169 results about "Renewable energy consumption" patented technology

The invention relates to a regional energy internet multi-source coordinated optimization operation strategy considering time-of-use power price. The strategy is technically characterized by comprising the following steps that step 1, the initial data parameter of a regional energy internet system is inputted; step 2, cold/heat/electric flexible load response under the time-of-use power price is analyzed, and two classes of response models of cold/heat/electric flexible load are constructed; step 3, a regional energy internet system optimization scheduling model of the minimal economic cost and the operation constraint conditions thereof are constructed; and step 4, the regional energy internet system optimization scheduling model of the minimal economic cost is solved by using a Hessian interior point method. The regional energy internet renewable energy consumption level can be enhanced, and the strategy is also significant for realizing economic and safe operation of the system.

The invention discloses a relay communication system utilizing regenerable energy power supply and an energy-saving mode. The relay communication system is characterized in that traditional power grid energy supplies power for a base station, regenerable energy collected by an energy collecting device supplies power for a relay, and the relay processes received signals and forward the received signals; in a downlink link, the relay periodically sends channel state information and current energy storage to the base station, and the base station determines to select a direct connection transmission mode or a relay transmission mode according to load information, information fed back by the relay and the channel conditions and conducts corresponding downlink resource distribution; in an uplink link, the relay periodically sends the state information of channels from a user to the relay and the current energy storage to the base station, the base station combines the information, the load information and state information, of channels from the relay to the base station and from a user to the base station, obtained by self-estimation to choose a direct connection transmission mode or a relay transmission mode, and conducts corresponding uplink link source distribution. By the adoption of the method, communication quality can be ensured, and non-renewable energy consumption can be saved.

The invention discloses a distributed optimal operation method considering the uncertainty for an active distribution network, which comprises the steps of firstly, building an uncertainty model of photovoltaic output by using a robust optimization method in consideration of the uncertainty of the photovoltaic output; secondly, building an optimal scheduling model of the active distribution network, wherein the model takes the minimum operation cost as an objective function and comprehensively considers power flow constraints, safe operation constraints and output constraints of adjustable andcontrollable resources; then building an optimal scheduling model of multiple microgrids connected to the distribution network, wherein the model takes the minimum operation cost of the microgrids asan objective function and adds the problem of renewable energy consumption serving as a penalty function to the objective function; and modifying the distribution network model and the microgrid model based on a Lagrange function in consideration of a coupling relationship between the distribution network and the microgrids in tie-line power so as to build a distributed optimal scheduling model of the active distribution network.

The invention discloses a renewable energy capacity allocation method for promoting consumption, includes the following steps: (1) acquiring a power network topology and modeling according to the power network structure to form a data matrix capable of representing the characteristics of the power network, (2) to test the rationality of power network data and its adaptability to power network planning, (3) Analyzing the boundary conditions of various flexible resources in the power grid, (4) uploading the renewable energy and load power curve in the dispatching center, (5) establishing the renewable energy planning model which includes the planning layer model and the operation layer model, (6) solving the renewable energy planning model based on Matlab simulation platform; The invention comprehensively considers the constraint of source-network-load-storage, and establishes a model aiming at the renewable energy consumption based on the objective functions and constraint conditions ofthe planning layer and the operation layer, so as to obtain the multi-point layout and planning of the renewable energy with the highest renewable energy utilization rate and the largest renewable energy consumption capacity.

The invention relates to a multi-objective optimization scheduling method for a multi-supply power system based on an analytic hierarchy process, and belongs to the technical field of power system automation. The method comprises the steps: solving an established multi-objective optimization scheduling model of the multi-supply power system by adopting an NSGA-II multi-objective genetic algorithmto obtain a Pareto optimal solution set; normalizing the obtained target value Pareto optimal solution set by adopting a fuzzy membership function, scoring and sequencing each solution in the solutionset by using an analytic hierarchy process, and selecting an optimal scheduling solution; and obtaining a decision basis for optimal scheduling of the current multi-supply power system based on the optimal scheduling solution. According to the invention, the power system multi-objective optimization scheduling model is established, and the requirements of system economy, renewable energy consumption level, system safety and the like are integrated; the solutions are graded and sorted by adopting an analytic hierarchy process, and an optimal solution is selected. The obtained result gives consideration to subjectivity and objectivity of evaluation, is more reasonable, and facilitates safe, economical and stable operation of a power system and improvement of the new energy consumption level.

The invention discloses an optimal scheduling model for a park-level comprehensive energy system. The optimal scheduling model comprises an energy supply technology module, which models the park energy supply technology from the aspects of energy production, conversion, conveying, storage and the like; a terminal energy demand module, which depicts three types of industries and three terminal energy demands of cooling, heating and power of lives of residents; and a system operation optimization module. According to the optimal scheduling model for the park-level comprehensive energy system provided by the invention, firstly, load shedding sequence processing can be carried out according to reliability requirements under extreme conditions such as energy supply shortage and the like, and the energy supply reliability of important users such as hospitals is guaranteed; secondly, energy storage can be carried out in the electricity low valley period, and the renewable energy consumption capacity of a system is increased; and finally, stored energy can be used for energy supply during the heat supply peak period to perform thermoelectric decoupling, so that the flexibility of the system is enhanced, and a better application prospect is brought.

The invention relates to a comprehensive energy system day-ahead economic dispatching method and system, and the method comprises the steps: carrying out the prediction of wind power, photovoltaic power generation, electric load and thermal load of a comprehensive energy system, and obtaining a day-ahead prediction curve, namely a prediction result; and according to the prediction result, calculating an optimization target and constraint conditions of the comprehensive energy system, thereby executing day-ahead optimization, and obtaining the output of each CHP energy station in the comprehensive energy system, the output of the battery energy storage system, the output of the gas-fired boiler and the control instruction of the P2G equipment. According to the invention, the operation flexibility and the renewable energy consumption capability are improved.

The objective of the invention is to solve the disadvantage of insufficient flexibility of a comprehensive energy system caused by the fact that network access of an electric vehicle is not consideredin an optimization model established by a deterministic optimization method in the prior art. The invention discloses an economic dispatching optimization method for a microgrid comprising an electric vehicle charging load. The uncertainty and randomness of an electric vehicle charging load, wind-solar output and a CCHP system cooling, heating and power load are considered, an expected value model in stochastic programming is used for describing uncertainty and randomness of a charging load, an opportunity constraint form is used for representing the construction capacity of a charging facility so that the charging requirement of the electric vehicle can be met, and a multi-scene stochastic programming method is used for describing uncertainty and randomness of each stochastic variable. The expected target of the invention is to improve the flexibility of the comprehensive energy system, enhance the renewable energy consumption capability, reduce the comprehensive operation cost of the system in the operation period and provide necessary technical support for the economic dispatching operation of the microgrid.

The invention discloses a multi-stage power supply planning method for maximizing renewable energy utilization. The method includes: acquiring power supply planning data, system basic technical data,system operation constraint condition data and system operation prediction data; constructing a multi-stage power supply planning model, a power supply planning budget and construction limitation constraint, a system operation basic constraint, a thermal power plant operation constraint, a hydraulic power plant operation constraint, a renewable energy power plant operation constraint, a delivery channel operation constraint and a renewable energy power plant investment portfolio constraint by taking the maximum renewable energy utilization amount as an objective function; and inputting the obtained data into the constructed power supply planning model, performing solving to obtain a power supply planning construction scheme and a renewable energy consumption evaluation result, and carryingout multi-stage power supply planning to realize maximum utilization of renewable energy. According to the method, the defects in a traditional power supply planning method are overcome, the multi-aspect requirements of system operation can be better met, the utilization level of renewable energy sources is greatly improved, and the method has stronger guiding significance for actual constructionof multiple types of power supplies.

The invention relates to a power grid side energy storage device capacity calculation method considering the kilowatt-hour cost of energy storage devices, and belongs to the field of power system optimization planning and energy storage. The method comprises establishing a charging and discharging life model of multiple types of electrochemical energy storage devices, and converting the charging and discharging life of the energy storage devices into the charging and discharging kilowatt-hour cost of the energy storage devices; comprehensively considering the optimal planning objective function of the power grid, the constraint conditions of elements in the power grid and the investment operation cost of the power grid, and establishing a capacity planning model of the power grid side energy storage device considering the kilowatt-hour cost of the energy storage device; and finally, carrying out optimization solution on the model to obtain an optimization planning scheme of the capacity of the power grid side large-scale energy storage device with the lowest operation cost. According to the method, the kilowatt-hour cost of the energy storage devices is considered, the capacity calculation method suitable for the power grid side large-scale energy storage devices is provided, and after connection of the power grid side energy storage devices, the investment and operation cost of the power grid is reduced while the peak regulation and frequency modulation capacity and the renewable energy consumption capacity of the power grid are improved.

The invention discloses an integrated scheduling method for demand-side resources and renewable energy in an intelligent distribution network environment. The method comprises the following steps that: the basic information of a power distribution network system is obtained, wherein the power distribution network system comprises a scheduling center, at least one response agent in communication connection with the scheduling center, and at least one demand-side resource in communication connection with the response agents; a rolling optimization scheduling model under multiple time scales is established according to the basic information, wherein the scheduling model comprises an objective function and constraint conditions, wherein the objective function is used for calculating the operation cost of the power distribution network system, and the optimization objective of the scheduling model is to minimize the value of the objective function; the optimal solution of the scheduling model is calculated, wherein the optimal solution comprises the optimal load of each demand-side resource; and the load of each demand-side resource is adjusted to be the optimal load. Therefore, the distributed demand-side resources are scheduled orderly, the operation cost of the power distribution network system is reduced, peak load shifting can be realized, and renewable energy consumption can be improved. The invention also discloses a corresponding computing device.

The invention provides a vehicle wind energy conversion device, which comprises a wind collecting cover, of which the front part is provided with a wind collecting port and the rear part is provided with a first wind bin which is communicated with the wind collecting cover. The rear part of the first wind bin is provided with an air outlet port. The first wind bin is provided with a first impeller, the shaft of which passes through the first wind bin to the outside. A first driving wheel is arranged on the shaft and is connected with the driving wheel of an engine through a first transmission belt. The engine is connected with the AC/DC converter through wires. The AC/DC converter is connected with a storage battery through wires. With a rational structure, the vehicle wind energy conversion device can mutually transform the wind energy and the electric energy, convert the wind energy generated by air flowing relative to the car body into electric energy or pressure potential energy for storing in the vehicle traveling, particularly downhill, and provide auxiliary driving power for the vehicle in uphill traveling, thus greatly lowering the non-renewable energy consumption and effectively saving energy.

The invention discloses a comprehensive energy storage optimal configuration method and system. The method comprises the steps of giving the energy demands of a system at each time period and the maximum output of an energy production unit in the system at each time period in combination with the architecture of a user-side comprehensive energy system; establishing a physical model of an energy conversion unit and an energy storage unit in the system; and establishing a comprehensive energy storage optimal configuration model with the minimum load variance, the minimum renewable energy sourcereduction amount and the minimum comprehensive energy storage capacity as targets , wherein the optimal solution of the model is the optimal capacity which should be configured for various types of energy storage devices. The method can be applied to user-side comprehensive energy systems of various specific architectures, and through multi-energy complementation and multi-energy flow coordinatedoptimization scheduling, the effects of the user-side comprehensive energy systems on reducing the load peak-valley difference of a power grid and improving the renewable energy consumption capacity are fully excavated. According to the method, electric heating and cooling comprehensive energy storage can be coordinated and matched to promote peak load shifting and renewable energy consumption, and the operation safety and economy of the power system are effectively improved.

The invention discloses a capacity optimization configuration method for a power distribution network composite energy storage device. The method comprises the following steps of: (1), constructing acalculation model of a state of charge (SOC) of the energy storage device, (2) acquiring a load value of an independent microgrid system, (3) proposing an energy distribution strategy based on a low-pass filtering principle, (4) establishing a target function, (5) establishing constraint conditions of the target function, (6) constructing a simulated annealing particle swarm algorithm, (7) acquiring related parameters of a storage battery and a super capacitor, and (8) solving to obtain parameters such as the storage battery capacity, the super capacitor capacity andannual average cost, and further applying the steps (1) and (3) to obtain the charging and discharging power of the storage battery and the super capacitor. By optimizing and configuring the capacity of the power distribution network composite energy storage device, the distributed renewable energy consumption capacity of the power distribution network can be remarkably enhanced, and the power quality and the safety of power supply of the power distribution network under the condition that a high-proportion distributed power supply is connected are improved.

The invention discloses a data driving scheduling method based on renewable energy consumption capability. The method comprises the steps: obtaining a scheduling result according to the deviation between the actual output and predicted output of renewable energy, the safety constraint of a power grid, i.e., the conditions required by the power grid for maintaining safe and stable operation, and the capacity and climbing capability of a thermal power generating unit; constructing constraint conditions needing to be considered when the renewable energy consumption range of the power grid is constructed; establishing a variable distribution robust joint chance constraint according to the probability distribution characteristic of the deviation between the actual output and the predicted output of the renewable energy source, and measuring the absorption capacity of the renewable energy source; based on the variable distribution robust opportunity constraint and the renewable energy consumption capability, establishing a joint optimization random scheduling model by taking the power grid pre-scheduling cost and the renewable energy consumption probability as target functions; then converting the distribution robustness joint chance constraint into a second-order cone constraint, converting a two-stage distribution robustness optimization problem into a second-order cone programmingproblem by applying a robustness optimization standard technology, obtaining an absorption range of renewable energy sources by solving, and issuing the absorption range to a corresponding renewableenergy source unit; the method is used as scheduling guidance of renewable energy units. According to the method, the energy consumption capacity is remarkably enhanced, and the sample exterior performance of renewable energy consumption is improved.

The invention provides an integrated energy system economic dispatch optimization method, system and device, and a storage medium. The method comprises the steps of obtaining original data related to a day-ahead economic dispatch scene of an integrated energy system; according to the original data, establishing an integrated energy system day-ahead economic dispatch optimization objective function which takes integrated energy system economic operation minimization including energy purchase cost and charging and discharging depreciation cost of electric energy storage as an objective, establishing an integrated energy system day-ahead economic dispatching constraint condition covering power balance, external energy supply and equipment operation of the integrated energy system; and based on the day-ahead economic dispatching optimization objective function of the integrated energy system and the day-ahead economic dispatching constraint conditions of the integrated energy system, solving an optimal day-ahead economic dispatching scheme of the integrated energy system by adopting a multi-group particle swarm algorithm. According to the method, energy supply is optimized, transverse cooperative complementation and longitudinal gradient utilization among multiple energies are achieved, distributed renewable energy consumption is promoted, and the energy utilization rate is increased.

The invention discloses a cluster division method of a power distribution network based on high-proportion renewable energy. The method comprises the following steps: 1) abstracting the power distribution network into a network formed by connecting nodes and edges; 2) randomly changing a plurality of first preset values in the network into second preset values, and obtaining a plurality of individuals corresponding to the changed network; 3) obtaining a cluster performance index of the current individual according to the modularity index and the surplus electric quantity index; 4) judging whether the iteration is converged or not; 5) if yes, taking the changed connection architecture of the network as a target connection architecture; And 6) if not, performing individual selection, individual intersection and individual variation processing, taking an individual corresponding to the processed network as a current individual, and returning to execute the step 4) until a target connection framework is obtained. The invention discloses a power distribution network cluster division device based on high-proportion renewable energy sources. By applying the embodiment of the invention, the renewable energy consumption capability of the system can be improved through the cluster.

The invention relates to a method for analyzing and calculating the renewable energy consumption ability based on priority scheduling, which comprises the following steps: (1) constructing a power grid analysis model; (2) fitting the generation plan and load prediction data; (3) fitting power outage plan data; (4) carrying out simulation computation; (5) checking the renewable energy consumption situation; (6) adjusting the renewable energy generation plan; and (7) optimizing the renewable energy consumption ability. The renewable energy consumption ability analysis and calculation enters a fine stage. The generation plan is scheduled and compiled based on full consumption of renewable energy. A feasible intelligent method for analyzing and calculating the renewable energy consumption ability is put forwarded, which can meet the need of Internet development of renewable energy in the future.

The invention discloses a full-operating pre-coagulating type heat-source tower device. The full-operating pre-coagulating type heat-source tower device comprises a main solution loop, a pre-coagulating and spraying frost restrain loop and an air loop, wherein the main solution loop and the pre-coagulating and spraying frost restrain loop are connected in parallel; solutions or cooling water enters from the solution inlet end of a heat-source tower, and is divided into two parts in a parallel-connection mode after passing through a first electric driving three-way valve, and then the two parts enter the main solution loop and the pre-coagulating and spraying frost restrain loop respectively, and are gathered in a liquid collecting reservoir. The solution regeneration load of a heat-source tower heat pump unit under various winter heating operating conditions can be reduced; the solution renewable energy consumption is reduced; meanwhile, cooling water consumption in the summer refrigerating operation is reduced; the winter and summer comprehensive performance of a heat-source tower heat pump system is improved.

The invention relates to an electric vehicle cluster charging power optimization method for promoting renewable energy consumption. The method comprises the following steps: S1, establishing a mathematical model of electric vehicle collector combination configuration and operation, and according to the model, determining an objective function that minimizes the cost of load power supply and the total power loss cost of the electric vehicle, a general constraint condition of power flow analysis and a constraint condition of system stable operation; S2, formulating a two-stage algorithm, and dividing variables into two classes, namely a main problem of EVA optimal configuration and a sub-problem of an optimal charging strategy of a single electric vehicle; S3, dividing the optimized variables of the main-sub-problems into two parts of EVA optimal configuration and power adjustment under the optimal configuration, and iteratively solving the main-sub-problems until the convergence condition is met so as to ensure that the charging plan of each electric vehicle can meet the requirement of the overall target. According to the method, under a given EVA configuration, the optimal configuration of the EVA and the charging power adjustment of the electric vehicle can minimize the total cost.

The invention discloses a household multi-microgrid system optimization control method based on event-driven automatic demand response. The method comprises the steps of: building a multi-microgrid system model according to the power supply and consumption information of a supply side and a demand side of a household multi-microgrid system; analyzing the operation condition of the household multi-microgrid system, determining an event type and a triggering condition, and establishing an event triggering mechanism; establishing a household resource scheduling model for the event type in the microgrid, and guiding a network access load to complete self power consumption optimization by taking the lowest daily operation cost of the household microgrid as a target and combining the real-time electricity price and the scheduling potential; and establishing an energy sharing model for power interaction between microgrids, calculating the energy level of each sub microgrid in the system withthe purpose of maximizing the overall interaction benefit of the system, and deciding the interaction power between the microgrids according to the historical participation degree and related scheduling criteria of the sub microgrids. According to the invention, the operation cost of the household multi-microgrid system is effectively reduced, the renewable energy consumption rate of the system isimproved, and the automatic demand response of the system is achieved.