Abstract: Provided are a method and energy harvesting system for extracting maximum power from an input source. When the energy harvesting system includes a converter, a sensing part, an artificial intelligence (AI) calculator, and a resistor part, the method includes: sensing an input voltage and an input current from the input source using the sensing part, converting the input voltage and the input current corresponding to analog values into digital values through an analog-to-digital converter (ADC) block, and transmitting the digital values to the AI calculator; calculating input power on the basis of the digital values using the AI calculator and acquiring an optimal sampling ratio for extracting maximum power on the basis of the input power; controlling a resistor divider ratio on the basis of the optimal sampling ratio to equalize a sampling ratio to the optimal sampling ratio; and performing a regulation operation through the converter.

Abstract: A method of trading electrical energy is provided. The method comprises a smart agent receiving state data affecting electricity usage within an electrical power grid over a specified time period and forecasting, with a supply/demand model, supply and demand for electricity within the power grid according to the state data. The smart agent uses a reinforced learning neural network to calculate a price for electricity according the state data and forecasted supply and demand. The smart agent submits an order to a matching engine to buy or sell electricity on the power grid at the calculated price according to specified market rules. The smart engine receives an acknowledgment from the matching engine if the order is matched to another agent on the power grid or a rejection from the matching engine if the order is not matched to another agent.

Abstract: In an electronic apparatus, reference information stored on a memory includes standard appliance ownership information describing owned home appliances of at least one standard household and standard monthly power consumption information of the standard household. A processor obtains first monthly power consumption information of a first household which owns a first home appliance of a same type as a standard home appliance described in the standard appliance ownership information. Based on a difference between the standard and first monthly power consumption information being within a threshold range, the processor compares appliance monthly power consumption information of the standard home appliance and of the first home appliance, and, based on the result being within a threshold range, predicts first appliance ownership information on owned home appliances of the first household based on the standard appliance ownership information.

Abstract: An energy efficiency data collection system architecture may be configured to enable efficient and accurate collection of energy efficiency data associated with users and/or sites associated with users and generation of profiles associated with the users based on the energy efficiency data. An energy efficiency data collection service may receive location information, image data, and user-input data from an application operating on a mobile device associated with a user. The energy efficiency data collection service may generate profiles based on the information received from the application and may provide incentives to the users in response to participating in an energy efficiency data collection survey.

Abstract: The disclosure provides a multi-energy integrated short-term load forecasting method and system, which relates to the technical field of load forecasting. In the disclosure, after classifying the acquired relevant data of multi-energy integrated short-term load forecasting, the data after sample classification is used to train the multi-energy integrated short-term load forecasting model. The model is composed of multiple layers of temporal convolutional networks having multi-head self-attention mechanism and rotary position embedding. Finally, the trained model is used to carry out the multi-energy integrated short-term load forecasting. The disclosure can fully mine the coupling feature between multi-energy loads, improve the accuracy of multi-energy integrated short-term load forecasting, and further improve the management level and service efficiency of integrated energy demand side.

Abstract: Various embodiments of the teachings herein include a system comprising: a local supply of renewable power; a storage device with a discharge characteristic; a switch for electrically connecting the storage device to the local supply; and a system controller. The system controller may be configured to: receive from the local supply a signal indicative of available power; read from a memory a time history of past activations of the storage device; estimate a future demand of power based on the time history; estimate a charge of the storage device based on the future demand of power and the discharge characteristic; compare the charge to the future demand of power; and if the charge is larger than the future demand of power by a predetermined margin, electrically connect the local supply of renewable power to the storage device by closing the switch.

Abstract: A system and method for protecting an electric power distribution system integrated with a hybrid machine-learning model includes a plurality of field protection systems, a plurality of electrical switching circuits, and a local area network. Data from each of the plurality of field protection systems that is connected to the electrical switching circuits that are configured for protecting the electric power distribution system, is transmitted to the cloud. The received data is processed to identify a change in patterns and compute an error related to the HMLM in comparison with the processed data. The HMLM that is implemented in the plurality of FPS is calibrated to minimize the error and send updates to develop a new decision making firmware thereby to control actuation of the plurality of the electrical switching circuits.

Abstract: A method for providing frequency balancing in a power network grid by an RBS of a radio communication network. The RBS includes one or more power supply units, PSUs, connected to the power network grid. The method includes detecting a deviation of a power network grid frequency measured in a PSU of the one or more PSUs, the power network grid frequency is measured upstream of a power factor correction, PFC, unit of the PSU, deactivating the one or more PSU in response to the detected deviation, determining one or more further PSU to be deactivated based on the detected deviation, the RBS is in a first frequency containment reserve, FCR, zone and the one or more further PSU are in a second FCR zone, other than the first FCR zone, and sending a deactivation indication to the determined one or more further PSU.

Abstract: A command device according to the present disclosure includes a first communication unit that receives a first command value representing an externally-commanded charge-discharge amount with respect to a storage battery connected to a power system, a low-pass filter and a high-pass filter for extracting a short-period component of a measurement value with respect to electrical power at an interconnection point of a PCS that controls charging and discharging of the storage battery, and an amount-of-control calculation unit that calculates a third command value by addition of a first command value and a second command value generated based on the short-period component, and commands the PCS to use the third command value.

Abstract: The present invention relates to an energy management system for a building, comprising at least one heat pump, at least one first thermal energy storage device for providing domestic hot water, at least one second thermal energy storage device for providing space heating, at least one renewable energy generation device, at least one first state of charge analyser for determining the state of charge of the at least one first thermal energy storage device, at least one second state of charge analyser for determining the state of charge of the at least one second thermal energy storage device, and a controller configured to control the at least one heat pump, the at least one first thermal energy storage device, the at least one second thermal energy storage device, and the at least one renewable energy generation device.

Abstract: A software module is deployed in a MOM system without requiring the operator to know where to deploy the software module within the network of the computational resources that are addressed and/or accessed within the MOM system. A number of software modules are provided, each including a set of metadata with a number of deploy criteria. A plurality of computational resource layers are provided, with each resource layer having different computational resources and being enabled to communicate layer specific data, which include resource availability information. A deployment instance is executed that evaluates the metadata and the layer specific data and, depending on the evaluation, the computational resource layer and the computational resource on which the software module will be deployed is determined. The software module is then executed on the determined computational resource within the determined computational resource layer.

Abstract: A method for indicating to a user the expected time for an air purifier to achieve a target level of pollution in a room by: (A) acquiring the current level of pollution (CP) in said room; (B) acquiring current air flow speed (CAFS) through said air purifier; (C) comparing the current level of pollution (CP) with a pre-determined target level of pollution (IP); (D) calculating the expected time (T) required to reduce current pollution (CP) to said target level of pollution (IP) at current air flow speed (CAFS); (E) indicating said expected time (T) required to reduce current pollution to said target level of pollution at current air flow speed to a user; and (F) repeating steps (A) to (E).

Abstract: An energy optimization platform may receive user preference information associated with operations of assets of a microgrid. The user preference information may identify user preferences regarding reducing cost, reducing an emission of carbon dioxide, and a resilience against a power outage. The assets may include at least one of one or more solar panels, one or more generators, or one or more batteries. The energy optimization platform may receive load forecast information regarding an electrical load. The energy optimization platform may provide the user preference information and the load forecast information as inputs to an energy model. The energy model predicts, as an output, operating states of the assets based on the user preference information and the load forecast information. The energy optimization platform may determine an optimized combination of the operating states and may provide, to a microgrid controller, optimization information regarding the optimized combination of the operating states.

Abstract: Provided is a method, device, and system capable of performing control so that the voltage of a grid to which a distributed resource is connected is decreased through charging of an ESS group, performing control so that the voltage of the grid to which the distributed resource is connected is increased through discharging of the ESS group, calculating a voltage control amount through a charge amount and a discharge amount for each ESS group when the voltage of the grid to which the distributed resource is connected is stabilized, and providing a performance incentive for voltage stabilization based on the voltage control amount.

Abstract: Methods and systems describe multicasting the messages over a broadcast medium (e.g., a TV network). In particular, the methods and systems recite the use of Advanced Television Systems Committee (“ATSC”) 3.0, a new broadcast television transmission standard in the United States. Using ATSC 3.0, the methods and systems can disseminate messages to all the electrical equipment.

Abstract: Provided are a wire electric discharge machine, a correction device, and a correction method which accurately correct position information indicating the position of a supporting point of each of an upper guide and a lower guide. The correction device includes: a storage unit that stores the position information; an inclination control unit that causes a wire electrode to incline at a predetermined angle; a measurement unit that measures a relative movement amount from a state in which the lower guide and a measurement site are separated by a predetermined distance in a relative movement direction to a state in which the wire electrode inclined at the predetermined angle reaches the measurement site; and an information correction unit that corrects the position information of the storage unit on the basis of the predetermined angle and the relative movement amount.

Abstract: A demand and supply planning method generates a supply-demand plan including information that specifies operation of an energy generation unit for each unit time in a microgrid having energy generation units being connected to an external energy supply system and generating energy while consuming fuel, an energy storage unit, and a load unit; by calculating an optimization problem related to an objective function including terms related to energy transfer from the external energy supply system in the microgrid and terms related to fuel consumption in the microgrid by using a constraint condition related to a relationship between information related to an operating duration time in each of the one or more energy generation units at a start time for generating the supply-demand plan and a minimum operation time constraint of the energy generation unit; and outputting the supply-demand plan based on a calculation result of the optimization problem.

Abstract: Risk element information indicating risk elements is acquired. An asset capable of becoming a fault due to a risk element indicated in the risk element information, and a fault probability that the asset becomes the fault are specified based on static configuration information. A risk model in which the asset capable of becoming the fault and the fault probability are associated is generated in advance. In response to a designated input, an one asset to be evaluated is specified as an evaluation target asset, based on the designated input. A risk model related to the evaluation target asset is specified. A risk evaluation value being an index indicating a risk of the evaluation target asset is calculated based on the fault probability of the evaluation target asset and the static configuration information. The risk evaluation value of the evaluation target asset is associated with the asset of the risk model.

Abstract: Provided herein are embodiments of systems, devices, and methods for a multi-mode, cross-platform design environment to deploy and monitor microgrid controllers rapidly, safely, and inexpensively. A multi-mode environment may run offline, real-time, and live. A cross-platform environment may run on different operating systems and environments. A design system may allow users (e.g., engineers, managers) to design, test, deploy, tune, and monitor microgrid controllers before and after deployment.

Abstract: An adaptive engine and adaptive control method. The method comprises receiving an input regressor and applying one or more estimation laws to the input regressor to estimate a plurality of estimated model parameter tensors for a nonlinear model. The method also includes computing an estimation error or a cost function using a system output measurement and an estimated system output for the previous iteration and determining a model order based at least in part on the estimation error or the cost function and receiving two or more possible control signals each using a corresponding control portion of the nonlinear model. In addition, the method includes generating two or more estimated system outputs each using a corresponding estimation portion of the nonlinear model and selecting a preferred control signal from a set comprising at least the two or more possible control signals or a preferred combination of possible control signals.