79 results about "Electricity cost" patented technology

The application discloses a branch power supply load control linkage system, comprising a load monitoring control master device, a switch control slave device and a communication module, wherein the load monitoring control master device is used for monitoring the remote control port switch state of a special transformer terminal in real time and providing remote control ability, so as to realize accurate detection and remote control of the load switch state of industrial and commercial users; the switch control slave device is used for remotely controlling the pull-out switch of a drawer to cut off power supply, so as to accurately control the load of industrial and commercial enterprises on a mixed line; and the communication module is used for realizing linkage control of the master device on multiple slave devices. The application realizes accurate distinction and control of industrial and commercial loads, so that all users can realize high efficiency and controllability under the condition of orderly power utilization, and the situation of arrears of public area electricity charges in old communities is solved.

This invention relates to the field of thermal power generation cost accounting technology, and proposes a dynamic modeling method and system for the cost per kilowatt-hour based on the forward and reverse balance method. The method includes: real-time acquisition of data on instantaneous flow rate of the coal feeder, coal pile volume, density, coal analysis upon entering the furnace, unit operation, and fuel price; calculation of dynamic coal quality data using a multimodal fusion algorithm; calculation of forward fuel cost based on flow rate, coal quality, and price data; calculation of reverse balance theoretical cost by inferring the theoretical standard coal quantity based on unit operation data; comparison and verification of forward and reverse costs to determine the final fuel cost; and calculation of dynamic cost per kilowatt-hour by combining variable cost and power generation data. This invention achieves a nonlinear dynamic mapping from multi-dimensional real-time data to accurate cost per kilowatt-hour, enabling high-precision, real-time, and automated dynamic modeling of the cost per kilowatt-hour for thermal power generation enterprises.

This invention provides a method and system for economical operation scheduling of water source pumping stations based on time-of-use pricing. By constructing a two-layer architecture model for water lifting capacity configuration and start-up combination decision-making, and using unit start-up and shutdown limits, canal system safety operation, and ten-day water lifting targets as constraints, an optimization model is built and solved to minimize pumping station operating energy consumption and electricity costs, accurately generating start-up combination schemes for each time period within a ten-day period. This invention overcomes the scheduling limitations of discrete flow regulation for constant-speed pump units, comprehensively considering engineering safety, water supply safety, and operational economy. It constructs a scheduling methodology adapted to the dual constraints of poor unit flexibility and weak canal system regulation and storage, achieving economical operation based on time-of-use pricing while ensuring the dynamic optimization performance of the model, improving the robustness and intelligence of scheduling decisions, and filling the research gap in the optimized scheduling of pure constant-speed pump water source pumping stations.

This invention relates to the field of power system demand response technology, and provides a user demand response method based on master-slave game theory under cost control constraints. The method includes: establishing a demand response model using master-slave game theory, where electricity retailers design time-of-use pricing strategies, and electricity users respond based on a convex utility function; the utility function includes a quantification term for electricity usage satisfaction and a calculation term for electricity costs; the electricity retailers' revenue function includes four functions: user electricity costs, long-term market electricity purchase costs, current market electricity purchase costs, and conditional risk value, coupled with the characteristics of the electricity spot market and risk management requirements; proving the existence of a Nash equilibrium solution using backward induction; and optimizing the strategy based on a slime mold optimization algorithm. This invention provides important support for electricity retailers to formulate flexible pricing mechanisms and tap demand-side resources in terms of cost control for users with high response potential and optimization of peak-valley load differences.

This utility model relates to the field of steam generator technology and provides a steam generator exhaust gas reuse device, including: a steam generator body, and a drive assembly disposed on the outer surface of the steam generator body. The drive assembly includes: an exhaust gas port disposed on the outer surface of the steam generator body, wherein one end of the exhaust gas port is connected to a tapered tube; multiple through holes formed on the outer surface of the tapered tube, and one end of each of the multiple through holes is connected to a junction box; two sets of docking holes respectively disposed at both ends of the multiple junction boxes, one set of the docking holes communicating with an external exhaust gas treatment box. In this utility model, high-temperature exhaust gas blows the blades and rotating shaft to rotate. When the rotating shaft rotates, it drives gear one, internal gear, gear two and the output end of the generator to rotate, which facilitates the generator to generate electricity and then delivers it to external electrical equipment, which helps to save electricity costs and realize the reuse of high-temperature exhaust gas.

This invention relates to a coupled clearing method and apparatus for virtual power plants participating in the spot electricity market, applied in the field of electricity market technology. The method includes: calculating the High-Gross Price Ratio (HGRP) as the threshold for economic compensation of DRVPPs, compensating DRVPPs only when the node marginal price is higher than the HGRP, thus preventing the activation of non-economical DRVPPs during low-price periods, preventing low-cost generation resources from being squeezed out of the market, and ensuring the authenticity and effectiveness of the market clearing price signal; incorporating DRVPPs as a controllable and constrained demand-side adjustment variable into the clearing model, avoiding the failure to reflect the adjustment value due to its inclusion in load forecasting, and overcoming the problem of simply treating it as "negative load" and ignoring response constraints, thereby improving the rationality of the clearing results; and adopting a differentiated economic compensation mechanism based on the node marginal price, linking the adjustment revenue of DRVPPs to the marginal electricity cost of the node, achieving precise matching of DRVPP resources with the actual adjustment needs of the system.

This invention discloses an electrical device and its control method and device, as well as a computer-readable storage medium. The electrical device is powered by an energy storage device or the power grid. The method includes: acquiring a set start-up time and a set temperature of the electrical device; determining the required energy consumption based on the temperature difference between the current temperature and the set temperature of the electrical device; determining the start-up time of the electrical device based on the set start-up time and the required energy consumption, provided that the remaining energy of the energy storage device is greater than or equal to the required energy consumption; and controlling the start-up of the electrical device based on the start-up time. The control method of this invention enables precise management of the start-up time and energy consumption of the electrical device, optimizes energy use, improves energy efficiency, and reduces electricity costs.

This invention provides an edge computing-based electricity bill collection method and system. The method involves determining the gateway attributes of each edge computing gateway within a meter distribution topology and their correspondence with smart meters; a cloud server determining and sending execution configuration data for the gateway based on its gateway attributes; the edge computing gateway configuring its program based on the received execution configuration data, generating corresponding baseline processing units and customized processing units at the edge computing gateway; the edge computing gateway collecting electricity consumption data transmitted by the meters, processing the corresponding electricity consumption data according to the baseline processing units and customized processing units to obtain baseline processing information and / or customized processing information; determining corresponding target synchronization devices based on the information attributes of the baseline processing information and / or customized processing information, and sending the baseline processing information and / or customized processing information to the corresponding target synchronization devices to enable the target synchronization devices to complete the electricity bill collection process.

The application discloses a hybrid energy storage integration method and device based on energy storage selection, a terminal device and a storage medium, and belongs to the technical field of energy storage. The method comprises the following steps: calculating the scene matching degree of the to-be-integrated energy storage and the to-be-integrated energy storage application scene according to power grid energy storage data, real-time sensor data and simulation data, and screening out a target energy storage type according to the degree of electricity cost in the operation cost data; constructing a power distribution model and operation power, equipment state safety, energy storage operation environment and application scene constraints according to power grid topology data, power grid energy storage data, real-time sensor data and operation cost data; taking the minimum comprehensive operation cost as a target, solving the model under each constraint to obtain a current power distribution amount, calculating a selection adaptation degree according to real-time sensor data, energy storage rated power, the current comprehensive operation cost and the average degree of electricity cost; and determining a final power distribution amount and integrating operation according to the selection adaptation degree. Through implementation of the application, the problem that existing technologies cannot dynamically integrate energy storage is solved.

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 present application relates to the technical field of computing power load prediction, and discloses a load dynamic prediction and evaluation method for computing power-electricity deep coupling, obtains a multi-dimensional computing power operation parameter set of a target computing power cluster, obtains an electricity state parameter set of a matched electricity supply network, constructs a computing power-electricity coupling correlation mapping model according to the multi-dimensional computing power operation parameter set and the electricity state parameter set, performs rolling prediction on the computing power load demand of the target computing power cluster in a continuous time window, generates an initial load prediction sequence group, determines the computing power supply-demand balance degree, the electricity cost sensitivity and the resource utilization efficiency of a prediction result unit, generates a three-tuple evaluation index structure, performs confidence screening on the initial load prediction sequence group, obtains a credible load prediction sequence set, inputs a dynamic feedback adjustment framework, generates a power supply adjustment suggestion strategy, and improves the cooperative operation level of a heterogeneous computing power cluster and a diversified electricity system under the premise of ensuring the prediction accuracy and the real-time regulation.

This invention belongs to the field of hydrogen energy storage optimization technology, specifically involving a two-stage optimization method for hydrogen energy storage in industrial parks that considers demand-based pricing and hydrogen pricing. The steps include: establishing an objective function for industrial park operators with hydrogen loads to achieve optimal overall benefits in the pre-month optimization phase; establishing a probability distribution model of hydrogen load for fuel cell electric vehicles (FCEVs); establishing constraints for the safe operation of the hydrogen energy storage system, constraints for photovoltaic participation in the hydrogen energy storage system, and constraints for hydrogen balance and power balance in the hydrogen energy storage system; establishing an intraday model for upper-level players to optimize the park's maximum profit and an intraday model for lower-level FCEV users to minimize hydrogen refueling costs, and setting constraints; solving the two-level model to obtain the optimal two-stage optimization scheme for hydrogen energy storage. This invention enables industrial parks to have dual control over energy costs and hydrogen revenue, effectively reducing electricity penalties caused by exceeding demand limits and the risk of hydrogen supply and demand fluctuations.

This invention discloses a method for protecting the privacy of electric vehicle-assisted household electricity consumption, relating to the field of smart grid and vehicle-to-everything (V2X) integration technology. The method includes: acquiring household electricity load data, electricity price information, and electric vehicle battery status information to generate a target load sequence; constructing a constrained Markov decision process, using KL divergence as the cost function to measure privacy leakage, and employing a privacy threshold as a hard constraint; decomposing the privacy metric into single-step metrics through temporal decomposition and estimating them using a generative adversarial network (GAN); alternately updating the policy network and dual variables using the Lagrange multiplier method; and regulating the charging and discharging behavior of the electric vehicle through an energy management unit to optimize electricity costs while satisfying privacy constraints. This method achieves quantifiable and controllable privacy protection, reduces system deployment costs, and improves algorithm robustness.

This invention proposes a dual-control method and system for power regulation fees and AVC (Active Power Control) assessment at renewable energy power plants based on multi-objective collaborative optimization. Belonging to the field of renewable energy power generation prediction technology, the method includes: establishing separate power regulation fee cost models and AVC assessment cost models, and constructing a joint objective function based on these models; constructing real-time optimization models for active and reactive power regulation at each time step based on the joint objective function; and using a particle swarm optimization algorithm to perform real-time calculations of the real-time optimization models, outputting the optimal solutions for active and reactive power regulation at the next time step. This invention optimizes the power control of renewable energy power plants by comprehensively considering power regulation fees and AVC assessment factors, reducing plant operating costs and achieving optimal control of renewable energy power plant operation.

A method for coordinated scheduling of steel production and electricity based on a large language model, belonging to the field of intelligent manufacturing and information, is disclosed. The method includes: constructing a domain-specific large language model for production-electricity coordination; constructing a production-electricity coordinated scheduling optimization model; constructing a Markov decision process model; generating rolling plans based on the domain-specific large language model; and optimizing strategies using knowledge-driven reinforcement learning. This invention can achieve coordinated optimization of production efficiency and electricity costs while satisfying the coupling constraints of production and electricity.

This application discloses a billing and settlement method, system, equipment, and medium for battery swapping stations. The billing and settlement method includes: obtaining the total number of vehicles belonging to the same customer and the average daily operating mileage of each vehicle; obtaining a tiered service fee unit price based on the total number of vehicles and the average daily operating mileage of each vehicle, wherein the higher the total number of vehicles, the lower the tiered service fee unit price, and the higher the average daily operating mileage of each vehicle, the lower the tiered service fee unit price; determining the customer's battery swapping service fee based on the tiered service fee unit price; and obtaining the customer's settlement fee based on a minimum service fee, the customer's battery swapping service fee, and the customer's electricity bill. Using the embodiments of this application, by calculating service fees in tiers, the frequency of battery swapping by customers and the utilization rate of battery swapping stations can be increased, thereby increasing the profitability of battery swapping stations; at the same time, by setting a minimum service fee, basic operating cost recovery can be guaranteed, reducing the operating risk of battery swapping stations.

The building energy consumption optimization method and device, the storage medium and the computer device provided by the application obtain short-time and next-day load curves through short-term and medium-term load prediction, and based on the linkage regulation and control of the short-term load curve, environmental parameters and equipment energy efficiency, the regulation and control lag caused by rough prediction granularity is avoided, thereby improving the timeliness and accuracy of energy consumption response. At the same time, according to the next-day load curve, a peak-valley electricity price optimization strategy is generated, which can make the electricity consumption of each region more in line with the actual demand and electricity price fluctuation, fully utilize the peak-valley electricity price, and reduce the electricity cost. When the personalized electricity consumption scheme is executed, personnel distribution data is introduced for adjustment to ensure that the electricity consumption scheme is highly matched with personnel activities, unnecessary energy consumption waste is avoided, and then fine energy consumption management of each region in the building is realized, energy saving potential is fully tapped, and energy consumption optimization effect is improved.

The application discloses a method and equipment for optimizing arrangement of multiple types of wind turbines in an offshore wind farm and a readable medium, and belongs to the technical field of offshore wind farm planning and design and intelligent optimization algorithm. The method realizes integrated coding of wind turbine position, type and activation state by using four-dimensional chromosome coding, retains gradient information through a soft constraint smoothing penalty mechanism, corrects space violations by combining a guided multi-strategy mutation operator that fuses wind power engineering knowledge, balances global exploration and local development capabilities of the algorithm by supplementing population diversity repair and elite-random environment selection strategies. The application can minimize the penalty electricity cost on the premise of meeting the target capacity, adapt to irregular non-convex and offshore wind farms containing complex engineering constraints, and improve the economic benefits and layout optimization efficiency of the whole life cycle of the offshore wind farm.

This application discloses an adaptive energy-saving operation control system and method for escalators that detects passenger flow, relating to the field of intelligent control technology. It solves the technical problem in existing technologies where the threshold is generally set to a fixed value when comparing passenger flow with a threshold. This can lead to congestion and potentially stampedes during peak periods like holidays. This application utilizes data sensors to collect real-time passenger flow data entering the escalator area; it controls the escalator's start and stop based on the real-time passenger flow; it adjusts the escalator's operating speed based on the real-time passenger flow; it predicts passenger flow based on historical data; and it determines the escalator's maintenance and inspection time based on the prediction results. This system not only controls start and stop but also adjusts the operating speed based on real-time passenger flow. Appropriate speed reduction can bring exponential energy savings, directly reducing electricity costs and extending equipment lifespan.

Embodiments of the present application disclose a control method and device of a machine room air conditioner, an air conditioner and a storage medium. The method comprises: acquiring a peak-valley electricity price parameter of a current region, and determining a current electricity price period according to the peak-valley electricity price parameter; and adjusting a set temperature according to the current electricity price period. By implementing the method of the embodiments of the present application, the set temperature of the air conditioner is adjusted according to different strategies in different electricity price periods, so that the comprehensive electricity utilization rate of the peak-valley electricity price is improved, the comprehensive electricity fee is reduced, and energy is saved while maintaining normal operation of the machine room equipment.

This system provides a proposal system that can suggest changes to the operating schedule of equipment to improve economic efficiency. [Solution] The proposed system 10 includes an acquisition unit 23a that acquires the operating schedule of the equipment 35 installed in the house 70 and the electricity purchase price for each time period in the house 70; an estimation unit 23b that estimates the power consumption of the equipment 35; a calculation unit 23c that calculates a first electricity charge when the equipment 35 is operated in a first time period determined by the acquired operating schedule, and a second electricity charge when the equipment 35 is operated in a second time period where the electricity purchase price is lower than in the first time period, based on the acquired electricity purchase price and the estimated power consumption; and a proposal unit 23d that proposes operating the equipment 35 in the second time period by presenting the amount of savings determined by the calculated first and second electricity charges.

The application discloses a container plant factory energy-saving regulation and control method based on fuzzy reinforcement learning and distributed collaborative optimization, and relates to the technical field of industrial automation control. The method comprises the following steps: collecting in-box environment, equipment energy consumption, external environment, time-of-use electricity price and crop canopy image data; performing core derived feature calculation based on the data to construct a comprehensive state vector; inputting the comprehensive state vector into an intelligent decision-making model based on a deep Q network; using a fuzzy reward calculator, obtaining an instant reward value according to a crop stress index and an electricity price pressure level through fuzzy rule base reasoning, training the model based on the value and making a decision, and outputting macro joint action instructions containing temperature, light and ventilation intentions; inputting the instructions into a hierarchical rule collaborative optimization layer, sequentially checking and refining through safety and boundary rules, energy efficiency optimization rules and economic dispatching rules, generating device-level control instructions and executing the instructions, and effectively reducing system energy consumption and electricity cost on the premise of ensuring the stability of the crop growth environment.

This invention provides a two-stage electricity bill prediction method and apparatus based on user profiles and multi-dimensional data feature fusion. It belongs to the field of electricity bill prediction technology. The method includes the following steps: obtaining user profiles of the target user, as well as weather information, holiday information, other comprehensive information, abnormal event information, electricity price, and pricing rules corresponding to the prediction day; filtering feature values ​​for daily electricity consumption prediction based on the user profiles; inputting the filtered feature values ​​into a prediction model to obtain the predicted daily electricity consumption; determining whether there are abnormal events on the prediction day; if there are abnormal events, correcting the predicted daily electricity consumption by invoking a pre-established fitting correction relationship based on historical electricity consumption data according to the abnormal event information, obtaining the final predicted daily electricity consumption; and calculating the electricity bill for the prediction day based on the final predicted daily electricity consumption, electricity price, and pricing rules. This method can improve prediction accuracy while reducing the amount of data required for electricity bill prediction for ordinary residential users.

This invention discloses an energy storage control method, device, and microgrid. The energy storage control method includes: acquiring load data, electricity price sequences, and energy storage data; wherein the electricity price sequence includes set time periods for at least two electricity price tiers; predicting load electricity consumption according to the set time periods based on the load data to obtain an electricity consumption sequence; and calculating an economic target based on the electricity consumption sequence, electricity price sequence, and energy storage data; specifically, during the set time periods for low electricity price tiers, combining the energy storage data and electricity consumption sequence, determining that energy storage charging will be performed during the lowest electricity price period, and determining the charging power; during the set time periods for high electricity price tiers, combining the energy storage data and electricity consumption sequence, determining that energy storage discharging will be performed during the highest electricity price period, and determining the discharging power. The technical solution of this invention comprehensively considers the impact of electricity prices when predicting microgrid load, effectively reducing the electricity cost of the microgrid and contributing to increased economic benefits.

This application relates to the field of energy storage, disclosing an energy storage system, a control method for the energy storage system, and an energy storage cabinet. A static transfer switch directly collects the real-time power value of the load and transmits it to an energy storage converter. The energy storage converter directly adjusts its output power value in real time based on the real-time power value of the load transmitted by the static transfer switch. This direct and rapid data interaction between the static transfer switch and the energy storage converter effectively shortens the transmission path of the real-time power value of the load, reducing the response time of the energy storage system to load power fluctuations from hundreds of milliseconds to tens of milliseconds. This significantly improves the response speed of the energy storage converter to load power fluctuations, enabling the energy storage system to quickly track load power fluctuations and reduce the risk of reverse current. Furthermore, this energy storage system can more fully utilize new energy sources, reduce the consumption of grid power, and save on electricity costs.

The present application relates to a controller, a compressor plant having such a controller and a method for controlling the plant, the compressor plant comprising a compressor device and a heat recovery system providing recovered heat to a heat grid, the method comprising the steps of: providing a mathematical model of the compressor device and the heat recovery system; providing an electricity cost and / or a cost of the heat grid; providing a desired pressure of the compressed gas and a desired temperature of the heat grid; providing a control algorithm controlling the speed of the compressor device and the flow in the heat recovery system; from which control algorithm a control sequence of the flow in the heat recovery system and the speed of the compressor device is determined, taking into account the electricity cost and / or the heating cost of the heat grid, so that the total operating cost is minimized.

This invention provides a method and system for controlling railway regenerative braking energy and new energy access based on maximum demand optimization. The method includes: monitoring the real-time power output from the grid on the high-voltage side of the traction substation and the power output from the traction bus on the low-voltage side, and calculating the average power output within a preset rolling time window; determining historical load data, regenerative braking energy data, and configuration parameters of the energy storage system for the traction substation; determining a discharge power threshold based on a preset maximum demand reduction value; comparing the average power output with the discharge power threshold; determining a discharge control command when the average power output reaches or exceeds the discharge power threshold; and executing the discharge control command to control the energy storage system to release the stored regenerative braking energy and / or the accessed new energy power. This invention enables efficient synergistic utilization of regenerative braking energy and new energy sources, significantly reducing railway operating electricity costs while improving system reliability.

The utility model provides a kind of grid service power management equipment, the utility model belongs to electronic equipment technical field, including shell, display screen, MCU and temperature and humidity sensor;The shell front surface embeds display screen;The temperature and humidity sensor is arranged in the shell interior;Reset button and switch-on button are further provided on the shell;The display screen and temperature and humidity sensor are connected with MCU respectively;The MCU is communicated with server and obtains electricity fee data;The temperature and humidity sensor embeds temperature and humidity sensor circuit;Display screen embeds display circuit;Reset button and switch-on button connect soft start-up circuit;The MCU embeds corresponding MCU circuit;The MCU circuit is connected with temperature and humidity sensor circuit, display circuit and soft start-up circuit respectively.The utility model realizes in advance to judge the voltage amplitude of battery by soft start-up circuit, actively closes power supply, prevents that MCU is in some important process suddenly power off, and some important information is not in time stored or displayed.

This invention provides an industrial load optimization scheduling method and system that integrates AI intelligent agents and dynamic boundary constraints. The method utilizes AI intelligent agents to analyze production intentions and dynamically adjust process constraint boundaries to achieve optimized scheduling of industrial loads driven by price signals. This method can maximize the potential for cost reduction and peak avoidance for enterprises while ensuring production continuity and product quality. The actual measured target is to reduce electricity costs by more than 15% compared to the traditional static model.

The present application relates to the technical field of data monitoring, in particular to a kind of electric power enterprise marketing account intelligent check supervision method;According to the data discrete characteristics and local data fluctuation characteristics of the sequence of power consumption behavior characteristics, obtain suspected abnormal data points;According to the number characteristics, data difference characteristics and time interval characteristics of the similar data points of suspected abnormal data points, obtain significant fluctuation degree;According to the difference characteristics of significant fluctuation degree in the same position of suspected abnormal data points and other power consumption behavior characteristic sequences, the difference characteristics of local data change, obtain significant abnormal degree;According to the number characteristics of suspected abnormal data points, significant abnormal degree and time interval characteristics from current date, obtain the account risk coefficient of user.The present application carries out self-adaptive adjustment according to the account risk coefficient of electricity fee monitoring interval, carries out account check monitoring according to self-adaptive monitoring interval, so that electricity fee account check is more efficient and has pertinence, improves the accuracy of electricity fee settlement.