137 results about "Electric consumption" patented technology

This system enables energy management that automatically creates an economically efficient operating schedule for energy storage devices, taking into account electricity procurement costs. [Solution] Customer 5 is equipped with an electrical load 25, a solar power generation device 50, and energy storage devices 20, 30, and is capable of buying and selling electricity to and from the power grid 3. Server 10 creates an operation schedule for the energy storage devices 30, 40 for the next day based on the power procurement unit price for each of several time slots that divide the next day's 24 hours, the predicted power generation amount by the solar cells 50 and the predicted power consumption amount of customer 5 for each of the multiple time slots, and the comparison and determination result of the power procurement unit price and determination threshold in the time slot group that includes the default operating candidate period for the energy storage devices 30, 40 among the multiple time slots. HEMS 20 generates operation commands for the energy storage devices 30, 40 according to the operation schedule created by Server 10.

In the context of an electrical utility system, changing cloud conditions may cause a customer having solar panels to greatly increase or decrease electrical demand in a difficult-to-predict manner. Accordingly, a spinning reserve maintained by an electric utility company must be larger, and is therefore more expensive. In an example, the spinning reserve may be managed by: calculating a stable sequence of forecasts of smoothed real-time consumption, wherein the calculating is based at least in part on smoothed estimates of consumption data. A stable sequence of forecasts of real-time measured load may be calculated by subtracting forecasts of real-time distributed solar photovoltaic (PV) generation data from the stable sequence of forecasts of smoothed real-time consumption. The spinning reserve of the electricity system may be controlled based at least in part on the stable sequence of forecasts of real-time measured load.

This invention belongs to the field of power system analysis and load forecasting technology, and discloses a method and device for forecasting residential electricity consumption. The method couples the population structure subsystem, socio-economic subsystem, and residential electricity consumption system to construct a closed-loop feedback system, forming a system dynamics model. Based on the current initial value of per capita electricity consumption and the calculated rate of change of per capita electricity consumption, the predicted per capita electricity consumption is calculated. This invention can effectively reflect the dynamic evolution of electricity demand under multi-factor coupling conditions, and can provide intuitive and reliable decision-making basis for power grid planning, power load management, and energy policy formulation. It is applicable to medium- and long-term forecasting scenarios of residential electricity consumption at different regional scales.

This invention discloses a method for reliability assessment of distribution networks involving integrated energy parks in a market environment, belonging to the field of distribution network reliability assessment technology. The method includes: constructing constraints on multi-energy conversion equipment within the integrated energy park and quantity-price elasticity curves for end-user electricity in the integrated energy park; based on the constructed constraints on the multi-energy conversion equipment and the quantity-price elasticity curves for end-user electricity, changing the external electricity purchase price of the integrated energy park to obtain the integrated elastic quantity-price curve of the integrated energy park; constructing a two-state model of the probability distribution function of the electricity sales price and component failures according to the electricity sales price and the faults occurring in the distribution network, and generating typical distribution network operation scenarios; and simulating operation using an optimal load reduction model of the distribution network based on the electricity sales price and the electricity consumption of the integrated energy park, outputting evaluation indicators. The method described in this invention significantly improves the accuracy of the load model and achieves a complete and closed-loop quantitative reliability assessment.

This invention discloses a photovoltaic energy storage system, including a shared energy storage module, an inverter control module, and multiple energy metering modules. The shared energy storage module includes multiple energy storage batteries for storing electrical energy or supplying power to load modules. The inverter control module is connected to each photovoltaic power generation module, each load module, the shared energy storage module, and the power grid. It controls the electrical energy generated by each photovoltaic power generation module to supply power to each load module, store it in the shared energy storage module, or connect it to the power grid; the shared energy storage module supplies power to each load module. Each energy metering module is set up for each user, located between each user's photovoltaic power generation module, load module, and inverter control module, for detecting power generation and consumption. The inverter control module is configured to calculate absolute power generation or absolute power consumption based on power generation and consumption; accumulate pre-stored power based on absolute power generation and absolute power consumption; and control the power supply to each user based on the pre-stored power. This improves fairness and efficiency.

The application provides a lifting pump main motor bearing vibration lightweight intelligent prediction method, realizes accurate prediction of future state of lifting pump main motor bearing vibration, collects power consumption, power, current, temperature and water flow of the lifting pump main motor bearing as model input variables through a sensor, establishes a lifting pump main motor bearing vibration lightweight intelligent prediction model, constructs a multi-layer convolution module stacking structure to extract deep features of input data, relieves influence of insufficient generalization on model prediction performance, realizes accurate prediction of lifting pump main motor bearing vibration, designs a convolution module self-organizing reconstruction mechanism, groups similar convolution kernels by using spectral clustering, self-organizes a low-rank similar convolution kernel result matrix, and assigns the low-rank similar convolution kernel result matrix to a weight vector of a newly-built convolution kernel in each lightweight convolution module, so that the number of parameters of the prediction model is reduced.

This invention proposes a method and system for electricity consumption completion and prediction based on missing electricity consumption data. For historical electricity consumption data with random missing values, the method first acquires the historical electricity consumption data containing random missing values ​​and a mask, then uses a generative adversarial network (GAN) to perform data imputation, and finally uses a long short-term memory (LSTM) network to predict future electricity consumption. Finally, the GAN is fine-tuned under the constraints of the prediction results to achieve joint optimization of completion and prediction. This invention effectively mitigates the adverse effects of missing data on prediction accuracy through the collaborative mechanism between the data completion and prediction modules; it uses the temporal characteristics of the missing data restored by the GAN to ensure that the completion results are consistent with the real data in terms of statistical distribution and temporal patterns. This invention achieves joint optimization of completion and prediction through a prediction error inverse constraint generator, thus maintaining good prediction stability under different missing rates and seasonal conditions.

1. Name of the design product: electric meter and its main body. 2. Use of the design product: the overall use of the products of designs 1-6 is electric meter, and the partial use of the products of designs 1 and 4 is as the main body of electric meter. 3. Design points of the design product: the shape of designs 2-3 and 5-6; the shape shown by solid lines of designs 1 and 4. 4. Picture or photo best indicating the design points: the perspective view of design 1. 5. Design 1 is designated as the basic design.

This invention discloses a big data-based energy storage capacity time-sharing leasing control system and method, relating to the field of time-sharing leasing control technology. It involves marking electricity-consuming enterprises within the monitoring range, acquiring historical electricity consumption records of these enterprises based on historical electricity consumption data from a preset monitoring period, and calculating the basic electricity load forecast values ​​for each time period, taking into account historical influencing factors. For enterprises with only a single working label, the corresponding predicted energy storage demand is calculated according to the label type. For enterprises with more than one working label, the maximum value of the predicted demand corresponding to each label is taken as the final demand. For enterprises without labels, the basic load forecast value is used as the final demand. Time-sharing capacity is pre-allocated based on enterprise type priority, and the results are pushed to the enterprise to confirm leasing intentions. This invention, through a priority capacity pre-allocation mechanism based on enterprise importance, prioritizes electricity demand when capacity resources are limited.

We provide the system. [Solution] A data acquisition method for obtaining power consumption information, An analytical method for analyzing and predicting consumption trends based on past electricity consumption information, A strategy generation means for generating an electricity usage plan based on analyzed consumption trends, An information exchange means that uses communication technology to ensure secure information transmission to perform secure transmission and reception of data, A means of adjusting the balance between power supply and consumption in real time, An information display device that shows the electricity consumption status of homes and businesses on the user's mobile device and suggests ways to improve energy efficiency, A system that includes this.

A procedure for operating an electrical energy system in a building includes a step for collecting a variety of consumption data on the electrical active energy drawn. This active energy is drawn from the public electricity grid and / or from existing energy generators within the building's energy system via a grid connection point. A load profile is determined based on the consumption data. This load profile describes the expected or historical trend of the active energy drawn over a given period. A backup generator for generating and / or supplying electrical energy is then selected based on the load profile. The backup generator is intended to operate instead of, or in addition to, existing energy generators within the building's energy system and / or to reduce the amount of active energy drawn from the public grid.

The application discloses a kind of hydrogen fuel power supply's residual power estimation method.Hydrogen fuel power supply includes the fuel tank of built-in solid hydrogen material, hydrogen fuel power supply is based on the hydrogen production reaction caused by water injection to fuel tank, to hydrogen gas supply power pile power generation, estimation method includes: based on the real-time water injection quantity integration of single fuel tank, calculate the theoretical residual power generation of fuel tank;Theoretical total power generation and theoretical residual power generation of all fuel tanks are summarized to obtain theoretical power generation;Based on the real-time output power integration of power pile, in combination with the loss of monitored electric quantity, calculate actual consumed energy;Theoretical power generation and actual consumed energy are weighted and fused using feasibility coefficient, estimate used power, based on used power to calculate current residual power.The technical scheme of the present application can improve the estimation accuracy of residual power, can predict the future power generation capacity of the remaining fuel in the fuel tank, reduce the problem of inaccurate residual power display, meet the use demand.

This invention belongs to the field of power system data analysis and power consumption forecasting technology, specifically involving a method and system for predicting the power consumption curve of proxy power purchasers in extreme scenarios. The method first constructs a power consumption forecasting model. The model uses an encoder to extract features from multi-source meteorological data of extreme scenarios through supervised contrastive learning, obtaining meteorological feature vectors for the extreme scenarios. A decoder is then used to predict the total daily power consumption based on the extracted meteorological feature vectors. Multi-source meteorological data for the forecast day is acquired and input into the trained power consumption forecasting model to predict the total daily power consumption for the forecast day. Based on the total daily power consumption for the forecast day, the time-of-use power consumption curve for the forecast day is obtained. This invention achieves high-precision total daily power consumption forecasting under extreme scenarios by efficiently extracting meteorological data features through an encoder and achieving rapid and accurate adaptation with a small number of samples through a decoder.

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.

The application discloses a kind of both can guarantee calculation real-time, and can realize the high-fidelity restoration of missing link working condition flow power consumption settlement method, device, equipment and medium, wherein method includes: receiving the electric meter data message sent by edge computing node;According to the time zone of electric meter, the timestamp of energy consumption cumulative indication value is uniformly converted into logical local time, and maximum tolerance disorder time is determined based on network delay fluctuation in data message upload process to construct flow water level line, and flow water level line is used to drive the flow settlement of statistical window;Based on instantaneous power feature vector, load fingerprint library of electric meter is generated using clustering algorithm, and the load fingerprint library includes various load fingerprint patterns and their corresponding reference values;After detecting that electric meter is missing and recovered, extract the instantaneous power feature vector before and after missing, deduce the load fingerprint pattern sequence during missing period in combination with load fingerprint library, and restore the power increment generated during missing period to the corresponding each statistical window in missing period.

We provide a forecasting system that can predict the power consumption of multiple consumers. [Solution] The prediction system 10 includes an acquisition unit 54 that acquires first information regarding the power consumption of at least some of the customers 20a by collecting measurement data from power measuring devices installed in at least some of the customers 20a from communication devices installed in at least some of the customers 20a that have contracts with an electric power company; a prediction unit 55 that predicts the power consumption of the multiple customers 20 based on the acquired first information; and an output unit 56 that outputs prediction data showing the predicted power consumption of the multiple customers 20.

This application provides an integrated photovoltaic and power management control board and system, including an MPPT control module, a charging module, a discharging module, a power monitoring and alarm module, and a display module. The power monitoring and alarm module can not only calculate the battery power, but also calculate the photovoltaic input power during the operation of the MPPT control module, the charging power during the operation of the charging module, and the discharging power during the operation of the discharging module. By reusing the power monitoring and alarm module, the management of the battery, the MPPT control module, the charging module, and the discharging module can be realized. Only one chip is needed, which has high integration, small footprint, and low cost.

The utility model discloses a kind of efficient energy-saving mixing equipment, including mixing kettle and the stirring motor being set to the bottom of mixing kettle and rotating it, the upper end of mixing kettle and the position of front near bottom are respectively provided with feed inlet, discharge port, further including multiple groups of weighing cylinder, the frequency converter of electric connection is further fixedly arranged outside stirring motor, the feed inlet outside the upper end of mixing kettle is fixedly connected with mounting bracket, and mounting bracket is fixedly installed to multiple groups of weighing cylinder, and the feed inlet on the upper end of mixing kettle is connected by the blanking tube at the bottom of weighing cylinder.The utility model makes the rotation speed / power of the stirring motor of mixing kettle reduce to 50% of original power before material enters mixing kettle, to achieve the effect of half of power consumption, and restore initial state after material ratio is completed and valve is opened to enter mixing kettle, to realize the normal mixing of material, to realize standby, idle running process energy consumption management and control, to reduce the power consumption of raw material mixing process.

The present application relates to a kind of energy storage scheduling method and system for peak demand reduction and peak valley arbitrage.The method comprises the following steps: setting parameters and initializing;at each time t in the demand control time period, the real-time discharge power is calculated according to the current remaining available power of the energy storage system and the remaining time to the end of demand control;at the end of each demand metering period, the grid-side demand and the load-side demand of the period are calculated, and the grid-side maximum demand and the load-side maximum demand are updated in real time;the real-time load power is continuously monitored and obtained, if the real-time load power is greater than the grid-side maximum demand, the energy storage system is controlled to discharge according to the calculated real-time discharge power to reduce demand;otherwise, control the energy storage system to execute standby;whether to enable peak valley arbitrage mode is judged based on the dynamic discharge power and the realized demand reduction amount;if enabled, the energy storage system continuously discharges according to the dynamic discharge power;if not enabled, the energy storage system remains in demand lock control mode.

We provide a scheduling system and scheduling program that create an energy usage schedule that can reduce energy costs without changing the lifestyle of consumers. [Solution] The system includes an estimation task 161 that estimates the lifestyle 3 of customer P based on the amount of electricity used measured at predetermined intervals by a smart meter 2 installed at customer P's home, a pricing plan 5 in which the energy usage charges fluctuate according to the time of day in conjunction with the market price in the wholesale electricity market 4, and a scheduling task 162 that creates an electricity usage schedule based on the lifestyle 3, such that at least a portion of the time of day when customer P uses electricity is in line with the lifestyle 3 and is a time when usage charges are low.

The application discloses a kind of table area electric heating load identification method and system, belong to power grid data analysis and intelligent identification technical field.The method includes: obtaining the historical load of to-be-identified table area, time and multi-dimensional time series data such as meteorology by data acquisition module;Utilize a deep learning model comprising time series feature extraction module and key feature weighting module to process data to generate preliminary classification results;Based on the business rules of the growth of heating season electricity consumption and the stability of non-heating season electricity consumption, the historical load is compared and verified across years;The preliminary classification result of model is combined with the verification result of rule, and whether table area is electric heating load is comprehensively judged.This application combines the pattern recognition ability of deep learning with the deterministic logic of business rules, realizes the high-precision, high-robustness automatic identification of electric heating load, and provides an effective technical means for power grid intelligent management.

This electronic whiteboard system incorporates an automatic air conditioning control system that remotely controls a demand control board and can reduce the total power consumption and CO2 emissions of the entire facility by more than 30% compared to pre-registered actual water, energy, and heat usage values. [Solution] In an electronic whiteboard system, a demand control board, which is retrofitted to the indoor and outdoor units of an air conditioner and equipped with a CO2 sensor and a schedule timer, has a schedule timer that can change the control rate between peak time and other times, a CO2 sensor that controls up to 80% according to the indoor CO2 concentration, a demand control and linkage function that works in conjunction with existing demand control to achieve up to 80% reduction in air conditioning power consumption, and a smartphone app linkage function that allows facility managers to check the CO2 concentration, temperature, and humidity for each area on their smartphones. By installing this board, power consumption will be reduced by 50%, exceeding the government's CO2 reduction target, and the reduction results will be published in real time using an electronic whiteboard.

In an electric power supply-demand adjustment system for performing electric power supply-demand adjustment by causing, by using a computer including a processor and memory, customers to control power consumption in accordance with an instruction issued by an aggregator, the processor, on the basis of demand response (DR) event information stored in the memory and including a scheduled event regarding the electric power supply-demand adjustment, and customer profile information stored in the memory and indicating a feature of a time-shiftable process performed by the customers consuming electric power, obtains a combination of processes shifted within an acceptable range, in which combination a power reduction amount fulfills a requested adjustment amount, to generate, for each of the customers, DR request information including a request for supply-demand adjustment of a power adjustment amount determined by the scheduled DR event, and determines a width of the shift to carry out electric power supply-demand adjustment.

This invention provides an information processing device, information processing system, information processing method, and information processing program that can return previously unrealized environmental value to users. [Solution] The center server 100, as an information processing device, includes a reception unit that receives the amount of self-consumption of electricity generated by a solar panel 300, which is a power generation device that generates electricity using renewable energy, at a facility where the solar panel 300 is installed; an acquisition unit that acquires the environmental value corresponding to the amount of self-consumption; and a billing unit that bills the user for an amount obtained by deducting the amount corresponding to the environmental value from the electricity charges paid by the user who used the electricity.

The application discloses a kind of energy storage capacity configuration method, device, equipment and medium of photovoltaic energy storage system, involve photovoltaic energy storage technical field, comprising: obtaining the photovoltaic power generation curve of photovoltaic energy storage system, the power load curve of target family;According to photovoltaic power generation curve and power load curve, determine the daily self-generation self-use capacity of photovoltaic energy storage system, daily self-generation self-use capacity refers to the energy storage capacity required for photovoltaic energy storage system to meet the daily self-generation self-use of target family;According to target standby time, determine the first period covering the maximum total power consumption from power load curve, and the total power consumption of power load curve in the first period is used as the standby capacity of photovoltaic energy storage system;The sum between daily self-generation self-use capacity and standby capacity is used as the reference energy storage capacity of photovoltaic energy storage system;Compare reference energy storage capacity with the battery capacity of each battery model adapted to photovoltaic energy storage system to determine the target energy storage capacity to be configured.

This invention belongs to the field of electric vehicle technology, and particularly relates to a method, system, device, and storage medium for predicting the remaining driving range of a vehicle. It aims to solve the technical problem in existing technologies that fail to consider the impact of battery aging on the battery's usable capacity, potentially leading to decreased calculation accuracy and affecting user experience. The method includes: acquiring operating parameter data of the electric vehicle; preprocessing the operating parameter data to obtain preprocessed data; calculating the energy consumption of the electric vehicle during discharge based on the preprocessed data to obtain a discharge energy consumption value; calculating the charging capacity during charging based on the preprocessed data, and calculating the current state of equilibrium (SOH) of the battery based on the capacity value; and calculating a predicted value for the remaining driving range of the vehicle based on the discharge energy consumption value and the SOH value to obtain a prediction result.

This invention relates to the field of automated control technology for thermal power generation, and discloses a peak-shaving optimization control system for thermal power units. The system includes a data acquisition and processing module, a multi-objective optimization module, and a peak-shaving execution module. This invention connects to the power plant's distributed control system and plant-level monitoring information system to collect real-time unit operation data and user demand data. The collected data is preprocessed, and the peak electricity demand for the day is predicted based on the user demand data. The theoretical power generation is calculated using an objective function model based on the predicted peak demand and unit operation data. Peak-shaving is then performed based on the theoretical power generation; if the theoretical power generation exceeds the current actual power generation, peak-shaving is executed. The objective function model comprehensively analyzes multiple aspects, including economic cost, power generation revenue, and user demand, achieving coordinated optimization of multiple objectives during peak-shaving and improving the intelligence and economy of peak-shaving control.

The application discloses a kind of based on energy consumption side's province and land two-level non-fossil energy power consumption accounting method, belong to power system data management and green energy accounting technical field.The method follows user subject and consumption base principle, first determines accounting period and boundary, collects total social power consumption, power market transaction, cross-provincial power flow direction and other basic data;Secondly, a provincial accounting model is constructed, and five types of power consumption, including medium and long-term transaction, cross-provincial net inflow and self-generation and self-use, are integrated to calculate the total consumption of the province;At the same time, a city-level accounting model is constructed, and the city consumption is accounted according to the user types of direct entry into the city and proxy power purchase, combined with the provincial allocation coefficient.The application realizes the coordination and unification of physical power and green certificate rights and interests, solves the problems of repeated calculation and province-city disconnection in existing accounting, and provides reliable technical support for government energy-saving assessment, renewable energy responsibility weight calculation and non-fossil energy consumption accounting.

This invention relates to the field of power management technology, and discloses a grid-connected management system based on the recovery of curtailed solar energy from photovoltaic modules. It includes a mode selection module for selecting the energy recovery mode; an independent management module for executing independent management and recovery operations; an analysis and prediction module for collecting power supply parameters and load consumption parameters; a model prediction module for predicting power supply and load consumption values; and a fusion management module for executing fusion management and recovery operations. This invention avoids the lag problem inherent in real-time prediction and analysis operations, reserving sufficient time for subsequent grid-connected management operations for curtailed solar energy recovery. It prevents insufficient power supply to local loads due to a surge in electricity consumption at some point in the future, ensuring the safety and reliability of the grid-connected management system, avoiding the waste of curtailed solar energy, reducing the electricity consumption cost of local loads, and improving the economic efficiency of the grid-connected management system.