Apparatus and methods for recovering energy in a petroleum, petrochemical, or chemical plant as described. The invention relates to a recovered electric power measuring system comprising at least one processor; at least one memory storing computer-executable instructions; and at least one receiver configured to receive data from a sensor on an electrical powerline connected to a generator of a power-recovery turbine, the power-recovery turbine located in a petroleum, petrochemical, or chemical process zone wherein a portion of a first process stream flows through the power-recovery turbine and generates recovered electric power as direct current, the power-recovery turbine electrically connected to a single DC to AC inverter and the output of the DC to AC inverter electrically connected to a first substation.

In one aspect, a method to determine a capacity of a microgrid includes applying a current test load to the microgrid and measuring a current through an energy storage device, the current indicating a charging status of the energy storage device based on a current load being applied to the microgrid through activated power outlets being served by the microgrid and the current test load, the energy storage device being integrated with the microgrid. The method also includes, responsive to a determination that the measured current based on the current load being applied to the microgrid and the current test load indicates that the energy storage device is discharging, determining the capacity of the microgrid, wherein the capacity is the current load being applied to the microgrid through activated power outlets and a test load applied to the microgrid immediately preceding the current test load.

An example energy storage system and a related method are disclosed. In the energy storage system, a controller obtains information about user equipment, and then controls a converter and a battery group based on the information about the user equipment, to supply electric energy to an electric device or receive electric energy from a power sourcing device. In this way, the energy storage system can provide reasonable power scheduling, thereby improving utilization of the energy storage system.

A microgrid power flow monitoring and control system is described herein. The control system may determine active and reactive power sharing shortage on the electric power delivery system. The control system may utilize the control strategies of generation units, such as ISO control, droop control and constant power control to estimate power flow within a microgrid or other isolated system. A control strategy of one or more generators may be modified based on the determined power flow.

A method for designing a distributed communication topology of a micro-grid based on network mirroring and global propagation rates includes the following steps: first, determining the communication connectivity of distributed directed networks in the micro-grid; next, obtaining, for connected directed communication networks, mirror networks thereof based on a mirroring operation, and selecting an optimal distributed directed communication topology corresponding to a maximum performance indicator based on algebraic connectivity and communication costs; solving, for the optimized distributed communication topology, pinned distributed generation sets corresponding to different pinning numbers based on global propagation rates and out-degrees; and finally, establishing a distributed secondary voltage control of the micro-grid based on the optimal distributed communication network and pinned nodes of the micro-grid, to achieve accurate reactive power sharing and average voltage restoration.

Methods for implementing power delivery transactions between a buyer and a seller of electrical energy supplied to an electrical grid by an integrated renewable energy source (RES) and energy storage system (ESS) of a RES-ESS facility are provided. Estimated total potential output of the RES is compared to a point of grid interconnect (POGI) limit to identify potential RES overgeneration, and the buyer is charged if potential RES overgeneration is less than potential overgeneration during one or more retrospective time windows. The method provides a basis for the RES-ESS facility owner to be paid for an estimated amount of energy that did not get stored as a result of a grid operator not fully discharging an ESS prior to the start of a new day.

A method may include determining a position and movement of a shadow on a plurality of solar modules of a solar power plant using an analysis of irradiance data from sensors disposed proximate the plurality of solar modules. The method may include predicting future power output for the plurality of solar panels based on the movement of the shadow over the plurality of solar modules and modifying a power output of the solar power plant based on the predicted future power output.

An energy saving support system according to an embodiment is configured to provide a consumer, who has an electric load to which electric energy is supplied from an electric power supply system within a house, with energy consumption-related information through a photo frame or the like. The information providing apparatus is configured to acquire an acceptability level, which stepwise indicates a degree of interest of the consumer in the energy consumption-related information, and to determine the energy consumption-related information to be newly provided to the consumer based on the acceptability level.

Provided is a source-load cooperation access method for a power distribution region. The method includes: establishing a timing feature model of a distributed generator and a timing feature model of a load respectively, acquiring a timing feature of the distributed generator in an access power distribution region by using maximum likelihood estimation and acquiring a timing feature of a user which accesses the power distribution region by using classification and regression trees; and inputting the timing feature of the distributed generator and the timing feature of the user which access the power distribution region into a combination optimization model, and determining a source-load access feeder through optimization.

Disclosed is an optimal power flow acquiring method for regional distribution network of small hydropower groups based on deep learning, which specifically includes the following steps: generating required data sets by adopting continuous power flow and power flow equation calculation methods; the data set is randomly divided into training data (80 percent) and test data (20 percent); training the built convolutional neural network model with training data to learn the mapping relationship between load and generator output power; inputting test data, and directly obtaining P.sub.G and Q.sub.G from the trained convolutional neural network; and solving residual variables V.sub.i and θ.sub.i with traditional power flow solver. The application can accelerate the solving speed of the optimal power flow problem with higher prediction accuracy.