39results about How to "Smooth load fluctuation" patented technology

The invention discloses an electricity-gas interconnected comprehensive energy system peak clipping and valley filling method based on electricity-to-gas conversion. The method comprises the steps of firstly respectively establishing a power network model, a natural gas network model, an electricity-to-gas conversion model and a gas turbine model, wherein the power network and the natural gas network are coupled to form an electricity-gas interconnected comprehensive energy system via the electricity-to-gas conversion model and the gas turbine model; then introducing an economic conversion coefficient to project a net load peak clipping and valley filling target to an economic dimension, and forming a target with the lowest comprehensive cost together with the target with the lowest system operation cost, and establishing an electricity-gas interconnected comprehensive energy system peak clipping and valley filling model with consideration on various constraints of the power network and the natural gas network; and solving by using optimization software The General Algebraic Modeling System (GAMS), wherein an example analysis result shows that the model provided by the invention has good peak clipping and valley filling effect.

The present invention provides a multi-population genetic particle swarm optimization method containing the micro-grid capacity configuration of electric automobiles. The method realizes the energy storage function of an electric automobile on the premise that the electricity demand of the electric automobile can be met. According to the technical scheme of the invention, a multi-target model, with the annual cost, the annual loss of load probability and the peak-valley difference of a load curve as targets, is proposed. Based on the multi-population genetic particle swarm algorithm, a target function is solved out. In this way, the optimal capacity of each unit in a micro-grid system can be obtained precisely. On the premise that the system reliability is ensured and the load fluctuation is stabilized and inhibited, a higher economic benefit is obtained. Through optimizing the micro-grid system containing the electric automobile, the mobile energy-storage device of the electric automobile is utilized to realize the peak-load shifting purpose on the basis that the reliability and the economy of the system are guaranteed. Meanwhile, the peak-valley difference of the system curve is reduced. Not only is the stability of the power system improved, but also the economic benefit is higher. Therefore, the popularization and the utilization of a cleaning device of the electric automobile are facilitated.

The invention relates to an orderly charging system and method for an electric taxi charging station, and belongs to the field of intelligent power grid control. The system is composed of a battery management system, a batter charger, a charging point, an SCADA (supervisor control and data acquisition) system/a PQ (performance quality) monitoring system, an orderly charging control center and a batter charging information database. According to the background load of a to-be-predicted power grid and the demand on the charging power of an electric taxi, the optimal charging start time and the optimal charging phase plan are formulated for each electric taxi, and the electric power of the power grid at a valley period is fully utilized for charging a power battery of the electric taxi, so that the load of a superior transformer substation can be adjusted, the difference between the peak and the valley can be relieved, the load fluctuation of the power grid can be restrained, and the economy and the efficiency of the power grid are improved. Meanwhile, according to the single phase charging manner of the taxi, the optimal charging phase can be selected via the system, so the unbalance of the three-phase load can be reduced.

The invention discloses an ultra-short-term power load forecasting and early warning method based on a Kalman filter and wavelet echo state network. In order to solve the problem that noise and the like are contained in power load data, a Kalman filtering method is adopted to conduct real-time estimating on 'collected data', with the help of a forgetting factor, the weight of old-fashioned data is weakened, and prediction accuracy is improved. Before ultra-short-term load forecasting is conducted, firstly, a principal component is used for analyzing and determining main working procedures for influencing the change of a power load, the main working procedures are used as the input of a power load capacity prediction model, afterwards, wavelets are used for decomposing the loads of different spectral characteristics (high frequency, follow-up and stability) of the power load, echo state network singe power loads are respectively established for predicting and modeling, various forecasting components are integrated to obtain a total load variation trend, and ultimately an early warning test is conducted on the prediction model specified by a user.

The invention discloses a double-layer bidding optimization method for a pumped storage unit in a day-ahead electric power spot market. The method comprises the steps of firstly randomly generating Wgroups of new quoted prices in a quoted price range; then calling a gurobi optimizer to solve the market clearing model, and optimizing related parameters of the pumped storage unit under the target of minimum total power generation cost of the whole system; and with the goal of obtaining the maximum income of the pumped storage unit in the electric power spot market, optimizing the iterative process through a genetic algorithm until the optimal quotation and capacity optimization result of the pumped storage unit is output. According to the method, reasonable arrangement of the capacity of the pumped storage unit and optimization of resource allocation can be realized, and meanwhile, higher income is obtained, so that the competitiveness of the pumped storage power station in the market is improved.

The invention discloses a charging and discharging automatic demand response optimization method for an electric car, and the method comprises the following steps: S1, obtaining the state information of the electric car connected in a power distribution network; S2, constructing an SDCO-ADR optimization configuration; S3, obtaining an initial charging and discharging plan (shown in the description), which can bring the biggest benefit to a user, based on the demand side optimization of PSDR; S4, obtaining an optimal charging and discharging plan (shown in the description), which enables the load fluctuation variance of the power distribution network to be minimum, based on supply side optimization of IBDR; S5, constructing an SDCO-ADR optimization configuration, and building a CVaR model of a client response intention decision. The method automatically carries out fine resource configuration according to the demand signal of a power company side and the condition of a user side, achieves the coordinative optimization of the supply and demand sides, and irons out the defects that manual response is low in efficiency, poor in reliability, strong in nondeterminacy and easy to cause response fatigue.

The invention relates to an electric vehicle charging load random connecting control system and method of charging pile self-decision, and belongs to the field of electric vehicle intelligent charging. The system comprises a control decision generator and a plurality of intelligent charging piles. The control decision generator obtains the electricity price and load information of a current control area, calculates the probability distribution of corresponding charging start moments of users of different charging time durations according to a load curve by means of the designed random connecting method, and issues control instructions to all the intelligent charging piles, and the charging piles determine the final charging start time according to the probabilities of the connecting users.The method has a good peak-load shifting effect, can restrain the power grid load fluctuation and reduce the charging cost of the users of electric vehicles; the whole control process is independently completed by the device in the control area, concentrated type communication and control are not needed, implementation is simple and convenient, and the system is low in cost and suitable for orderly charging of residential areas with large-scale private electric vehicles.

The invention discloses an active power distribution network multi-level redundant coordinated control method considering an electric vehicle and energy storage and belongs to the new energy coordinated control technological field. The method is characterized by including the following steps that: 1, the operation data of an active distribution network are obtained; 2, the load characteristic model of the electric vehicle is established; 3, the energy storage and release characteristic model of the energy storage is established; 4, the multi-level redundant coordinated control strategy of theactive distribution network containing the electric vehicle and energy storage is constructed; and 5, the multi-level redundant coordinated control of a daily scheduling model, a hourly scheduling model and a real-time scheduling model is solved. According to the method of the invention, starting from the active distribution network, the active power distribution network multi-level redundant coordinated control method considering the electric vehicle and energy storage is researched on the basis of the idea of redundant interval division, and a promotion foundation and technical support can be provided for the further development of new energy sources such as electric vehicles.

The invention belongs to the field of steam explosion and relates to a gas explosion processor. The gas explosion processor comprises a frame (1), an outer cylinder body (2), an inner cylinder body (3), a steam pipe (4), a lower sealing end cover (5), an upper sealing end cover (6), a material receiving bin (7), a material receiving bin support plate (8) and a feeding bin (9). The gas explosion processor is characterized by further comprising a support airbag (10), an airbag fixing plate (11), a synchronous cylinder body (12), a synchronous cylinder piston (13), a pulse cylinder body (14), a pulse cylinder piston (15), a pulse cylinder piston connecting plate (16), a guiding rod (17), an elastic sealing component (18) and a control mechanism. According to the invention, the airbag support is adopted for promoting the sealing effect; the opening force of the lower sealing end cover is increased in the manner of double cylinder stacking; the lower sealing end cover can be opened within a shorter period of time; the materials in the storage tank can be instantly exploded within 60-75 milliseconds; the steam explosion effect and efficiency are greatly promoted; the structure is compact; the gas explosion processor is suitable for popularization.

The invention relates to an electric automobile charging power regulating method and system. The method includes firstly determining scheduling plan power of electric automobile charging power, and then solving actual charging power of various electric automobiles under demand response management according to the scheduling plan power, wherein the scheduling plan power is related to electric load,the higher the electric load is, the lower the scheduling plan power is, the actual charging power is positively correlated to the scheduling plan power, the lower the scheduling plan power is, the lower the actual charging power of the electric automobile is. The charging power is regulated, particularly the charging power of the electric automobile is reduced at the electricity utilization peak, and the charging power of the electric automobile is not limited in the valley of electricity utilization. The system can achieve orderly guide and real-time power control in charging of the electric automobile, reduces charging load to a certain degree at the electricity utilization peak on the basis of the full use of the existing distribution network resources, realizes peak shaving of the power grid, stabilizes the difference between the peak and the valley of the power grid, reduces load fluctuation of the power grid, and improve stability of the power grid.

The invention relates to a cooperative interaction method and system for an electric vehicle charging station and a photovoltaic power station. The method comprises the following steps: acquiring nodepower information of each photovoltaic power station, a user power utilization terminal and an electric vehicle accessed to the electric vehicle charging station in an area; establishing an electricvehicle-photovoltaic power generation collaborative interaction dynamic planning model according to the acquired information, wherein the electric vehicle-photovoltaic power generation collaborative interaction dynamic planning model comprises an objective function for realizing minimum energy system load variance in the region and a corresponding constraint condition; solving the electric vehicle-photovoltaic power generation collaborative interaction dynamic planning model through a particle swarm optimization algorithm based on hybridization; and formulating an energy collaborative interaction strategy in the regional energy system according to the obtained optimal solution. Compared with the prior art, energy cooperative interaction between the photovoltaic power station and the electric vehicle charging station is achieved, stable operation of a regional energy system is ensured, and meanwhile environmental protection benefits are considered.

The invention provides a method and a system for controlling virtual inertia of a mobile energy storage system. According to the method and the system, a DC virtual inertia is added in the DC side control of the mobile energy storage system, the control of a virtual synchronous machine is added to the AC control of the mobile energy storage system and inertia and damping are added to the DC side mobile energy storage system so as to better stabilize the DC side fluctuation. The fluctuation includes random fluctuation of the distributed power source and load fluctuation generated by the DC loadand the virtual synchronous machine so that plug-and-play of the DC side load is realized and stable voltage support is provided for the DC side small inertia system. Meanwhile, inertia and damping are provided for the AC side through the virtual synchronous machine control method so that the AC side load fluctuation is stabilized and the power quality of the power supply area of the mobile energy storage system is improved.

The invention discloses an urban distributed source network load storage scheduling optimization method based on an LSTM (Long Short Term Memory) algorithm in the field of load regulation. The method comprises the following steps: 1, acquiring historical load data of a medium-voltage line through a power system; 2, an available historical load data sequence is cleaned and reserved, and a line load prediction model is established based on an LSTM algorithm; 3, inputting the real-time load of the line at the current moment into the line load prediction model, and performing real-time prediction to obtain a line load value at the next moment; step 4, obtaining an adjustable load interval of the charging station corresponding to the current line; 5, according to the line load value obtained through prediction in the step 3, the optimal load adjustment method of the charging station in the adjustable load interval at the next moment is obtained based on the particle swarm optimization; and 6, the charging station executes the load adjustment method in the step 5, and the steps 3-6 are repeated. According to the invention, the operation efficiency of the distribution network line after large-scale access of various distributed source network load storage can be effectively improved, the network loss is reduced, and the load fluctuation is stabilized.

The invention relates to a comprehensive energy utilization system for desert and an operation method thereof. The comprehensive energy utilization system comprises a wind driven generator, a solar photovoltaic module, a solar heat collector, a heat storage tank, a fermentation tank, a gas storage tank, a biogas generator, a lithium bromide unit, a storage battery energy storage device, a fresh water preparation device, a fresh water reservoir, a psammophyte plantation, a desert animal breeding garden, a water pump and a bitter alkaline water tank. According to the invention, the renewable energy sources of solar energy and wind energy enriched in the desert area are fully utilized, and the generated clean electric energy meets the power consumption of the area. The storage battery energy storage device stores generated surplus electric energy when wind and light resources are rich, the gas storage tank is used for the biogas power generation system, the waste heat utilization system conducts gradient utilization on waste heat of a biogas power generator, and the solar heat collector and the heat storage tank supply energy to the system to achieve multiple guarantees of heat sources.

The invention discloses a microgrid new energy hybrid energy storage system. The system comprises a new energy power generation subsystem, an energy storage subsystem, an energy conversion subsystem and a power distribution subsystem, wherein the new energy power generation subsystem comprises tie lines connected with each power supply loop. The system also comprises a disturbance detection moduleand a reactive power compensation module. The power output end of the new energy power generation subsystem is connected with the input ends of the tie lines through the disturbance detection module;front-end network nodes are arranged at the output ends of the tie lines; middle-end network nodes are arranged at the input end and the output end of the reactive compensation module respectively. The energy storage subsystem comprises capacitors with a number equal to the number of the power supply loops, wherein each capacitor is connected with a switching device, each switching device is provided with a rear-end network node, and the new energy power generation subsystem selects a corresponding reactive power compensation module to establish connection with the energy storage subsystem based on a detection result of the disturbance detection module. According to the system, power generation and load fluctuation can be stabilized on the basis of low cost, and the stable operation of amicrogrid is kept.

The invention discloses heat supply systems and a heat supply method based on coupling phase change, and belongs to the field of civil heat supply. The heat supply systems comprise the civil heat supply system and the solar heating system. The heat supply systems comprise a first water circulation loop composed of a heat source, a thermal station and a heat user which are connected in sequence, the heat storage device comprises a box body, a partition plate is arranged in the middle of the box body and divides the interior of the box body into a first heat preservation area and a second heat preservation area, and the first heat preservation area and the second heat preservation area are each provided with an inlet end and an outlet end; The two ends of the first heat preservation area areconnected with a heating station and a heat source correspondingly. The two ends of the second heat preservation area are connected with the heating station and the heat source correspondingly. and the first heat preservation area, the heater and the second heat preservation area form a second water circulation loop. The high temperature of the second heat preservation area is kept through the second water circulation loop, and therefore it is guaranteed that water entering the thermal station is within the high temperature range. Phase-change heat storage and a solar heating system are combined, the characteristics of intermittency and instability of solar energy can be stabilized, the phase-change material can reach a phase-change area more quickly, and energy consumption is reduced.

The invention provides a park-type comprehensive energy system optimization operation strategy and load characteristic modeling method, and the method comprises the steps: building a system income model of each time section according to the electricity selling income of a park-type comprehensive energy system and the total cost of power generation and by taking the maximum operation benefit as anobjective function; establishing constraint conditions of the park-type comprehensive energy system; and under the constraint conditions of the park-type comprehensive energy system, with the maximumoperation benefit of the park-type comprehensive energy system being taken as the objective function, making a power output strategy of the park-type comprehensive energy system. According to the invention, multiple market factors such as time-of-use electricity price, energy storage and charging and discharging cost and photovoltaic on-grid benchmarking electricity price are comprehensively considered, the maximum operation income of the commercial park comprehensive energy system is taken as a target, the market factors and operation economy are comprehensively considered, a grid-connected load characteristic modeling method is proposed, multiple optimized operation strategies are obtained, and investment and return appreciation of the park-type comprehensive energy system can be realized.

The invention discloses a two-stage full-cycle rolling scheduling method, and belongs to the field of power system automation. Comprising the following steps: step 1, establishing a day-ahead scheduling model, and executing day-ahead scheduling calculation; step 2, calculating each segment parameter of the intra-day scheduling model; and step 3, establishing an intra-day scheduling model, and performing intra-day scheduling calculation according to calculation results of the step 1 and the step 2. According to the method, a rolling scheduling method is adopted, a day-ahead scheduling result and an intra-day scheduling result are updated according to recent prediction results of loads and renewable energy sources, the scheduling accuracy and the calculation efficiency are improved by setting the length of a scheduling range, optimal configuration solution is carried out on different types of resources in all stages, and social welfare optimization is achieved.