141results about How to "Improve absorption capacity" patented technology

The invention provides a multi-power-supply cooperative frequency modulation control method, and relates to the field of power grid dispatching, and the method comprises the steps: obtaining the real-time operation data of a power grid, the real-time operation data of the power grid comprises system frequency deviation, load prediction information, and the real-time output and adjustment capability data of multiple power supplies such as wind power, photovoltaic, hydroelectric and thermal power; according to the real-time operation data of the power grid, through a mixed integer linear programming algorithm, taking power generation cost minimization as a target function, and taking multi-power output upper and lower limits, a climbing rate, a system frequency deviation limit value and the like as constraint conditions, calculating an optimal output distribution scheme of multiple power supplies; and converting the optimal output distribution scheme into a power supply output adjustment instruction. Cooperative frequency modulation of multiple power supplies is realized, the system frequency stability and economical efficiency are improved, the renewable energy source grid connection and consumption capability is enhanced, and an effective solution is provided for large-scale new energy source access to a power grid.

The invention relates to the technical field of smart power grids, and discloses a distributed renewable energy source and energy storage cooperative scheduling system of Internet of Things data, comprising a data acquisition and monitoring module used for acquiring the running states of distributed energy sources and energy storage units through the Internet of Things technology; the energy supply and demand prediction module is used for predicting energy supply and load demand according to historical data, real-time data and meteorological information and generating basic data of a scheduling strategy; the collaborative scheduling strategy module formulates a collaborative scheduling scheme of the renewable energy and the energy storage unit based on energy supply and demand prediction, and adjusts the charging and discharging time of the energy storage unit; the double-layer optimization decision module is responsible for long-period energy storage planning and short-period real-time scheduling optimization; and the real-time monitoring and feedback module dynamically adjusts a scheduling strategy based on feedback data. According to the invention, through real-time monitoring, supply and demand prediction and cooperative scheduling of renewable energy sources and energy storage equipment, the system can optimize distribution and use of energy to the greatest extent, and energy waste is reduced.

The invention belongs to the technical field of distributed resource control of a power distribution network, and particularly relates to a distributed resource cooperative control method based on layering and partitioning autonomy of the power distribution network. The method comprises the following steps: S100, proposing an active power grid layering and zoning control strategy oriented to feeder autonomy; s200, establishing a power distribution network area power regulation and control information model of hierarchical and distributed control; and S300, realizing distributed resource cooperative control based on layering and partitioning autonomy of the power distribution network. According to the distributed resource cooperative control method provided by the invention, the distributed photovoltaic, user load and distributed energy storage coordinated control in the transformer area is realized by combining a feeder-autonomous-oriented active power distribution network layered and partitioned control strategy and utilizing the edge computing capability of the transformer area intelligent fusion terminal, the distributed photovoltaic absorption capability is improved, and the distributed resource utilization rate is improved. Energy supply and demand imbalance caused by distributed photovoltaic randomness is stabilized, and the economic operation level of a power distribution area is improved.

The invention discloses a reconfiguration-based operation optimization method for a power distribution system containing a reconfigurable soft switch. The method comprises the following steps of: 1, constructing a self-energy-storage type reconfigurable intelligent soft switch topology based on asymmetric voltage source converter capacity and feeder line selection; 2, modeling is carried out on the self-energy-storage recombined intelligent soft switch; and 3, modeling the reconfiguration-based flexible power distribution system containing the reconfigurable soft switch, and obtaining an optimal operation strategy of the power distribution system by solving the optimization operation model. According to the invention, the multi-element controllable equipment of the power distribution system can be reasonably utilized to improve the utilization rate of the traditional multi-terminal intelligent soft switch to the capacity of the voltage source converter, and the maximum transmission power of the traditional multi-terminal intelligent soft switch can be improved, so that the operation loss of the power distribution system can be reduced, and the new energy consumption can be improved.

The invention discloses a multi-type power supply cooperative scheduling operation method and device, a medium and a product, and relates to the field of new energy. The method comprises the following steps: firstly, establishing a power supply side output fluctuation minimum objective function O1, a new energy abandoned energy cost minimum objective function O2 and constraint conditions thereof, wherein the constraint conditions comprise constraint conditions of wind power generation, photovoltaic power generation and an energy storage power station; adopting a multi-target grey wolf optimization algorithm to solve an optimal solution set of new energy and energy storage power station output as an optimal solution of a new energy optimization layer; establishing a minimum target function O3 of dispatching operation energy consumption of the thermal power generating unit and constraint conditions thereof by combining the coal fuel quantity of the thermal power generating unit and the start-stop operation energy consumption; solving an optimal solution set of the start-stop state, the output state and the operation energy consumption of the thermal power generating unit by adopting an improved quantum particle swarm algorithm to serve as an optimal solution of a thermal power generating unit optimization layer; cooperative scheduling operation of multiple types of power supplies is guided based on the optimal solutions of the new energy optimization layer and the thermal power generating unit optimization layer, and the stability, accuracy, flexibility and economical efficiency of cooperative scheduling can be improved.

The invention relates to the technical field of image recognition and processing, and discloses a main network energy storage power station planning system and method based on wind-solar space-time correlation, and the system comprises a data collection and preprocessing module which carries out the cleaning and preprocessing of a data collection and preprocessing module; the wind and light space-time characteristic analysis module is used for researching space-time distribution characteristics and reverse peak regulation characteristics of wind power and photovoltaic output and correlation between the space-time distribution characteristics and the reverse peak regulation characteristics; a modeling and simulation module; the scene generation and screening module is used for generating a typical daily operation scene; and the energy storage technology evaluation module is used for comprehensively evaluating the technical performance of different types of stored energy. According to the method, the spatial-temporal distribution characteristics, the reverse peak regulation characteristics and the correlation of wind power and photovoltaic output are deeply researched, the output spatial-temporal correlation model suitable for large-scale wind and light is constructed, the level of accepting and utilizing renewable energy sources by a power grid is greatly improved, and the effect of remarkably improving the absorption capacity of the power grid to the renewable energy sources is achieved.

The invention relates to a source network load storage collaborative planning method and system considering a multi-agent mixed game, and the method comprises the following steps: building a power distribution network collaborative planning model considering a source network load storage agent master-slave-cooperation mixed game, and enabling the power distribution network collaborative planning model to be a double-layer model, comprising an upper-layer master-slave game sub-model of a power distribution network operator and other subjects and a lower-layer cooperative game sub-model between a source load storage side subject; and solving the power distribution network collaborative planning model by adopting a solving strategy combining a target cascade analysis method and an adaptive coefficient alternating direction multiplier method to obtain an optimal planning scheme of a new line, a distributed power supply and an energy storage device. Compared with the prior art, the method has the advantages that efficient configuration and coordinated utilization of source network load storage resources can be realized, and the planning reliability is improved.

The invention discloses a novel distribution network multi-virtual power plant distributed resource aggregation and optimization operation method. The method comprises the following steps: 1, solving a virtual power plant feasible region based on a vertex enumeration method; 2, realizing multi-virtual power plant cooperative operation optimization based on a binary consistency algorithm; 3, based on the virtual power plant feasible region solving method based on the vertex enumeration method and the multi-virtual power plant cooperative operation optimization method based on the binary consistency algorithm, constructing a resource aggregation and aggregate optimization operation framework process; in the process, firstly, distributed resources are aggregated through a vertex enumeration method to obtain a virtual power plant feasible region; and carrying out collaborative operation optimization on the multiple virtual power plants by utilizing a binary consistency algorithm. By means of the method, efficient aggregation and optimized operation of distributed resources are achieved, the operation efficiency and economical efficiency of the power distribution network are improved, and the method has important economic and social benefits.

The invention discloses a wind-solar power generation and electric vehicle load cooperative control method based on user behaviors, and relates to the technical field of electric power system automation, and the method comprises the steps: obtaining historical power generation and real-time power generation data of a wind-solar power generation system according to an electric vehicle power load demand curve in a future time period, predicting a generating capacity curve of the wind-solar power generation system in the time period; performing matching analysis on the electric load demand curve of the electric vehicle and the wind-solar power generation curve to obtain a matching difference degree, and triggering cooperative control when the matching difference degree is greater than a preset threshold value; in the cooperative control, the generated power of the wind-solar power generation system and the actual power load of the electric vehicle are monitored in real time, the matching difference degree is calculated, and the generated power of the wind-solar power generation system is dynamically adjusted according to the change trend of the matching difference degree. The running cost of the electric vehicle is reduced, the utilization efficiency of wind and light power generation is improved, the energy utilization efficiency and the renewable energy permeability of the rail transit system are improved, and the purposes of energy conservation, emission reduction and green development are achieved.

The invention relates to a port energy station operation optimization method and system considering logistics whole link refinement, and the method comprises the following steps: determining typical energy equipment based on a typical structure of a port energy station under energy flow-logistics coupling, and constructing an energy equipment operation constraint; on the basis of the operation characteristics of port logistics activities, port logistics full-link operation characteristics and energy consumption characteristics are obtained, and logistics full-link operation constraints are constructed; based on constraint conditions including the energy equipment operation constraint and the logistics full-link operation constraint, establishing a port energy station operation simulation model considering the logistics full-link energy consumption time sequence adjustable characteristic; and effectively solving the port energy station operation simulation model to obtain a port energy station operation optimization scheme. Compared with the prior art, the method has the advantages that the operation cost of the port energy station can be effectively reduced, the clean energy consumption capability is improved, and the logistics load peak-valley difference is reduced.

The invention discloses a cloud energy storage operation mechanism based on thermal inertia of an urban building air conditioning system, which relates to the field of energy storage and comprises the following steps: (1) establishing a fixed-frequency air conditioner virtual energy storage monomer model and an aggregation model based on the thermal inertia of the urban building air conditioning system; (2) designing a cloud energy storage operation mechanism taking air conditioner aggregation virtual energy storage as a main leasing resource, and establishing a cloud energy storage operator model, a cloud energy storage user model and a transaction pricing strategy; and (3) solving the cloud energy storage operation model by taking the minimum power consumption cost of the user as a target, and distributing and evaluating the social total welfare brought by the cloud energy storage mechanism. According to the energy storage operation mechanism provided by the invention, the electricity consumption cost of the subscribing user can be effectively reduced, and the early-stage investment and the later-stage operation and maintenance cost of an operator are reduced; and under the dual-carbon background, the strategy is also beneficial to the real-time consumption of new energy on the user side.

The invention discloses a wind-light load multi-stage scene tree generation method based on source load uncertainty feature extraction, and the method comprises the steps: extracting wind-light load scene features based on a constructed stacked sparse auto-encoder model, and obtaining a wind-light load scene feature set; clustering the wind-light load scene feature set based on a density peak value improved affinity propagation algorithm to obtain a wind-light load typical day curve as a root node of the scene tree; generating a wind-light load scene tree year by year on the basis of considering different load growth modes according to root nodes of the scene tree; a scene tree is reduced through a scene tree reduction method based on the Sinkhorn distance, so that the scale of the scene tree is reduced. The wind and light load multi-stage scene tree generated by the method can reflect the time sequence information of the new energy output and load, characterize the randomness and volatility of the new energy output and load, can reflect the uncertainty of the long-term increase of the new energy output and load, and is of great significance to the planning and construction of a power grid.

The invention provides a hoisting type charging device and an automatic folding and unfolding method. The charging device comprises a charging gun; the charging pile is suspended on the ceiling or the cross beam, and the charging pile is provided with a charging cable; the wire coil comprises a first half wire coil and a second half wire coil which are oppositely buckled into a whole, and a wire twisting prevention structure is arranged at the butt joint position of the first half wire coil and the second half wire coil; one end of the charging cable is sequentially wound on the first half wire coil, penetrates through the anti-twisting wire structure, then is wound on the second half wire coil and then is connected with the charging gun; the two electric winches are suspended on a ceiling or a cross beam and are used for driving the wire coil to lift through a suspension rope so as to enable the charging cable to be wound and unwound in an anti-torsion manner; the radio sensor is arranged on any electric winch and used for sensing arrival or departure of the corresponding vehicle, and the radio sensor is in communication connection with the electric winches and used for controlling descending or ascending of the two electric winches; automatic lifting can be achieved based on parking of a vehicle, and a charging cable is effectively wound and unwound in an anti-torsion mode through the cable coil structure.

The invention relates to the technical field of energy storage power supply control, in particular to an energy storage power supply control method and system and an energy storage power supply, and the method comprises the steps: calculating the complexity of all power grid load data in each peak load interval and the average level difference of each power grid load data compared with all other power grid load data; determining the response capability of the energy storage power supply; determining charging correlation factors of the energy storage power supply by analyzing correlation of variation trends between all power grid load data and all charging electric quantity data in each valley load interval and extreme distribution conditions of all power grid load data, constructing control hysteresis of the energy storage power supply in each time period in combination with the response capability, and determining the energy storage power supply according to the control hysteresis of the energy storage power supply in each time period. And controlling the energy storage power supply after the current moment. The invention aims to improve the absorption capability of the energy storage power supply for new energy power resources and the response timeliness of the energy storage power supply.

The invention discloses a time sequence power grid planning method based on a new energy consumption rate, and particularly relates to the technical field of power grid planning. By collecting and analyzing new energy output fluctuation and load change data in different time periods in a power grid, a new energy and load fluctuation curve is constructed, the harmonic distortion severity degree is evaluated in combination with real-time data of harmonic monitoring equipment, the load influence and reactive power margin fluctuation of harmonic waves on a reactive power regulation device are identified, and the reactive power regulation device is optimized. The power quality risk is quantified based on the comprehensive analysis result, the time period is divided into high risk, medium risk and low risk levels, a power quality improvement scheme is formulated, and in the medium risk time period, the output quantity of a reactive power regulation device and the starting frequency of a harmonic filter are dynamically adjusted by predicting the voltage support risk, so that the power quality is improved. And the voltage stability of the power grid under the harmonic fluctuation condition is ensured, so that the power quality and the safety and stability of new energy consumption are remarkably improved.

The invention discloses a multi-resource collaborative new energy power system two-stage scheduling method and device, and the method comprises the steps: building a stage optimization scheduling model according to the uncertainty and intermittence characteristics of wind power; day-ahead scheduling stage constraints are set, and a power transmission network structure is optimized and a unit start-stop strategy is determined through a stage optimization scheduling model according to a day-ahead predicted value of a next-day load demand and renewable energy output; setting real-time scheduling stage constraints, and performing real-time PST adjustment on a voltage power angle and adjustment on unit output according to a next-day load and renewable energy output scene through a stage optimization scheduling model; and a solver is set to solve the stage optimization scheduling model, and an optimal scheduling strategy of a day-ahead scheduling stage and an optimal scheduling strategy of a real-time scheduling stage are obtained. According to the invention, the renewable energy consumption capability can be effectively improved, so that the overall economy of power grid operation is promoted.

The invention belongs to a new energy consumption method, provides a new energy consumption optimization method for a multi-type subject power system and a related device, and aims to solve the technical problems of resource waste and urgent need of consumption of new energy at present, and constructs an optimization clearing model based on multi-type subject participation. And acquiring a new energy 96-point prediction curve and a 96-point baseline load curve, solving the optimization clearing model in combination with the new energy 96-point prediction curve and the 96-point baseline load curve to obtain an optimization strategy, and optimizing the power system by adopting the optimization strategy. Multiple types of subjects are promoted to participate in the market through a market means so as to improve the absorption capacity of new energy and reduce the power abandoning rate of a new energy blocking area.

The invention relates to the technical field of power dispatching, in particular to a distributed robust chance constraint dispatching method and system for a multi-energy complementary power generation system, and the method comprises the steps: building a target function, taking the maximum new energy power generation power as a target, and comprehensively considering the output of a thermal power generating unit, a pumped storage unit, a wind power unit and a photovoltaic unit; establishing operation constraint conditions of the multi-energy complementary power generation system; the distributed robust chance constraint is introduced, the nonlinear constraint is subjected to linearization processing, the uncertainty of new energy output is represented, and a distributed robust chance constraint peak regulation scheduling model of the multi-energy complementary power generation system is constructed according to an objective function and constraint conditions; and solving the scheduling model by using a mixed integer linear programming method in combination with a solver, obtaining the optimal output distribution of each time period, and obtaining a scheduling method. According to the invention, the influence of the new energy output randomness and volatility on the peak regulation scheduling of the power system is effectively solved, and the new energy consumption capability and the operation stability of the multi-energy complementary power generation system are improved.

The invention provides a suspension type alternating current charging device and an automatic folding and unfolding method. The charging device comprises a charging gun; a power line extends from one end of the AC charging pile, and a charging line extends from the other end; the wire coil comprises a first half wire coil and a second half wire coil which are oppositely buckled into a whole, and a containing cavity is formed in the butt joint position of the two half wire coils; the alternating current charging pile is arranged in the accommodating cavity, and a power line guide groove and a charging line guide groove which are correspondingly communicated with the accommodating cavity are respectively formed in the butt joint part; the power line penetrates out along the power line guide groove to be wound on the first half wire coil, and the charging line penetrates out along the charging line guide groove to be wound on the second half wire coil to be connected with the charging gun. The electric winch is suspended on a ceiling or a cross beam and is used for driving the wire coil to lift through a traction rope so as to take up and pay off the charging wire in an anti-torsion manner; the radio sensor is used for sensing arrival or departure of a vehicle, and the radio sensor is in communication connection with the electric winch; the structure is simple and reliable, and automatic lifting based on vehicle parking can be achieved.

The invention discloses a receiving end power grid reactive power compensation equipment optimal configuration method considering power flow transfer. The method comprises the following steps: when high-voltage direct current or new energy power in a receiving-end power grid changes, calculating a power flow transfer factor of the receiving-end power grid; calculating a voltage weak node comprehensive evaluation index based on the power flow transfer factor of the receiving end power grid, and determining a voltage stability weak node set based on the comprehensive evaluation index; for the voltage stability weak node set, partitioning nodes in the voltage stability weak node set by calculating an electrical distance index, and respectively determining an alternative installation node set of the reactive compensation equipment for each node partition; through simulation, the sensitivity of weak node voltage to alternative nodes of the reactive power compensation device is calculated, and the installation place and capacity of the reactive power compensation device are determined based on the optimal particle swarm optimization.

The invention discloses a new energy consumption capability assessment method and device and a medium. The method comprises the steps of building a deep reinforcement learning model for new energy consumption capability evaluation; constructing a deep reinforcement learning framework based on a Lagrange flexible action evaluation algorithm; training the deep reinforcement learning model by adopting a deep reinforcement learning framework based on historical new energy output data and load data, and generating a new energy consumption capability evaluation agent; and performing consumption evaluation on the new energy output data and the load data of the to-be-evaluated scene by using the new energy consumption capability evaluation agent, and determining a new energy consumption capability evaluation result of the to-be-evaluated scene.

The invention discloses a multi-virtual power plant combined operation method and system considering shared hydrogen energy storage. An upper-layer optimization model taking the maximum operation net profit of a shared hydrogen energy storage operator as an optimization target and a lower-layer optimization model taking the minimum combined operation cost of each virtual power plant as an optimization target are established; actual values, fluctuation amplitudes and predicted values of the light and wind power generating capacity of each virtual power plant are obtained, and wind and light uncertainty constraint conditions are established; solving an upper-layer optimization model according to the state information to obtain an optimal solution of the operation net profit of the shared hydrogen energy storage operator, and solving a lower-layer optimization model to obtain a combined operation cost basic value of each virtual power plant under a wind-solar uncertainty constraint condition; with the maximum fluctuation amplitude sum of photovoltaic and wind power generation capacity as a risk objective function, introducing a risk avoidance deviation parameter to construct a first constraint, and introducing a benefit pursuit deviation parameter to construct a second constraint; and the optimal solution of the lower-layer optimization model meeting the first constraint and the second constraint realizes the optimal joint operation of the multiple virtual power plants.

The invention discloses a demand side flexible resource participation multi-objective optimization modeling method and a related device. The method comprises the following steps: determining initial data including wind power generation, thermal power generating units, electric vehicle disordered charging, distributed electric heating and user side energy storage; an objective function of the multi-objective optimization model is determined, boundary conditions of the multi-objective optimization model are designed according to the objective function and the basic data, and the multi-objective optimization model is constructed; designing a conventional thermal power adjustment scene and a typical demand side flexible resource adjustment scene based on the auxiliary service market; based on a conventional thermal power adjustment scene and a typical demand side flexible resource adjustment scene, the obtained initial data are utilized, an improved particle swarm optimization algorithm is adopted to solve a multi-target optimization model, and an optimization solving result is output. According to the method, the regulation capability of the power grid is optimized, the wind curtailment rate and the wind curtailment cost are effectively reduced, the absorption capability of new energy is improved, the problem of power curtailment caused by blockage of a delivery section is reduced, and the method has important significance in promoting sustainable development of the new energy.

The invention relates to a power system optimal configuration method for promoting rural renewable energy consumption. The method comprises the steps of S1, constructing a county new energy power generation resource potential evaluation model; s2, setting constraint conditions such as wind power, photovoltaic power, biomass power generation output, power system operation and energy storage configuration; s3, setting a power system optimization configuration objective function; s4, performing solution sorting on the model by adopting a sorting method approaching an ideal solution; according to the invention, key elements of the power system can be optimally configured, the renewable energy consumption capability is improved, and economic and environment-friendly operation of the power system is ensured; the method has the advantages that the output volatility is considered, key elements are optimally configured on the basis of time sequence production simulation, and the absorption capacity is improved.

The invention provides a low-voltage flexible interconnection regulation and control method and device for a power distribution network, and the method comprises the steps: obtaining the characteristics and parameters of regulation and control equipment of a power distribution system, and building various equipment models according to the characteristics and parameters, including an on-load voltage regulation transformer model, an electric vehicle charging and discharging model and a renewable energy model; obtaining seasonal load data and transformer use capacity data according to various equipment models; establishing a low-voltage flexible interconnection model of the power distribution network according to the seasonal load data and the transformer use capacity data; establishing a power distribution network low-voltage flexible interconnection regulation and control model oriented to new energy consumption and seasonal load supply based on various equipment models and the power distribution network low-voltage flexible interconnection model; and determining a new energy power distribution system interconnection regulation and control optimization strategy based on the power distribution network low-voltage flexible interconnection regulation and control model and the on-load voltage regulation transformer model. In this way, the new energy consumption capability can be improved while the seasonal load requirement of the new energy power distribution network can be met.

The invention relates to the technical field of power system frequency control, and particularly discloses a power optimization distribution control method based on a wind storage combined frequency modulation system, which comprises the following steps of: synchronously acquiring a power grid frequency modulation instruction, wind power output, an energy storage charge state and adjustable power capacity data; extracting wind power fluctuation frequency and amplitude characteristics and energy storage charge and discharge depth and response rate characteristics; by taking the features as state constraints, constructing a multi-objective optimization model taking the highest frequency modulation tracking precision and the minimum energy storage life loss as objectives, and solving the multi-objective optimization model to obtain a power optimal distribution coefficient; generating a wind power smoothing instruction and an energy storage amplitude limiting instruction according to the coefficient, and issuing and executing; collecting actual response data to calculate deviation, and dynamically correcting a weight coefficient and a constraint boundary of the optimization model; according to the invention, dynamic collaborative optimization of wind storage power is realized, and energy storage cycle loss and response deviation can be reduced.

This invention discloses a multi-agent game-theoretic collaborative planning method for airport integrated energy systems under physical-information-market coupling. The invention constructs a physical-market coupling model of the interaction between the integrated building energy system and the smart grid; defines independent decision-making entities such as the smart grid, multiple integrated building energy system operators, and renewable energy providers, and their multi-period objective functions; divides the planning period into multiple stages, establishing a dynamic game framework considering long-term investment and short-term operational coordination; uses subgame refined Nash equilibrium as the solution objective, and solves the inter-agent game strategies through mathematical programming and equilibrium constraints, and multi-agent reinforcement learning algorithms; generates multi-period equipment investment time-series diagrams for multi-agent collaboration and outputs typical daily scheduling schemes. The advantages of this invention are that it solves the problem of multi-agent interest conflicts and long-term / short-term decision coupling in airport integrated energy systems, reduces total system cost and carbon emissions, avoids redundant investment, and improves the renewable energy absorption capacity.

The embodiment of the invention provides a cooperative control system for a regional power grid. The regional power grid comprises a new energy electric field, a control center and n monitoring points. The cooperative control system provided by the embodiment of the invention is used for solving the problems of complex harmonic pollution, low efficiency of energy routing and other characteristics of the regional power transmission grid after the new energy is accessed to the power grid in a high proportion. The cooperative control system comprises a cooperative scheduling center and n cooperative scheduling groups in communication connection with the cooperative scheduling center, each monitoring point is connected to one cooperative scheduling group, the cooperative scheduling center is in communication connection with the control center, and each cooperative scheduling group comprises an energy router and a distributed power flow controller. The distributed power flow controller and the energy router are connected with the monitoring point. According to the cooperative control system provided by the embodiment of the invention, based on the cooperative control strategy of the energy router and the distributed power flow controller, harmonic waves in the power grid can be better treated, and the stability of the power grid is improved.

The invention belongs to the technical field of power system automation, and particularly relates to an adjustable load interaction capability key parameter confidence interval evaluation method. Comprising the steps of obtaining a system standby insufficient scene according to historical prediction data, forming a scene set, obtaining the maximum adjustable quantity of an adjustable load in a corresponding time period, and obtaining an adjustable load active response in the corresponding time period of the scene set according to historical operation data; calculating the actual maximum adjustable variable of the adjustable load, carrying out correlation analysis, generating a set taking the actual adjustable load value and the actual maximum adjustable variable of the adjustable load as elements, and grading the set into upper and lower standby difference scene grading sets according to the actual adjustable load value; clustering elements in the grading set to obtain a probability density function set of the actual maximum adjustable quantity of the adjustable load under different load levels; the confidence interval of the actual maximum adjustable quantity of the adjustable load under the given confidence is calculated, the contradiction between supply and demand is solved, peak clipping and valley filling are achieved, and the new energy consumption capacity is improved.

The present invention relates to the technical field of electric power dispatching, and discloses a collaborative dispatching method for source-load dual-side energy storage based on multi-agents. The method comprises: constructing an objective function and constraints for a source-load dual-side energy storage system based on a multi-agent; constructing a Markov decision model according to the objective function and constraints, and introducing an attention mechanism, solving the Markov decision model through the MAAN‑TD3 algorithm, obtaining the action space corresponding to the source-load dual-side energy storage system and executing it. The method can improve the utilization efficiency of energy storage, the new energy absorption capacity of the power supply side, and the system operation performance by collaboratively dispatching the load-source dual-side energy storage. On the other hand, the overall economic benefits can be improved on the basis of reducing the amount of abandoned wind.