165results about How to "Realize peak shaving and valley filling" patented technology

The invention discloses an intelligent electric meter system for residents for an intelligent smart grid. According to the intelligent electric meter system for the residents for the intelligent smart grid, one intelligent electric meter is arranged in home of each resident, two control terminals are respectively arranged on each controlled electric appliance and each user switch, and each distributed power supply is provided with a distributed power supply access device; each control terminal and the distributed power supply access device are interconnected through a PLC (Programmable Logic Computer) communication network, and the intelligent electric meter and a high-class measuring system AMI (Advanced Metering Infrastructure) carry out information interaction. The intelligent electric meter system is suitable for the residents having tiered pricing for electricity and time-sharing pricing for electricity, and aims at minimum electric charge expenditure of users, and is used for intelligently controlling the electric appliances and the distributed power supplies of the residents so as to realize peak clipping and valley filling of the electric charge, and provide power supply quality and power supply reliability.

The invention discloses a resident intelligent energy management system suitable for an intelligent power grid. Due to the adoption of the resident intelligent energy management system, peak and off peak load regulation of a power load is realized, and the power quality and power reliability are improved. An intelligent energy management controller and an intelligent electric meter are arranged in the home of each resident; a control terminal is arranged on each controllable domestic appliance and a user switch respectively; a distributed power supply accessing device is arranged on each distributed power supply; the controller is connected with the control terminal and the distributed power accessing device through a Zigbee wireless communication network; the intelligent electric meter is connected with the distributed power supply accessing device and the controllable domestic appliance; the controller is communicated with the intelligent electric meter through a bus; the intelligent electric meter is further connected with the secondary sides of a voltage mutual inductor and a current mutual inductor; the controller undergoes information interaction with a high-level measuring system AMI (Advanced Metering Infrastructure) of a main station through Ethernet communication; the controller is used for controlling switching of the control terminal and the distributed power supply accessing device; the control terminal is used for submitting the state of the switch to the controller; the controller is used for monitoring the state of the switch.

The invention discloses a household load scheduling method comprising the following steps of: classifying all loads according to different power utilization characteristics and user habits; determining a control scheme; establishing a load power utilization model; performing solution by using a discrete optimization algorithm based on molecular kinetic theory; obtaining, analyzing and processing a result. The method analyzes the operating characteristics and the use characteristics of various electric appliances at home, establishes a scheduling mathematic model according to classifications, performs multi-target optimization computation by using the discrete optimization algorithm based on molecular kinetic theory on a multivariable coordinative optimization condition, solves a household load scheduling solution set with the lowest power charge, the least influence on user living habits, and the maximum contribution to power stability. The method is beneficial to evaluation of smart home environment power utilization participation demand response potential and can be further used in a series of problems such as household power utilization smart home system load control and the like.

The invention relates to a multi-source heat pump cold and hot water unit integrating solar energy, air energy and sleeve accumulated energy. The multi-source heat pump cold and hot water unit is mainly composed of a solar thermal collector, an energy storage heat exchanger, an outdoor air heat exchanger, a compressor, a thermal storage water tank, a user side heat exchanger, a gas-liquid separator, a heat collecting water pump, a user circulating water pump, an electromagnetic valve, a motor-driven three-way reversing valve, a motor-driven four-way reversing valve, a start-stop valve, a throttling valve, a one-way valve and the like; according to different outdoor climatic conditions, multiple operation modes such as direct solar heat supply, living hot water produced by solar, solar heat accumulation, heat supply of an energy storage heat pump, heat supply of an air source heat pump, energy storage and air source heat pump combined heat supply, living hot water produced by an air source heat pump, cold supply of air source heat pump, air source heat pump cold accumulation, heat pump cold accumulation and production of life hot water, and cold accumulation cold supply are realized. The complementary utilization of air energy and solar energy and two-way utilization of cold and heat of a heat pump unit are realized, and one set of equipment is adopted to realize heating, refrigeration, energy storage and living hot water supply.

The invention discloses a multi-time scale demand response-based concentrated hybrid energy storage synergic control method. The multi-time scale demand response-based concentrated hybrid energy storage synergic control method comprises the following steps of S1, building a user multi-type demand power utilization characteristic model; S2, building a multi-time scale demand response model; and S3,determining a synergic control strategy of a concentrated hybrid energy storage system according to the multi-type demand power utilization characteristic model and the multi-time scale demand response model. According to the method, the charge-discharge strategy of the concentrated hybrid energy storage system is made according to the charge-discharge characteristics of the storage battery and the supercapacitor, the charge state and the user multi-type demand characteristic, the clean energy absorption is facilitated, the system running quality is optimized, and meanwhile, the running economy of the concentrated hybrid energy storage system is improved.

The invention relates to a distribution network flexible load cooperative dispatching method based on a particle swarm algorithm, belonging to the technical field of grid operation and control. The method comprises the following steps of: (1) considering stabilizing new energy access, peak clipping and valley filling and safe and economical operation of distribution network, establishing an optimization objective of flexible load cooperative dispatching model of distribution network; 2, synthetically considering the system balance constraint, the network constraint, the distribution power source and the adjustable load constraint, wherein each constraint condition can flexibly carry out parameter configuration and effective setting, and establishing the constraint of the optimization objective in the step 1; and 3, finally, solving the optimization objective of the load cooperative dispatch model satisfying the constraint condition by using the particle swarm optimization algorithm. This kind of cooperative control method provides space for alleviating the peak load regulation and realizing the large-scale consumption of new energy, and its economic benefits are enormous.

The invention discloses an intelligent power consumption management system facing a household wind and solar energy mutual-complementing power station and a management method thereof. The intelligent power consumption management system comprises an intelligent electric meter, a collector, a concentrator, a master station server, a short-message platform, a human-computer interaction terminal, a wind and solar power station, an intelligent control terminal, an intelligent socket, an intelligent switch, an intelligent home appliance, a temperature monitor, a humidity monitor and a smoke monitor, wherein an output terminal of the wind and solar power station is connected with the master station server via an RS485 interface; the intelligent electric meter is connected with the collector, the collector transmits intelligent electric meter information to the concentrator via the RS485 interface, and the concentrater is communicated with the master station server by using a network signal; the master station server transmits information to a user via the short-message platform, and the user performs a corresponding operation via the human-computer interaction terminal; the master station server controls the intelligent socket and the intelligent switch via the intelligent control terminal; and the temperature monitor, the humidity monitor and the smoke monitor communicate with the master station server via access points. According to the management system and management method, access and management of renewable energy can be achieved.

The invention relates to a light storage charging tower random optimization scheduling method considering peak load shifting of a power distribution network. The method comprises the following steps of: 1, establishing a tower day-ahead multi-objective optimization scheduling model by taking the minimum daily operation cost of the tower and the peak clipping and valley filling of the power distribution network as objectives; 2, evaluating the influence of peak load shifting by adopting the minimum variance of the curve of the electricity purchase quantity of each time period of the tower, andconverting multi-objective optimization into a single-objective optimization problem through an economic conversion coefficient; 3, considering the influence of the output uncertainty of the photovoltaic unit in the tower on day-ahead scheduling, describing by adopting a representative scene, and constructing a random optimization scheduling model by taking the tower day-ahead optimization scheduling and representative scene adjustment as the sum of first-stage decision and second-stage decision, day-ahead scheduling cost and real-time adjustment expected operation cost as targets; and 4, testing the actual light storage charging tower, and solving the model. According to the method, the probability optimal scheduling strategy under the scene that the light storage charging tower participates in peak load shifting of the power distribution network can be effectively obtained, economic, efficient and reliable operation of the tower is guaranteed, and peak load shifting of the regional power distribution network are achieved.

The invention provides an electric vehicle charging time sequence determining and service vehicle selecting method for participating in frequency modulation services. The method comprises inputting electrovalence information and vehicle information into a charging device; obtaining the required charging time according to initial electric quantity level, target electric quantity level and the maximum average charging rate of vehicles; obtaining vehicle parking time and possible charging time sequences of the vehicles according to turn-on time and departure time of the vehicles; calculating vehicle earnings under each charging time sequence according to a vehicle earning formula, and determining the time sequences for enabling the earnings to be maximum; determining charging time sequences after the vehicles respond to scheduling instructions; and enabling the charged vehicles to be evaluated at a charging place, and selecting service vehicles from small to large according to evaluation indexes. According to an embodiment, the vehicle charging benefit is effectively improved, the peak valley load difference of a power distribution network is reduced, and the frequency modulation service capacity is increased.

A sensitivity analysis based interaction cost calculation method for a microgrid and a power distribution grid comprises the following steps of: acquiring basic structure and parameter information of the microgrid participating in interaction; forecasting the output and the load power of a distributed power supply in a scheduling period, and acquiring time-sharing electricity cost information of the power distribution grid; considering the electricity purchasing cost of the microgrid in the scheduling period, the electricity sell gain and the power generation cost of the distributed power supply by taking minimum running cost of the microgrid as a target function, and building a microgrid running optimal scheduling model; setting a constraint condition of a microgrid optimal scheduling problem; solving a microgrid optimal scheduling mode formed by the target function and the constraint condition by using an optimization tool to obtain running cost corresponding to a scheduling plan; acquiring interactive time frame information of the power distribution grid; and respectively calculating positive interaction cost and negative interaction cost of the microgrid, and acquiring the relation between the interaction capacity and the interaction cost during the positive interaction of the microgrid through piecewise linearization. By the method, the interaction between the microgrid and the power distribution grid is achieved at the minimum cost.

The invention provides a power system source-load-storage coordinated rolling scheduling method based on flexibility margin, and relates to the field of power generation scheduling of power systems. The method comprises the following steps: firstly, determining an uncertain interval of wind power output and load, and establishing a flexible supply capacity model corresponding to each flexible resource; on the basis, respectively establishing a power system flexibility demand capacity model and a flexibility supply capacity model, and determining a flexibility margin index; then establishing asource load storage day-ahead coordination scheduling model and solving; and in each rolling period in the day, establishing and solving a source load storage intra-day rolling scheduling model of therolling period, and finally obtaining a scheduling result of each intra-day rolling period. Flexible resources such as a wind turbine generator, a thermal power generating unit, a gas-electric unit,a pumped storage unit and an interruptible load are taken into consideration, actual engineering can be effectively met through the scheduling plan formulated by the invention, and the operation economy and reliability of a power system are optimized.

The invention discloses a power distribution network optimization scheduling method based on an electric vehicle two-stage rolling strategy. According to the invention, modeling is carried out on thecharging demand of an electric vehicle, a real-time scheduling strategy of the electric vehicle is obtained through a grouping mechanism, the prediction value is updated in a two-stage rolling mannerby utilizing the latest power prediction information on the basis of day-ahead scheduling, the charging strategy of each sub-group of the electric vehicle is formulated, and the real-time scheduling of the electric vehicle is carried out through the charging and discharging priority. According to the two-stage rolling type strategy adjustment real-time charging optimization method, the model solving difficulty can be remarkably reduced and the model solving speed can be improved. The method can be applied to reasonable and feasible scheduling of an actual power grid, enables the scheduling ofthe electric vehicle to truly participate in the actual scheduling of the power grid, achieves the peak load shifting, and improves the permeability of renewable energy in the power grid.

The invention is applicable to the technical field of power network dispatching, and provides an UHV receiving-end power network peak load regulation control method, comprising the following steps: obtaining the UHV receiving-end power network in-network unified load regulation; If the load in the network is in the output range of the adjustable unit, the output level of the adjustable unit in thenetwork will be adjusted. If the load in the network is not in the output range of the adjustable unit, the power of the storage power station will be regulated. If the power of the storage power station can not meet the peak load regulation condition of the first power network, the transmission power of the UHV transmission channel is regulated. If the transmission variation of the UHV transmission channel can not meet the peak load regulation condition of the second power network, the charging and discharging power of the energy storage device is regulated. If the charging and discharging power of the energy storage device cannot meet the peak load regulation condition of the third power network, the load power of the terminal on the user side is adjusted so that the load power of the terminal on the user side meets the peak load regulation condition of the fourth power network. The invention can realize the peak clipping and valley filling of the power network, and ensure the safeand stable operation of the power network and the reliable power supply.

The invention discloses an adaptive micro grid energy storage system energy optimization management method. The method comprises the following steps: A, more energy for peak regulation than that in the former day by a battery in the micro grid energy storage system is determined; B, according to a ratio of the more energy for peak regulation than that in the former day by the battery to a lower limit of a battery energy storage capacity, a battery discharge threshold in the micro grid energy storage system is adjusted, when the ratio is larger than 1, the discharge threshold is reduced, and if the ratio is smaller than 1, the discharge threshold is increased. By using the adaptive micro grid energy storage system energy optimization management method of the invention, influences from real-time load fluctuation do not exist, local utilization of new energy can be realized maximally, and a large amount of excessive power can be prevented from flowing in a large grid.

The invention provides a molten salt electrode boiler heat storage and power generation system, and belongs to the field of energy storage. The system involves a heating part, a high-temperature molten salt storage tank and a heat utilization part; the heating part comprises a boiler body, a high-voltage electrode, a neutral electrode and a low-temperature molten salt supply head, wherein the high-voltage electrode, the neutral electrode and the low-temperature molten salt supply head are arranged in the boiler body, the high-voltage electrode is used for being connected with a power generation system, and the low-temperature molten salt supply head is used for filling the boiler body with low-temperature molten salt; one end of the high-temperature molten salt storage tank is connected with the bottom of the boiler body, and the other end of the high-temperature molten salt storage tank is connected with the heat utilization part; and the heat utilization part is used for carrying outheat exchange on the molten salt sent out by the high-temperature molten salt storage tank and a water working medium for pushing the steam turbine to act, and sending the cooled molten salt back tothe boiler body. Wind power photovoltaic curtailed electricity is used for heating the molten salt and storing heat in the off-peak period of electricity utilization, and high-temperature molten saltis used for heating feed water to generate high-temperature and high-pressure steam in the peak period of electricity utilization, so that the steam turbine is pushed to act, he stored heat is converted into electric energy to be output, and the curtailed wind and light can be effectively consumed to realize large-scale storage and scheduling of non-water renewable energy power.

The invention discloses a multi-scale direct load control method of an electric water heater group. The method comprises the following steps: generating single electric heater daily water data according to a family daily load curve, and setting multi-scale according to an electric power system daily load curve; and aggregating the electric water heater to form multiple water electric heater groups; and performing a quantum evolutionary algorithm on each scale of the water heater group to obtain an optimal control strategy. Through the adoption of the method disclosed by the invention, the peak-clipping and valley-filling can be effectively performed, and the method has important significance for the stability and the economy of the electrical power system.

The invention relates to a wind power dissipation scheduling method of cogeneration system based on electricity price-load linkage response. According to the method, a real-time electricity price mechanism is introduced, a new real-time electricity price is generated according to load change, the new real-time electricity price guides a power user to respond, load and real-time electricity price linkage response is achieved so as to guide the market behaviors among the main bodies of the power market and transfer the load across time periods. An electric boiler is installed in a heat load center so as to decouple the restraint of determining the electricity by heat, thereby reducing the heat energy loss in the transmission process. In the process of target optimization, the optimal coordination control of the daily load integral dynamic transfer across time periods and the thermal electrolytic coupling is achieved, so that the difference between the network cost and the auxiliary service cost of the abandoned wind is absorbed to the greatest extent, the wind energy is absorbed to the greatest extent, and meanwhile, the load peak-valley difference is reduced.

The invention discloses an adaptive dynamic programming method for multi-goal joint optimized dispatching. The method is characterized in that afterheat in a gas discharged from gas turbines is stored, a power grid dispatching model of a compound system is established through the mechanism analysis method, and a multi-goal function is created according to the minimum power generation cost and theminimum environmental cost; and the principle and goals of adaptive dynamic programming are finally provided to represent a process in which the optimum optimized dispatching scheme is obtained through the heuristic adaptive dynamic programming algorithm. The method disclosed by the invention has the advantages that impacts of the wind and photovoltaic power outputting randomness, intermittence and volatility and low predication precision on stable operation and active balance of a power system can be greatly reduced, the possibility of wind or photovoltaic power curtailments can be lessened,integrated wind-photovoltaic-storage-gas outputting can be smoothened, peak-load shifting can be achieved, the system operation cost and the discharge control cost of a power generation system can begreatly lowered, and the system operation benefits can be improved, so that safe, stable and economical operation of the power system can be guaranteed.

The invention relates to a two-stage source load storage optimization scheduling method for wind power consumption. The method comprises the steps: correcting day-ahead scheduling through intra-day scheduling for the uncertainty of wind power output; dividing load side responses, and carrying out enthusiasm of the load responses through price measures; establishing an electric and thermal load time-sharing response model, an excitation type load response model and a heating load model, and respectively calling in day-ahead and intra-day time periods; establishing source load storage optimal scheduling models under different conditions, wherein day-ahead scheduling takes minimum economic cost as a target, and intra-day scheduling takes minimum wind curtailment as a target to perform optimalscheduling; and finally, solving the optimization scheduling model by using an optimization particle swarm algorithm to prevent the algorithm from falling into global optimum or local optimum. According to the method, the source load storage side resources can be fully called to flexibly cope with the wind power output, the wind power is fully consumed, the model is conveniently, rapidly and accurately solved, and a flexible and economic source load storage optimal scheduling result for wind power consumption is obtained.

The invention discloses a coordination optimization method of wind power merchant and electric vehicle substation based on master-slave game, comprising the following steps: (1) signing a cooperationagreement between wind power merchant and electric vehicle substation; (2) after the wind power merchant obtains the on-grid electricity price of the next day from the distribution network operator, taking the charge and discharge price of the electric vehicle substation of the next day as a decision variable, constructing a price optimization model of the wind power merchant; (3) after obtainingthe charge/discharge price of the next day, taking the charge/discharge power of the next day as a decision variable to construct a charge/discharge power decision model of the electric vehicle substation; 4, modeling the optimization process of wind power merchant and the electric vehicle substation as the decision makers with different positions for the dynamic game for as the master-slave gamemodel. By using the coordinated optimization method proposed by the invention, the anti-peak regulation characteristic of the wind power is weakened, and the profits of the wind power merchant and theelectric vehicle substation are increased.

The invention discloses a wind-hydrogen coupling power generation system and a control method thereof. A wind generating set, an alkaline electrolytic cell, a fuel cell and a super capacitor are respectively coupled to a direct current bus through bidirectional DC/DC, and the direct current bus is connected to a power grid through a DC/AC inverter; the wind generating set converts wind energy intoelectric energy and transmits the electric energy to the direct-current bus in real time, and if wind power output is greater than the load requirement, the remaining electric energy is transmitted to the electrolytic cell to electrolyze water, and generated hydrogen is stored in a hydrogen storage tank; and if the wind power output is less than the load demand, the fuel cell takes hydrogen as fuel to generate electric energy and transmits the electric energy to the direct-current bus. The electrolytic cell and the fuel cell are used as energy type units, and the super capacitor is adopted tostabilize fluctuation caused by delay response of the electrolytic cell and the fuel cell in the system.

The invention discloses a comprehensive energy demand response quantity calculation method, which comprises the following steps of: (1) constructing energy consumption models of various loads according to operation characteristics of the loads used by a user; (2) establishing a comprehensive energy demand response quantification model; and (3) solving the quantization model in the step (2) by using a mixed integer optimization algorithm. According to the invention, accurate calculation of the comprehensive energy demand response capacity can be realized, the system optimization scheduling level and accurate management of user loads are improved, the power utilization mode is dynamically changed, the power utilization economy and the load flexible adjustment capability are improved, and a foundation is laid for further realizing peak clipping and valley filling of the system power utilization loads and reducing the foundation construction cost.

The invention relates to a natural gas heat and cold electric energy supply device based on fused salt heat storage. At present, no natural gas heat and cold electric energy supply device which is simple in structure and reasonable in design and can further improve the comprehensive utilization of energy and the energy supply stability exists. The natural gas heat and cold electric energy supply device comprises a fuel gas electric generator, a waste-heat utilization device, a gas-gas heat exchanger and a fan, wherein the fuel gas electric generator is connected with the waste-heat utilization device through a pipeline; the waste-heat utilization device is connected with the gas-gas heat exchanger through a pipeline; and the fan is connected with the gas-gas heat exchanger through a pipeline. The device is characterized by further comprising a fused salt phase change heat storage device, and the fused salt phase change heat storage device is connected to the fuel gas electric generator, the waste-heat utilization device and the gas-gas heat exchanger through pipelines respectively. The natural gas heat and cold electric energy supply device is reasonable in structural design and can further improve the comprehensive utilization rate of the energy and the energy supply stability.

A photovoltaic grid-connected generation power balancing control method is disclosed which includes three parts: maximum power tracking, grid-connected inversion and an energy storage system. The method, based on the maximum power tracking and grid-connected inversion control of photovoltaic power generation, introduces a battery energy storage system to realize a peak-shaving load-shifting and balancing function for generation power. The photovoltaic grid-connected power generation system solves photovoltaic power fluctuation. The system not only achieves the maximum power tracking and grid-connected power generation, but also stabilizes the grid-connected power through the power balancing control. When a power grid is faulted and disconnected, a photovoltaic array can still generate power, stores the power in the battery, and improves system efficiency.