85 results about "Energy cost" patented technology

This application relates to the field of energy dispatching, and in particular to a method and system for distributed energy storage dispatching based on multi-energy collaboration. The method includes: acquiring a set of factory order information; based on this, extracting and fusing multi-dimensional production value features to generate a dynamic production value assessment information set; based on this, combined with preset energy cost constraints, calculating dynamic electricity value thresholds and making global energy dispatching strategy decisions to generate an energy dispatching strategy information set; acquiring a set of energy supply influencing factors; based on the energy dispatching strategy information set and the energy supply influencing factors set, performing multi-timescale rolling optimization and global preset energy allocation to generate an energy allocation execution instruction set; based on this, issuing and executing dispatching instructions and dynamic production compensation for production lines and energy storage layers, generating and outputting a multi-energy collaborative dispatching report. This application can improve the economic efficiency of factories during energy dispatching.

A federated learning framework including household agents configured to continuously learn model parameters for managing charging periods and discharging periods of household batteries, and microgrid agents to maximize use of local energy based on a pricing policy, including accessing power from other microgrids when there is insufficient local energy to cover local demand. and selling surplus energy to the other microgrids when power generation by the microgrid surpasses the local demand. Each household machine learning agent is configured to control household energy demand from and supply to a microgrid which they are connected in order to minimize household energy cost while adapting to changes in the energy price that is determined based on the pricing policy of the microgrid agent that encourages reduction of carbon emission. A federated learning engine combines the model parameters from the household machine learning agents to update a global household machine learning agent.

The present application provides a kind of unmanned aerial vehicle path planning method and related equipment based on ecological sensitivity, obtain the multiple predicted paths between the current node and the next node of unmanned aerial vehicle;Unmanned aerial vehicle corresponding total power consumption and ecological sensitivity operator are calculated in advance when unmanned aerial vehicle flies along the predicted path;Based on the total power consumption and ecological sensitivity operator corresponding to unmanned aerial vehicle at each time point when unmanned aerial vehicle flies along the predicted path, the energy cost value corresponding to the predicted path is determined.In the case where the total power consumption is the same, the greater the ecological sensitivity operator, the lower the energy cost value, the predicted path with the minimum energy cost value is selected as the main path between the current node and the next node of unmanned aerial vehicle, so as to induce the path to deviate from sensitive area.

This invention belongs to the field of building energy consumption monitoring technology and provides an anomaly detection method based on ARIMA residuals. It utilizes an ARIMA model to extract the residual sequence after the linear trend of data, learns normal patterns using LSTM-AE, and identifies anomalies. Simultaneously, it combines correlation coefficient matrices and anomaly propagation matrices to analyze fault propagation paths, featuring high detection accuracy and strong interpretability. This invention improves anomaly detection accuracy and effectively reduces false alarm and false negative rates. It also effectively handles sparse data, making it suitable for scenarios such as building energy consumption monitoring. By constructing correlation coefficient matrices and anomaly propagation matrices, it analyzes the propagation paths and impact mechanisms of anomalies in multi-parameter systems, providing a reliable basis for anomaly tracing and system optimization. Through practical application, this invention helps enterprises promptly identify and resolve energy waste problems, save energy costs, optimize energy management systems, and improve energy utilization efficiency.

The present application relates to electric bus charging joint scheduling technical field, provide electric bus fixed and dynamic wireless charging joint scheduling method and system. Electric bus fixed and dynamic wireless charging joint scheduling method includes that fixed and dynamic wireless charging coordination problem is modeled as limited time domain constraint Markov decision process, and then the power of fixed and dynamic wireless charging is determined as charging scheduling strategy based on system state, and the optimization objective function is constructed as minimizing cumulative expected energy cost within the set operation period; the optimization objective function is solved by using the rolling time domain model predictive control method, and the terminal SOC shortage cost is decomposed into the expansion and contraction of the stage cost by using the convex potential function, while keeping the optimal charging scheduling strategy, the end of the day requirement is internalized in the rolling time domain of the rolling time domain model predictive control method.

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.

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.

System (10) for distributing generated electricity to an electrical network (17) and comprises at least one generator (11). A power carrying link (12) from the generators (11) to the grid is also connected to at least one service module (18), that incorporates equipment for performing a power consuming service unrelated to operation of the wind turbine and network. The service may be a computing function and benefits from being located “behind-the-meter” where cheaper energy costs are possible. For example, electricity generated by the wind turbines can be routed directly to the module(s) for use. A wind turbine generator foundation or a standalone platform configured to receive a removeable service module is also described.

The application provides an SCR catalyst regeneration plant energy consumption regulation system and method, the system comprises an equipment energy consumption collection module, a production plan optimization module and a control module; the equipment energy consumption collection module comprises various sensors arranged at each key equipment and process node of the plant, is used for collecting equipment energy consumption, process parameters and production data in real time, and is uniformly uploaded to a flexible load analysis module through an industrial communication network; the production plan optimization module is used for constructing and solving a multi-objective optimization model according to the equipment energy consumption, process parameters and production data collected by the equipment energy consumption collection module in real time, and generating an optimal production scheduling strategy; the control module is used for converting the optimal production scheduling strategy into control instructions of each process equipment and controlling automatic operation of each process equipment. One technical effect of the application is to maximize the reduction of energy cost, obtain demand side response income, and finally realize the minimization of comprehensive operation cost.

This invention belongs to the field of workshop scheduling optimization, specifically involving a batch flow remanufacturing system scheduling optimization method based on a rework mechanism. It includes constructing a dual objective: minimizing the total completion time for remanufacturing all batches of scrap products and minimizing the total cost of remanufacturing all batches of scrap products. The total cost of remanufacturing all batches of scrap products includes: the energy cost of the disassembly workstation, the energy cost of the reprocessing subsystem, the energy cost of the reassembly workstation, the system's basic energy cost, and additional costs incurred by rework and scrapping. A weighting coefficient is introduced to transform the dual objective into a single objective, constructing a comprehensive objective function. This comprehensive objective function is used as the fitness function of the whale optimization algorithm. The optimal solution output by the whale optimization algorithm is the best scheduling optimization scheme. This invention significantly improves the overall operating efficiency and sustainability of the system while comprehensively improving the cost-effectiveness of the remanufacturing system.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for user plane traffic gating based on energy cost. A policy control function, PCF, may be configured with information related to energy cost criteria or strategy. The PCF may be triggered, using the information, to obtain energy cost information from the network, e.g., from an energy efficiency control function, EECF. The PCF may use the energy cost measurement / information obtained from the EECF, and the energy cost criteria or strategy information to determine whether and which service flows need to be blocked. The PCF may include this information in one or more policy and charging control, PCC, rules that correspond to the service flows of interest, and may provide this information to a session management function, SMF, to further send corresponding one or more N4 rules to the user plane function, UPF.

This utility model discloses a photovoltaic energy storage integrated power generation device with a multi-scenario small off-grid dual power supply module, including a first foldable lightweight photovoltaic array and a supporting ground. A first support rod, a second support rod, a third support rod, and a fourth support rod are fixedly connected to the supporting ground. A first dual power supply module and a first load are fixedly connected to the first support rod. This utility model converts light energy into electrical energy through the first, second, third, and fourth foldable lightweight photovoltaic arrays and stores it in the first, second, third, and fourth dual power supply modules, respectively. The first, second, third, and fourth loads consume the stored electrical energy for daily use. It can be quickly deployed by a single person, is simple and convenient to operate, and reduces long-term energy costs by 60% with diesel power generation, thus significantly reducing costs.

The invention is entitled "Dynamic Nonlinear Optimization of Battery Energy Storage Systems." The invention provides a system and method for optimizing a battery energy storage system (BESS) that can involve: inputting data to an echo state network, the data relating to operation of a battery energy storage system and including one or more of: load data, renewable energy data, non-renewable energy data, carbon emissions, carbon credits, and weighted energy costs; and optimizing the operation of the battery energy storage system based on the data input to and processed by the echo state network and relating to the operation of the battery energy storage system.

Method for controlling a mobility concept for traffic relief in an agglomeration by means of at least one driving unit (1, 1') operating autonomously with an electric drive unit and an energy distribution system with at least one electrical energy storage device (3) and for controlling an energy distribution by means of the energy distribution system, characterized in that - when a vehicle (2) requests a ride with a driving unit (1, 1'), the vehicle (2) transmits its planned route, an estimated charge level of its electrical energy storage upon arrival of the vehicle (2) at a pick-up point for a driving unit (1, 1'), an estimated energy requirement for carrying out an individual journey of the vehicle (2) from a starting point to a destination point, and an amount of electrical energy that the vehicle (2) may make available to the energy distribution system to an application program (A), - using the application program (A) depending on traffic data and / or weather data and / or energy costs relating to the route, a fare (M) for the vehicle (2) as well as a possible pick-up location and a predicted travel time are determined and sent to the vehicle (2) and to the driving unit (1, 1'), wherein - if the vehicle (2) is confirmed as having been taken along, a driving unit (1, 1') is assigned to the vehicle (2), whereby if the vehicle (2) uses the electrical energy provided by the energy distribution system during the transport of the vehicle (2) with the driving unit (1, 1') or if the vehicle (2) feeds energy into the energy distribution system of the driving unit (1, 1'), the determined transport price (M) for the vehicle (2) is adjusted accordingly.

The application discloses a control device and method for oil residue gasification non-normal parking and pressure continuous starting, and the device comprises a gasification furnace, a cyclone separator and a water washing tower. The gasification furnace is connected with multiple process pipelines, and cut-off valves, regulating valves, sensors and other components are arranged on the pipelines to form a complete monitoring and control system. The method comprises the following steps: after the gasification furnace is non-normally parked, the oxygen, the feed oil and the synthesis gas are isolated, the system is depressurized, and the oil passage is purged; after fault treatment is completed, a pressure continuous starting program is directly triggered, the start-up pumping is closed, the stable furnace chamber pressure is established, the steam flow is established, and the feeding sequence is started. The whole process does not need to be cooled, replaced and re-heated. The application realizes the rapid pressure continuous starting of the gasification furnace after non-normal parking, greatly shortens the production recovery time, saves the material and energy cost, improves the control precision and the production continuity, is suitable for the existing oil residue hydrogen production gasification furnace system, and has low application cost.

Various aspects of this disclosure relate generally to wireless communication. In some aspects, a user equipment (UE) can receive signaling indicating a plurality of energy values ​​associated with communication with a network node, wherein each of the plurality of energy values ​​is associated with a different configuration from a plurality of configurations for communication with the network node. The UE can communicate with the network node according to a first configuration associated with a first energy value among the plurality of energy values. Numerous other aspects are described.

This invention provides a data center energy security scheduling method, system, equipment, and medium, belonging to the field of computer technology. Specifically, it models the problem as a constrained Markov decision process (CMDP), where the agent's objective is to minimize energy costs while adhering to a security constraint to ensure a continuous and sufficient power supply and prevent power shortages. A Lagrange-based constrained policy optimization algorithm is employed to learn a control strategy that conforms to predefined constraints. Under the premise of ensuring sufficient power supply to the data center, it effectively addresses the intermittency of renewable energy and electricity price fluctuations, achieving optimal operating costs and significantly improving the reliability and economy of microgrid operation.

The application discloses a kind of wind turbine unit optimization layout method based on three levels dynamic variation rate, comprising the following steps: step one: obtaining target wind farm information, including (1) the annual average wind resource information of target wind farm;(2) unit specification parameter;(3) wind farm planning area boundary;Step two: combined with fan wake wind speed and turbulence model, calculate annual total average power generation and evaluate full life cycle degree electric cost;Step three: the wind farm planning area is gridded, with the optimization target of flat standardization energy cost, carries out unit grid location preliminary optimization using the improved genetic optimization algorithm based on three levels dynamic variation rate, obtains several grid optimization schemes by integration theory;Step four: according to the preliminary optimization result of grid location, constructs the grid boundary of each candidate unit, carries out fine coordinate position optimization in corresponding grid using adaptive weight particle swarm optimization algorithm, and obtains the final unit layout scheme.

This invention relates to a method for increasing the biomass of *Scenedesmus* under light and its application. The method includes the following steps: inoculating *Scenedesmus* stock solution into a sterile liquid culture medium, and culturing the *Scenedesmus* under light using a composite spectrum of white and red light. This invention develops a novel method for culturing *Scenedesmus*, namely, culturing the *Scenedesmus* under light using a composite spectrum of white and red light. This method is simple to operate and easy to implement. It can significantly improve the growth rate and biomass accumulation of *Scenedesmus*, enabling high-quality, large-scale production; it can also improve light and electrical energy utilization efficiency, reduce energy costs, and solve the technical challenge of simultaneously increasing production and reducing energy consumption in *Scenedesmus* cultivation.

This invention relates to the field of intelligent egg roll production, providing an energy-saving intelligent control method and system for a frequency converter-driven egg roll production line. The method includes the following steps: acquiring real-time electricity price data and target output data; calculating a set of process parameters using a preset baking energy consumption dynamic model; generating corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis, and obtaining product batch data including two characteristic identifiers: slightly under-progressive and slightly over-progressive; generating global scheduling instructions for egg rolls with different characteristic identifiers based on the product batch data, status parameters, and preset target quality parameters; acquiring cycle power consumption and output data and calculating the comprehensive energy cost, generating deviation data by comparing it with the prediction results of the baking energy consumption dynamic model. This invention utilizes the unique heat transfer properties of egg roll production to transfer energy utilization, effectively reducing comprehensive energy consumption while ensuring stable production.

This invention discloses a method and system for calculating the revenue of distributed photovoltaic (PV) systems participating in peak-shaving ancillary services. The system includes a data acquisition module, an information storage module, and a revenue calculation module. By acquiring historical and future meteorological information, it predicts the user's power generation and consumption data. Simultaneously, it acquires information such as the time-of-use electricity price in the province where the distributed PV user is located, the PV feed-in tariff, demand information in the peak-shaving ancillary service market, clearing volume and price information, and user contract information. It calculates the user's grid-connected electricity and self-consumption rate, and determines the feasible time periods for the user to participate in peak-shaving ancillary services. Finally, it calculates the user's subsidy revenue, curtailment losses, and investor losses for participating in peak-shaving ancillary services, thereby obtaining the net revenue of the distributed PV user. This invention provides a scientific revenue assessment scheme for distributed PV users participating in peak-shaving ancillary services, assisting them in simultaneously achieving the dual goals of maximizing power generation revenue and optimizing energy costs.

The application discloses a kind of park integrated energy system double-layer optimization scheduling method and system, method includes: constructing park integrated energy system operation framework, modeling each equipment in operation framework;Establish the vehicle-to-grid interaction model considering the temporal and spatial distribution characteristics and charging and discharging behavior of electric vehicles, and the ice storage air conditioning load model;Set considering the PIES double-layer optimization scheduling strategy of vehicle-to-grid interaction and ice storage air conditioning coordination, define upper layer as PIES energy scheduling layer, lower layer as flexible load response layer;Solve electric vehicle optimization model and ice storage air conditioning optimization model, solve system operation cost optimization model, according to the solution result, each equipment in park integrated energy system is optimized and dispatched;The application has the advantages that: EV and IAC are deeply integrated, and collaborative scheduling is carried out, and double-layer optimization scheduling strategy is used, so that economic and low-carbon operation of system level is realized under the premise of guaranteeing user energy cost and comfort.

This invention belongs to the field of energy demand forecasting technology, and discloses a method and system for forecasting regional energy system demand. The method includes: determining the primary energy demand of each industry in a target region; constructing a calculation model for carbon emissions and energy utilization costs in the target region based on the primary energy demand of each industry, carbon emission coefficients of various primary energy sources, and utilization cost coefficients of various energy sources; constructing an optimization function based on determined energy utilization constraints and carbon emission constraints; solving the optimization function to obtain the optimal solution; and obtaining energy consumption, carbon emissions, and energy cost data for all industries in the target region based on the optimal solution, the target region carbon emission calculation model, and the energy utilization cost calculation model. This invention constructs an optimization function based on energy utilization constraints and carbon emission constraints, with the optimization objectives of minimizing total energy costs and achieving carbon neutrality in the energy system, realizing the overall simulation of energy system demand and carbon emissions under multiple scenario conditions.

This invention provides a refrigerant heat exchange mechanism, operating device, and operating machine, comprising a heat exchanger, at least one pre-amplifier unit, and a flow control unit. The at least one pre-amplifier unit has at least one refrigerant supply path in the heat exchanger unit for outputting refrigerant to the flow control unit. The flow control unit has a first selective flow path and a second selective flow path in the heat exchanger unit. The first and second selective flow paths are connected to the refrigerant supply path of the pre-amplifier unit and are configured with a switching structure to switch the refrigerant flow from the refrigerant supply path to the first selective flow path and / or the second selective flow path according to the requirements of the cold test operation. This not only controls the refrigerant flow rate and low-temperature load capacity, but also facilitates the relative adjustment of the compressor's operating power and the heater's heating power, thereby effectively saving energy costs.

The present invention relates to the technical field of power systems. Disclosed are a day-ahead and intraday electricity-carbon joint trading method based on carbon emission baseline decomposition, and a system. The method comprises: performing abnormal value detection and processing on historical energy consumption data of users; performing carbon emission decomposition on the basis of historical energy consumption curves of the users to obtain carbon emission baselines of different users; and establishing day-ahead electricity-carbon joint trading considering source-load uncertainty and intraday electricity-carbon joint trading considering the trading bias cost. In the day-ahead and intraday electricity-carbon joint trading method based on carbon emission baseline decomposition provided by the present invention, carbon emissions of multiple entities in a park are decomposed to the hourly level, thereby optimizing carbon emission control accuracy in the park; by optimizing the power purchase and sale cost, the distributed energy cost, and the carbon trading cost, the trading bias caused by inaccurate prediction is reduced; a model that accounts for the trading bias cost is constructed, thereby improving the flexibility of response to the market. The present invention achieves better effects in terms of control accuracy, trading bias, and flexibility.

This utility model relates to the field of agricultural product production technology and discloses a multi-stage drying device for agricultural product production, including a drying box. An air outlet pipe is fixedly installed on the outer wall of the drying box, and a preheating box is fixedly installed at one end of the air outlet pipe. A heat exchange tube one and a heat exchange tube two are fixedly installed inside the preheating box. The upper end of the heat exchange tube one is connected to the bottom end of the heat exchange tube two. The bottom end of the heat exchange tube one extends to the outer wall of the preheating box, and the upper end of the heat exchange tube two extends to the upper outer wall of the preheating box. The technical effect is that it can effectively recover the heat that would otherwise be directly emitted and wasted, and use it to preheat the fresh air entering the device, which greatly reduces the additional energy consumption during the operation of the device, lowers energy costs, improves energy utilization efficiency, and shortens the drying time of agricultural products.

This invention discloses a reentrant hybrid flow shop scheduling method based on the IMOEA / D algorithm. Specifically, it first establishes a BPM-RHFSP multi-objective optimization mathematical model with the optimization objectives of minimizing maximum completion time, total delay time, and total equipment energy cost. This transforms the actual production job scheduling problem into a combinatorial optimization mathematical model problem. Then, based on IMOEA / D, it solves the problem model by designing a variable threshold batching strategy for batch processing job decoding; multi-region global search and random variable neighborhood search; and reinforcement search for individuals within the elite solution set. This invention can effectively coordinate the processing of multiple equipment, improve the rationality of resource allocation, shorten the workshop manufacturing cycle and product delay time, and reduce energy costs.

Instead of the Peripheral Component Interconnect (PCI) Express (PCIe) link speed modulation and the PCIe link power state being utilized separately, the PCIe link speed modulation and PCIe link power state strategies are used in combination. The combination balances between the PCIe front end energy cost, the backend energy cost, and the quality of service (QOS). The performance / power space of the solid state drive (SSD) is mapped to the PCIe link speed modulation and PCIe link power state strategies to configure four distinctive zones, which provide high QoS at high performance points with a graceful performance degradation towards the lower performance points. A power / thermal constrained system dictates a certain performance that the SSD will be able to satisfy optimally by using both methods at different performance points.