply bus of the wind turbine system and then control a level of power consumption of one or more consumers coupled to the power supply bus based at least in part on the determined voltage level of the power supply bus. Power consumption may thereby be managed throughout the wind turbine system, without requiring a dedicated centralised controller and communications infrastructure.

A system and a method for regulating charging and discharging of an energy storage device as part of an electrical power distribution network is described. The invention is a smart control algorithm for a bi-directional switch in which an energy storage device, such as a battery set, is charged when electricity prices are low and discharged when electricity prices are high. The invention uses two different types of pricing data: forecasted price data and real-time price data. The forecasted price data is used to set a threshold. When the real-time price data of electricity exceeds this threshold, the energy storage device is set to discharge and send power to the grid. Otherwise the energy storage device is set to charge. The threshold is set periodically, typically in 30 minute to several hour intervals to capture the latest data.

An example method comprises receiving historical wind turbine failure data and asset data from SCADA systems, receiving first historical sensor data, determining healthy assets of the renewable energy assets by comparing signals to known healthy operating signals, training at least one machine learning model to indicate assets that may potentially fail and to a second set of assets that are operating within a healthy threshold, receiving first current sensor data of a second time period, applying a machine learning model to the current sensor data to generate a first failure prediction a failure and generate a list of assets that are operating within a healthy threshold, comparing the first failure prediction to a trigger criteria, generating and transmitting a first alert if comparing the first failure prediction to the trigger criteria indicates a failure prediction, and updating a list of assets to perform surveillance if within a healthy threshold.