14results about How to "Reduce curtailment" patented technology

The invention relates to the technical field of multi-objective optimization operation of a hybrid pumping and storage-containing water-wind-solar complementary system, and discloses a hybrid pumping and storage optimization scheduling method and system considering peak regulation and risk avoidance. The method comprises the following steps: acquiring historical data of a cascade basin water-wind-light power station and a power grid load, generating scheduling initial data through prediction, and generating scheduling scene data capable of representing the uncertainty of new energy based on the scheduling initial data and a prediction error; constructing an optimization model, solving the optimization model, and based on the solution of the optimization model, generating scheduling instructions of the drainage basin cascade hydropower station and the hybrid pumped storage power station; through the optimization model, the risk of power abandoning and load losing at the hydropower side is minimized, collaborative optimization meeting the peak regulation requirement of the power grid side is achieved, the flexible regulation advantage of hybrid pumping and storage is brought into full play, and stable operation and reliability of the system are promoted; and through linear processing, the solving speed and precision are improved, the real-time calculation efficiency of the system is ensured, and making of a scheduling decision is more efficient.

The invention relates to the technical field of energy planning, and particularly discloses a source-storage-transmission combined planning method considering carbon emission responsibility allocation, and the method comprises the steps: building a carbon emission responsibility double-layer allocation strategy; based on a carbon emission responsibility double-layer allocation strategy, establishing a source-storage-transmission combined planning model considering carbon emission responsibility allocation; and solving the source-storage-transmission combined planning model considering the carbon responsibility allocation to obtain a system source-storage-network optimal combined planning scheme. According to the method, carbon emission responsibilities are scientifically shared according to the principle of'who causes, who undertakes, who governs and who benefits', the effect of the carbon emission responsibilities in the planning process is effectively considered, an energy storage system is additionally arranged, the system flexibility is improved, and renewable energy consumption is promoted.

The invention discloses a wind and light storage cooperative control system based on source load matching. The system aligns a source load storage network and communication information and carries out credible evaluation; wind, light and load are predicted, and uncertainty levels are given; calculating a matching degree and a short plate hot spot, and combining network side hard constraints such as voltage, power flow and reverse transmission to obtain an acceptable boundary; when the matching is qualified and the complementary energy is still available, identifying the complementary energy / energy shortage and the reason, quickly checking the transferable margin and loss by the edge, generating a routing plan containing retention time and action budget, and scheduling the stored energy and the flexible load in a rolling manner; meanwhile, the risk budget and standby are written back according to feasibility, prediction uncertainty and communication quality, gray release and automatic rollback are achieved in cooperation with degradation and playback scoring, and consumption and traceability are improved.

The invention provides an operation control method and device of an electrolytic cell array. Based on the method, when it is monitored that the fluctuation amplitude of wind and light power generation data of a target wind and light power station is larger than a preset amplitude threshold value, the number of electrolytic cells to be scheduled at the current time in an electrolytic cell array can be determined firstly; constructing a multi-target cost function at least comprising an electrolytic cell operation and maintenance cost item, an electrolytic cell start-stop cost item and an energy storage battery system operation and maintenance cost item; meanwhile, according to the number of the electrolytic cells, a target constraint condition at least comprising a system overall power balance constraint condition is constructed; and on the basis of the target constraint condition and the multi-target cost function, a corresponding target scheduling strategy is obtained and utilized through optimization solution, and operation of the electrolytic cell array at the current time is controlled and adjusted. Therefore, the method can be well adapted to a large-scale fluctuation scene of wind and light power generation, and when the fluctuation of the wind and light power generation is large, the operation of the electrolytic cell array of the system can be timely and accurately adjusted.

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.

According to the wind-light storage coordinated configuration method based on the K-means and the simulated annealing genetic algorithm, the K-means algorithm is adopted to process initial data, then a wind-light storage configuration model is constructed, and finally the simulated annealing genetic algorithm is adopted to solve. According to the simulated annealing genetic algorithm, the advantage of strong local search capability of the simulated annealing algorithm and the advantage of strong global search capability of the genetic algorithm are combined, and the advantages can be mutually complemented, so that the precision and optimization speed of the algorithm are improved. By testing the wind and light energy storage configuration of a certain park, a good result is finally obtained, the investment cost is the lowest while wind and light curtailment is reduced, and an effective planning scheme is provided for the micro-grid.

The invention relates to the technical field of power system safety, and provides a power distribution system safety operation optimization method and system based on low inertia. The invention discloses a power distribution system safe operation optimization method based on low inertia. The method comprises the following steps: constructing an evaluation model based on a minimum inertia demand by taking minimization of the total operation cost of a system as an optimization target; under a set constraint condition, solving the evaluation model based on the minimum inertia demand by using a grey wolf algorithm to obtain a minimum inertia demand value at each moment; in the process of searching the minimum inertia demand value at each moment, the grey wolf algorithm adopts a convergence factor to determine a search area; the convergence factor is represented as the fractional order power of the ratio of the difference value of the maximum number of iterations and the current number of iterations to the maximum number of iterations. Response reliability of the system to sudden disturbance can be improved.

This application provides a method, apparatus, and electronic equipment for optimizing the distributed energy storage configuration in a new energy base. The method includes: determining a set of candidate distributed energy storage ratios for the new energy base to be configured with an energy storage system; acquiring operational data of the new energy base within a preset time period; constructing an energy storage configuration optimization model; for each candidate distributed energy storage ratio, solving the problem based on the operational data and the energy storage configuration optimization model to determine the total high-voltage side power supply and total operation and maintenance cost corresponding to that ratio; determining a target distributed energy storage ratio from the set of candidate distributed energy storage ratios based on the total high-voltage side power supply and total operation and maintenance cost corresponding to each candidate distributed energy storage ratio; and configuring energy storage in the new energy base based on the target distributed energy storage ratio. This application achieves a reasonable distributed energy storage configuration without changing the total planned energy storage capacity of the base, reducing dependence on high-voltage side power supply.

The present invention discloses a method for optimizing the adjustable load capacity of an electric power system based on the consumption of new energy, including obtaining the operating data of the electric power system to be analyzed; constructing an objective function with the goal of minimizing the adjustable load capacity under the premise that the amount of abandoned new energy meets the set requirements; constructing the constraint conditions of the objective function with the operating rules of the electric power system as constraints; using the linear interpolation method and the perturbation method to solve the objective function to obtain the final optimization result of the adjustable load capacity of the electric power system. The present invention takes the amount of abandoned new energy as a constraint condition, considers the operation strategy of the energy storage system dominated by time-of-use electricity prices, and solves the minimum value of the adjustable load capacity required for the system configuration; therefore, the method of the present invention not only improves the capacity of absorbing new energy and effectively reduces the amount of abandoned new energy, but also has high reliability, good accuracy, and is objective and scientific.

The invention discloses an off-grid wind-light-hydrogen-ammonia integrated system and a scheduling method, and relates to the technical field of renewable energy sources. The method comprises the following steps: after each rolling scheduling period is finished, calculating a relative error between actual wind and light generating capacity and predicted generating capacity; and if the preset threshold value is exceeded, triggering a deviation correction process, otherwise, continuing to use the original plan. During correction, energy deviation is calculated in combination with a scheduling plan and actual output, and bidirectional hierarchical regulation is implemented according to the direction of the energy deviation: hydrogen is preferentially stored when energy is surplus, and then energy is charged and stored; when energy is short, discharging is preferentially carried out, and then hydrogen is released. And dynamically updating the actual states of hydrogen storage and energy storage according to the initial conditions, and taking the actual states as initial conditions of the next period. According to the method, electricity abandoning and energy gaps are effectively reduced through a threshold triggering and grading response mechanism, and the system robustness and the green electricity utilization efficiency are remarkably improved while continuous and stable operation of the ammonia synthesis device is guaranteed.

The invention relates to a new energy power station electricity abandoning analysis method and system in an electricity market environment. The method comprises the following steps of collecting various data and fusing the data into a data set; using the data set and the LSTM model to predict the generating capacity of the new energy power station; determining a power grid constraint, and predicting a power market demand according to the data set; establishing a power abandoning calculation model according to the power grid constraint, the power market demand and the generating capacity, and obtaining the power abandoning quantity of the new energy power station through the power abandoning calculation model; according to the new energy power station optimization strategy making method, a detailed and comprehensive method is adopted in the aspect of data processing, and the method comprises the steps of collecting various types of data (such as new energy power generation data and power grid operation data), and conducting normalization processing and data fusion. The method is helpful for extracting useful information in the data and improving the prediction accuracy of the model.

This invention discloses a forward-looking section over-limit control method and system for transmission-distribution networks incorporating renewable energy. The control method comprises the following steps: obtaining the predicted renewable energy output data using existing data-driven distributed photovoltaic cluster output prediction methods; assuming full renewable energy generation, constructing a scenario where renewable energy is fully connected to the grid; using the Matpower tool to perform power flow calculations to determine the predicted section over-limit situation; establishing a forward-looking section over-limit control model and determining the objective function and constraints, the objective function being to minimize the sum of curtailment cost and over-limit penalty cost; using a CPLEX solver to solve the objective function in a rolling manner over time periods, deriving the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy; and issuing power adjustment commands. This invention, by establishing a multi-time period optimization model, coordinates photovoltaic curtailment and energy storage charging and discharging, significantly reducing the risk of section over-limit, improving grid security, and increasing renewable energy utilization.

The present invention relates to an ultra-high voltage direct current transmission curve optimization method for assisting the receiving province in peak load regulation, comprising the following steps: S1: obtaining the net load curve of the receiving province; S2: decomposing the agreed transmission amount according to the net load curve; S3: determining the peak and valley transmission power, duration and time period distribution in the ultra-high voltage direct current daily transmission curve according to the net load characteristics. The transmission curve optimization method proposed in the present invention can effectively alleviate the peak load regulation pressure of the receiving province, reduce the amount of abandoned wind and photovoltaic power, and reduce the electricity purchase cost of the receiving province.