13 results about "Power planning" patented technology

This invention discloses a method, apparatus, equipment, medium, and product for power configuration in clean energy bases, belonging to the field of power configuration technology. The method for power configuration in clean energy bases includes the following steps: obtaining demand data for various power configurations; constructing a power configuration model for the clean energy base based on the demand data; and generating a power configuration scheme for the clean energy base using the power configuration model. This invention constructs a power configuration model applicable to integrated wind, solar, coal gas, and hydrogen storage systems. It eliminates repetitive manual work, significantly shortens the design workflow, improves power planning and design efficiency, and eliminates reliance on manual experience, enhancing the scientific rigor and standardization of various power configuration schemes, improving the quality of power planning and design, and reducing power planning and design costs, thereby promoting the development of clean energy bases.

This invention belongs to the field of power planning and new energy power generation. It discloses a method, system, equipment, and medium for configuring the capacity of an amphibious power plant based on monthly balance. Based on the load forecast of the amphibious power plant and the predicted new energy power generation during the hydropower peak and off-peak seasons, a monthly power balance analysis of the amphibious power plant is performed to obtain the power deficit for each power-deficient month and the power balance for each power-excessive month. Based on the power deficit for each power-deficient month, the required coal-fired power generation capacity to ensure power supply during each power-deficient month is determined, and the maximum value is selected to obtain the coal-fired power generation capacity of the amphibious power plant. Based on the power balance for each power-excessive month, the required energy storage capacity to ensure the complete consumption of abandoned new energy power during each power-excessive month is determined, and the maximum value is selected to obtain the energy storage capacity of the amphibious power plant. This achieves a reasonable determination of the coal-fired power generation capacity and the energy storage capacity of the amphibious power plant.

This invention belongs to the field of power planning and design technology, and discloses a method and system for simulating wind farm output. The method first calculates the theoretical output, stochastic reduction factor, low temperature reduction factor, and maintenance reduction factor based on the target basic data of the project location, and calculates the hourly comprehensive reduction factor. Then, the actual output is calculated based on the theoretical output and the hourly comprehensive reduction factor. In this way, the impact of uncertainties such as temperature and maintenance on the output during the actual operation of the wind farm is taken into account. Based on mesoscale reanalysis data or measured wind speed data, it can quickly and accurately simulate the actual output data of the wind farm without the need for a complex modeling process, which can meet the needs of wind power project output prediction.

The invention relates to an alkaline electrolytic cell and PEM electrolytic cell power plan making method and device and a computer storage medium, and belongs to the technical field of hydrogen production. Predicted power of new energy power generation and actual power of the electrolytic cell are obtained, when the predicted power is larger than the actual power, power plans of the alkaline electrolytic cell and the PEM electrolytic cell are made according to the deviation value between the predicted power and the actual power, and the sum of the power of the alkaline electrolytic cell and the power of the PEM electrolytic cell can absorb the deviation value; and when the predicted power is not greater than the actual power, formulating power plans of the alkaline electrolytic cell and the PEM electrolytic cell according to a deviation value between the actual power and the predicted power, so that the sum of the power of the alkaline electrolytic cell and the PEM electrolytic cell can compensate the deviation value. According to the method, the power plan of the alkaline electrolytic cell and the PEM electrolytic cell is formulated by utilizing the deviation value between the predicted power of new energy power generation and the actual power of the electrolytic cell, so that the timeliness and the accuracy of control are improved, and the electrolytic cell keeps relatively high hydrogen production efficiency in hydrogen production.

This disclosure relates to the field of power system technology, and discloses a method, apparatus, equipment, and storage medium for medium- and long-term power planning based on the characteristics of next-generation coal-fired power plants. The method involves constructing a first multi-dimensional operational constraint for next-generation coal-fired power units based on multi-dimensional characteristics, including clean energy reduction, safety, efficient regulation, and intelligent operation. A second multi-dimensional operational constraint is constructed based on the requirements for multi-source coordinated operation. A target constraint system for next-generation coal-fired power units is then constructed based on the first, second, and comprehensive cost constraints. The initial installed capacity scheme is iteratively optimized using a target time-series production model combined with the target constraint system to obtain the target installed capacity scheme. Through the first multi-dimensional operational constraint, the four core characteristics of clean energy reduction, safety, efficient regulation, and intelligent operation are accurately covered, effectively solving the problem of inaccurate characterization of coal-fired power plants.

The application discloses a kind of based on deep Q network's directional energy deposition laser power offline planning method, belong to the field of additive manufacturing.The numerical model of macroscopic temperature field based on directional energy deposition process is constructed as interactive environment, the volume of molten pool is extracted as the state feature of heat process, and the target molten pool volume is determined by experiment calibration.The power planning problem is constructed as Markov decision process, the state vector consisting of molten pool volume sequence, discrete power adjustment action set and Gaussian reward function centered on target volume are defined, and the deep reinforcement learning framework is formed.Under this framework, the deep Q network agent is trained to learn the optimal power adjustment strategy.Finally, the laser power sequence of the deposition process is planned offline using the trained agent.The application can plan the optimal laser power sequence offline, stabilize the heat input of directional energy deposition process, effectively suppress defects such as incomplete fusion and cracks, and improve the quality of additive manufacturing.

This invention provides a power planning method and system based on the electricity market and carbon market, comprising: constructing a typical scenario for the planning target year; establishing a two-layer power planning model based on the electricity market and carbon market; wherein: the upper-layer model is used to determine the power planning scheme and pass the power planning scheme to the lower-layer model; the lower-layer model simulates electricity market and carbon market transactions based on the power planning scheme, and passes the market clearing price to the upper layer; the lower-layer model is transformed into a problem, incorporating the equivalent constraints of electricity market and carbon market clearing into the upper-layer model, and solving the upper-layer model to obtain the final results in the power planning scheme. This invention fully considers the impact of the electricity market and carbon market, constructs corresponding trading models and embeds them as constraints into the power planning model, and can accurately assess the benefits and costs of power sources participating in carbon quota trading in the carbon market and electricity energy trading in the electricity market.

This invention discloses a method and system for power planning and allocation in receiving provinces that considers uncertainties. The method includes: formulating a basic power supply plan; constructing a probabilistic scenario set of annual hydropower utilization hours based on historical water inflow data; setting green and low-carbon targets and calculating the inter-provincial renewable electricity volume required to meet the renewable energy consumption responsibility weight under different scenarios; establishing an inter-provincial transaction cost model to calculate the cost per kilowatt-hour and total transaction cost for each scenario; constructing a system annual operating cost model to obtain the total system cost under each scenario and then averaging it to obtain the expected total cost; and iteratively optimizing the installed capacity of new energy sources with a fixed increment until convergence, outputting the economically optimal solution. This invention achieves a coordinated balance between the economy, greenness, and security of power allocation by probabilistically handling hydropower uncertainties and introducing inter-provincial green electricity trading as an optimization variable.

The present application relates to the technical field of power planning, and more particularly to a thermal power start-up plan and energy storage configuration system for wind power uncertainty, comprising: a scenario generation module for obtaining multiple wind power fluctuation scenarios, a net load module for generating net load curves according to predicted load data and each wind power fluctuation scenario, a flexibility evaluation module for calculating multiple flexibility deficiency indexes of each net load curve under different thermal power start-up capacities, an entropy weight method module for calculating the objective weight of each index and the comprehensive score of each scenario using information entropy, and a start-up capacity module for determining the optimal thermal power start-up capacity that adapts to multiple scenarios according to the comprehensive score of each scenario. In the present application, the thermal power start-up plan simultaneously adapts to multiple wind power fluctuation scenarios, solving the problem that the traditional method only optimizes for a single wind power fluctuation scenario, resulting in a large amount of wind curtailment or load shedding under other fluctuation scenarios, and the inability to guarantee stable system operation.

This invention discloses a multi-stage wind and solar power integration method for DC transmission channels. The method involves acquiring DC transmission channel data; establishing models of the DC transmission channel, sending-end grid, and receiving-end grid based on the data; and establishing a decision model for DC transmission channel renewable energy integration. This invention uses surrogate affine approximation technology to solve the model, outputting two-region planning, trading, generation, and transmission dispatch schemes. This invention demonstrates advantages in solving performance indicators and the feasible region of the problem, and also illustrates the effectiveness of the algorithm in assisting renewable energy integration. It can be applied to DC transmission channel planning, the coordinated allocation of sending and receiving end flexibility resources in the operational field, renewable energy integration, renewable energy integration boundary solving, and DC transmission channel (tethering line) power planning, etc.

This invention discloses a control method, device, equipment, medium, and product for a hybrid electric locomotive, relating to the fields of rail transit engineering and vehicle engineering technology. The method includes: if the vehicle system of the hybrid electric locomotive meets the activation conditions, entering an activation mode; after entering the activation mode, performing operating condition prediction based on line forward information to obtain a target operating condition and corresponding vehicle state data; performing global power planning based on the vehicle state data to obtain target planning data; the target planning data includes a reference power trend, a target SOC reference trend, a minimum excitation baseline, and a weight configuration scheme; determining a target power allocation result based on the target planning data and joint life-cycle cost assessment rules; and converting the target power allocation result into control commands to control the hybrid electric locomotive. Through the above technical solution, optimal operation and intelligent decision-making of the locomotive throughout its entire life cycle can be achieved.

The application discloses a kind of based on deep Q network's directional energy deposition laser power offline planning method, belong to the field of additive manufacturing.The numerical model of macroscopic temperature field based on directional energy deposition process is constructed as interactive environment, the volume of molten pool is extracted as the state feature representing thermal process, and the target molten pool volume is determined by experiment calibration.The power planning problem is constructed as Markov decision process, the state vector consisting of molten pool volume sequence, discrete power adjustment action set and Gaussian reward function centered on target volume are defined to form a deep reinforcement learning framework.Under this framework, the deep Q network agent is trained to learn the optimal power adjustment strategy.Finally, the trained agent is used to plan the laser power sequence of the deposition process offline.The application can plan the optimal laser power sequence offline, stabilize the heat input of directional energy deposition process, effectively suppress defects such as incomplete fusion and cracks, and improve the quality of additive manufacturing.

The application discloses a high-proportion new energy grid-connected power source site selection method based on impedance short-circuit ratio, first defines impedance short-circuit ratio of an in-grid device, and after all grid-connected power sources outside the in-grid device are respectively equivalent to ground admittance, node impedance matrix and Thevenin equivalent impedance of the in-grid device are sequentially solved according to system topology and parameters, equivalent ground admittance value rules and the like; then, a change amount of impedance short-circuit ratio brought by full-load operation of the in-grid device when external grid-connected power sources are accessed or exited is solved; finally, a final power source site selection scheme is decided according to a decision weighted sum of impedance short-circuit ratios of all devices, the change amount and a minimum value of the changed impedance short-circuit ratio. The application realizes a breakthrough from single-point device evaluation to system global optimization for grid-connected power source planning, improves the scientificity of system planning and the safety of grid operation, and provides a system-level decision quantification tool for grid-connected power source site selection.