175 results about "Economic gain" patented technology

The invention provides an intelligent optimization method and system for a revenue mode of a commercial energy storage power station, and relates to the technical field of energy storage power stations. Establishing a multi-dimensional life loss coefficient matrix by analyzing the health state data of the energy storage equipment; a candidate charging and discharging scheduling strategy is generated based on a deep reinforcement learning model, and a double-constraint optimization charging and discharging strategy with predicted income and life loss as a reward function is adopted; and finally generating a control instruction to realize optimized operation of the energy storage power station. According to the method, equipment life loss and economic benefits are comprehensively considered, and long-term benefit maximization of the energy storage power station is realized.

The invention provides an elevator energy recovery application method and system based on a super capacitor, and relates to the technical field of energy recovery, and the method comprises the steps: collecting elevator operation data and super capacitor state data, constructing a state space and an action space, and constructing a reward function according to peak-valley electricity price economic benefits, super capacitor life loss and energy utilization efficiency; training a deep reinforcement learning model based on the double-Q network to obtain an energy recovery optimization strategy; when the elevator is braked, regenerative braking energy is stored in the super capacitor; when the elevator is driven, the stored energy is released for traction; the optimal storage allocation scheme of the multiple elevator rooms is calculated through the virtual energy storage unit, hierarchical control is implemented based on an optimization strategy and the allocation scheme, the upper layer adopts fuzzy self-adaptive weight to determine the energy storage priority, and the lower layer adopts a distributed algorithm to calculate the energy allocation coefficient and the target power; and the charge-discharge rate is updated according to the health state of the supercapacitor.

The invention discloses a wind power plant dual-mode dynamic active wake flow control method and system and a medium, and the method comprises the steps: taking the maximum power output, power balance and fatigue load stabilization as optimization targets for solving and obtaining an optimal control instruction if a current control mode is a power efficiency improvement mode; otherwise, taking the maximum power output as an optimization target to solve and obtain an optimal control instruction; issuing the optimal control instruction to the virtual wind power plant, and delaying to obtain a delayed control instruction; if the mode is a power efficiency increasing mode, directly issuing to a real wind power plant; and if the mode is a power tracking mode, solving a final optimal control instruction by taking power reference tracking, control reference tracking and fatigue load stabilization as optimization targets, and issuing the final optimal control instruction to the real wind power plant. The method aims at weakening the influence of the wake effect in the wind power plant through dynamic active wake control, improving the generating capacity, maintaining the fatigue load balance and bringing higher economic benefits to operators.

The invention discloses a wind power-containing electric power system source load collaborative scheduling method considering the participation of a smelting type high-energy load, and the method comprises the steps: analyzing the scheduling demands of a wind power-containing electric power system, and building a model considering the load of an electric arc furnace and the wind power output uncertainty based on the schedulable characteristics of the load of the electric arc furnace; a data driving method is adopted to generate a large-scale scene, the uncertainty superposition influence of the electric arc furnace load and the wind power output is analyzed, and the reserve capacity needed by the electric power system for coping with uncertainty fluctuation is determined; a smelting type high-energy load self-adaptive electricity price mechanism considering wind power output change and source load fluctuation is provided, and iron and steel enterprises are stimulated to participate in demand response; and establishing an optimal scheduling model giving consideration to interests of multiple parties, and solving an optimal scheduling scheme by adopting an artificial bee colony algorithm. According to the method, economic benefits and social responsibilities of smelting type high-energy load enterprises are considered, support is provided for the enterprises to participate in consumption of blocked wind power, and new energy consumption and economic and stable operation of a power system are facilitated.

The invention discloses a hydropower station experience electric quantity distribution method in an electric power market environment, particularly relates to the field of electric power optimization, and is used for solving the problems of accuracy and adaptability of electric quantity distribution of a hydropower station in a complex market environment. A multi-dimensional feature mapping matrix and a dynamic credibility evaluation system are constructed, and accurate quantitative analysis of historical prediction results is realized; based on the evaluation result, the short-term abnormal signal is accurately corrected by adopting a classification identification method, so that the prediction result can reflect the actual dynamic change in time; furthermore, by combining a nonlinear multi-objective optimization model, three core objectives of economic benefit maximization, risk minimization and ecological flow balance are organically fused, and an electric quantity distribution scheme with high economic benefit, low operation risk and ecological protection requirements is generated through a complex mathematical algorithm.

The invention discloses an energy storage operation optimization method and system based on hierarchical multi-agent reinforcement learning. The method comprises the following steps: firstly, initializing a hierarchical multi-agent reinforcement learning decision framework, and defining an interlayer communication synchronization mechanism; then, designing an upper layer reward function for balancing the electric charge income and the battery life loss cost, and optimizing an upper layer planning strategy; a lower layer reward function integrating current smoothness and budget tracking precision is designed, and a lower layer execution strategy is optimized; and finally, deploying the optimized upper-layer planning strategy and the optimized lower-layer execution strategy to an energy storage scheduling task, generating a charging and discharging power budget by an upper-layer planning agent in a day-ahead scheduling stage, and receiving a budget instruction and performing power adjustment by a lower-layer execution agent. According to the invention, by constructing the hierarchical decision-making architecture, coordinated optimization of short-term economic benefit and long-term life protection of the energy storage equipment is realized.

The invention provides a prediction method and system for quantity report, quotation and bidding by a building load aggregator, and the method comprises the steps: collecting bidding historical data, and carrying out the preprocessing of the bidding historical data; inputting the preprocessed bidding historical data as an input item into a pre-trained quantity and quotation behavior prediction model to obtain a bidding action probability distribution result of the competitor; and based on the bidding action probability distribution result of the competitor, in a preset bidding decision simulation environment, predicting an optimal quantity report quotation bidding strategy of our party as a building load aggregator, and outputting a final prediction result. According to the method, the market competition pattern can be dynamically predicted, and the optimal quantity and quotation strategy is generated, so that the bid winning rate and the economic benefit of the building load aggregator in the demand response real-time market are improved.

The invention relates to a dynamic multi-dimensional quality evaluation system and method for a thermal power plant intelligent inventory supervision model. Real-time data flow of the DCS is collected and compared with the model prediction value, and a prediction error is generated; based on the load rate, the fuel characteristic and other characteristics, the current operation state is matched to a preset working condition library, and historical data is called for index calculation; the method comprises the following steps of: according to stability, reusability and economic indexes such as a variable coefficient of a prediction error, a model calling frequency, economic benefit influence and the like, normalizing the indexes by adopting a range method, and calculating the weight of each index by utilizing an entropy weight method; constructing a weighted standardization matrix, defining a dynamic ideal solution, calculating a close degree index, and outputting a comprehensive evaluation result; according to the scoring result, an optimization instruction is automatically pushed, and model parameter adjustment or data calibration is carried out, a set of dynamic and multi-dimensional thermal power plant supervision model evaluation system is constructed, the model quality can be objectively and comprehensively evaluated, and a closed-loop optimization mechanism is provided.

The invention provides a low-carbon integrated energy system modeling method based on a hybrid energy storage system. And constructing a multi-dimensional constraint and cost optimization objective function, and establishing a global optimization framework of the integrated energy system. Wherein the balance constraint and the assembly constraint ensure dynamic matching of electric / hot / cold / gas multi-energy flow and cooperative operation of equipment, and the problem of unbalanced supply and demand of a traditional system is solved. The carbon emission constraint is divided through a dynamic carbon valence interval, the carbon emission and the carbon cost are in nonlinear correlation, a low-carbon technology path is guided, the green certificate constraint converts excess renewable energy power generation into economic benefits, and dual excitation of environmental protection and economy is formed. And the target function comprehensively optimizes equipment investment, maintenance cost and market income, and drives multi-energy complementation and full life cycle cost optimization. The system is adaptive to renewable energy fluctuation, load change and energy price fluctuation through optimal configuration of system output and equipment capacity, and economical and efficient operation under the low-carbon target is achieved.

The invention discloses a virtual power plant response capability assessment method and device, and relates to the technical field of power system scheduling and operation optimization, and the method comprises the following steps: dynamically selecting an active resource sub-network based on a first model, and generating a first response capability curve, the first model comprising a sparse expert model based on a gating mechanism; initial optimization and joint optimization are carried out on the first model, the initial optimization updates preset network parameters of the active resource sub-network through an attention distillation optimization algorithm, and the joint optimization optimizes parameters of the first model through a prediction error of a first response capability curve and historical data; generating a second response capability curve based on the optimized first model and virtual power plant prediction data; and according to the data parameters of the second response capability curve, calculating a peak-valley arbitrage income, and outputting a virtual power plant response capability evaluation result. The method and the device are used for solving the problems of insufficient resource isomerism processing and disjunction between the evaluation result and the actual economic benefit.

The invention discloses an electric vehicle travel scene ordered charging method under the guidance of dynamic electricity price, and the method comprises the steps: carrying out the charging load space-time distribution prediction through an EV charging load space-time distribution prediction model, and obtaining the load space-time distribution characteristics of each charging station; generating an optimized electricity price strategy through a master-slave game model, and making a dynamic electricity price scheme by an electric vehicle aggregator in combination with a station charging load condition and a charging responsivity function; and simulating user travel behaviors according to the road network traffic flow data, and making a user charging plan based on the corrected electricity price information. According to the method, an ordered charging regulation and control strategy based on dynamic electricity price response is provided, a dynamic electricity price model based on charging load real-time change is constructed, meanwhile, a double-layer game model of a load aggregator and a user is established in combination with user travel space-time distribution characteristics, and an ordered charging optimization strategy giving consideration to multi-party benefits is formed; and finally, dual goals of power grid operation optimization and user economic benefits are realized.

The invention discloses an electric power spot market transaction strategy optimization method and system suitable for a combined distribution and storage main body, and belongs to the field of electrical engineering. According to the method, a quotation strategy optimization model of a joint distribution and storage main body in an electric power spot market is constructed based on a master-slave game architecture. The method comprises the following steps: firstly, respectively establishing transaction strategy optimization models of three subjects including a thermal power generating unit, a new energy power station and industrial and commercial users; secondly, an electric power spot market optimization clearing model is constructed; thirdly, the market optimization clearing model is equivalently converted into a constraint condition of a joint distribution and storage main body optimization problem through a KKT condition, so that a non-convex nonlinear double-layer game model is converted into a nonlinear single-layer optimization problem; finally, nonlinear terms in the optimization problem are linearized, and a mathematical model easy to solve is formed. Therefore, by constructing the transaction strategy model and performing numerical simulation, the optimal transaction strategy of the combined distribution and storage main body is finally output, the optimal transaction strategy can be used for guiding the spot market transaction decision, and the economic benefit is maximized.

The invention discloses a capacity configuration method and system based on participation of energy storage in spot joint market income, and the method comprises the steps: building a capacity planning model framework based on participation of an energy storage power station in electric power spot joint market income based on consideration of uncertainty conditions of wind power output; establishing a bidding model that the energy storage power station participates in the day-ahead energy-frequency modulation combined market under a master-slave game bidding strategy, and calculating the optimal configuration of an economic benefit guide energy storage power station capacity planning model; converting the bidding model into a single-layer equilibrium constraint mathematical programming problem according to a strong duality theory and a KKT condition; and solving the global energy storage power station capacity planning model by adopting a mode of nesting a CPLEX solver in a particle swarm algorithm. The method has the beneficial effects that the economic benefit of the energy storage power station can be maximized through scientific capacity configuration and a market bidding strategy, the market competitiveness of the energy storage power station is effectively improved, and wide application of an energy storage technology in a modern power system is promoted.

The application provides a heating and pressing device and an operation method thereof. The device comprises a substrate with a loading area, an operation window is opened on the loading area, a secondary material positioning mechanism is arranged at the operation window, a primary material positioning mechanism is arranged on the side of the loading area, a top suction assembly is arranged below the loading area, a heat pressing area is formed between the top suction assembly and the secondary material positioning mechanism, a heating and pressing mechanism is arranged on one side of the heat pressing area, the heating and pressing mechanism comprises a moving assembly, a downward pressing and heating assembly and a side pressing and heating assembly are connected to the moving assembly, the downward pressing and heating assembly is arranged above the heat pressing area, and the side pressing and heating assembly is arranged on the side of the heat pressing area. The X and Y direction pushing and pressing structure is matched with the suction and positioning structure to ensure the close contact and position accuracy of small parts and products, improve the assembly effect, optimize the product quality, improve the product yield, and increase the economic benefits. The flexible material is used for pressing and heating, so that the elastic buffer pressure is provided, and the product surface is protected.

The invention discloses a distributed power supply energy storage configuration method and device. The method comprises the following steps: identifying peak load characteristics of a user side based on historical load data; analyzing output data of the distributed power supply according to the historical power generation data; establishing an energy storage optimization configuration model by taking maximization of user economic benefits as an optimization target; a double-layer optimization method is adopted, based on the energy storage optimization configuration model and peak load characteristics, a charging and discharging plan of the energy storage system is optimized at the upper layer, and a dynamic scheduling strategy is optimized at the lower layer; the real-time electricity price and the user load are predicted in a rolling mode, a dynamic scheduling strategy is combined, a charging and discharging plan is further corrected in the operation process of the energy storage system, the consumption proportion of renewable energy sources is optimized in combination with output data, and the energy storage system and the distributed power supply are made to operate cooperatively. According to the invention, optimal configuration and efficient scheduling can be carried out on the distributed power supply and the energy storage system at the user side.

The invention belongs to the technical field of wind turbine generator operation and maintenance, and discloses a wind turbine generator intelligent operation and maintenance decision-making system based on big data and fault prediction. Comprising the following steps: analyzing the residual service life of a key part based on a constructed rule system and acquired related data of a wind turbine generator, and acquiring probability density distribution of the residual service life of the key part; the analysis module is used for generating an expected economic loss curve through the probability density distribution of the remaining service life of the key component, acquiring the total execution cost of each feasible maintenance window based on the expected economic loss curve, and analyzing the accumulated risk cost acquired based on the generated feasible maintenance list; according to the method, the net present value of each feasible maintenance window is determined, an operation and maintenance decision suggestion list is generated, an operation and maintenance work order is automatically distributed after a maintenance scheme is selected based on operation and maintenance decision suggestions, maintenance opportunity selection is improved from experience judgment to a quantifiable economic optimization problem, and asset economic benefits are maximized while equipment reliability is guaranteed.

The invention provides a virtual power plant two-stage joint optimization scheduling method and system for participation of a power market, and a related device, and the method comprises the following steps: 1, depicting the uncertainty characteristics of renewable energy sources, and obtaining a prediction error confidence interval; step 2, constructing a virtual power plant day-ahead scheduling model taking the maximum market income as a target; step 3, obtaining a day-ahead energy declaration curve and an energy storage operation strategy corresponding to the virtual power plant based on the obtained virtual power plant day-ahead scheduling model; 4, obtaining the actual output of the renewable energy in real time, and calculating the output deviation between the obtained actual output and the date energy declaration curve obtained in the step 3; 5, constructing a virtual power plant real-time scheduling model according to the obtained output deviation; 6, generating an interaction strategy between energy storage and a power grid according to the obtained real-time scheduling model of the virtual power plant; on the premise of guaranteeing the power supply stability of the system, the economic benefits of the virtual power plant participating in the power market transaction can be remarkably improved.

The invention relates to the field of power systems, and particularly discloses a virtual power plant scheduling method considering multi-class demand response and user comprehensive satisfaction, which comprises the following steps: constructing a virtual power plant aggregated with a distributed unit, a renewable energy unit, an energy storage system and a load user; constructing a scheduling optimization model of the virtual power plant by taking the maximum operation income in the scheduling period of the virtual power plant as the target, and constructing a user comprehensive satisfaction model by taking the maximum average value of the comprehensive satisfaction of all load users in the scheduling period of the virtual power plant as the target; and by taking the scheduling optimization model as an upper layer model and the user comprehensive satisfaction model as a lower layer model, constructing a virtual power plant double-layer scheduling model considering the multi-class demand response and the user comprehensive satisfaction, and solving to obtain a scheduling decision of the virtual power plant. According to the method, the maximization of economic benefits and environmental benefits can be realized while the virtual power plant ensures the power supply and maintains the stability of a power grid, and the power utilization demand and satisfaction of a user can be ensured.

The invention belongs to the technical field of power system automation and energy storage regulation and control, particularly relates to a thermal power energy storage frequency modulation auxiliary service benefit maximization method, and aims to solve the problems of disjunction between technical response and economic benefit, large equipment loss and poor market adaptability in a traditional frequency modulation strategy. According to the method, a multi-time-scale instruction analysis model is constructed, thermal power coal consumption and energy storage loss characteristics are fused, a dynamic cost-income coupling function is established, and thermal storage power is distributed in real time based on a rolling time domain optimization algorithm; and dynamically correcting model parameters by executing feedback and an online learning mechanism, and synchronously generating a market bidding strategy and benefit pre-judgment report. The system supports state-of-charge boundary adaptive adjustment and equipment collaborative aging evaluation, and is deployed at an edge computing node to realize millisecond-level response. According to the invention, the economic benefit of frequency modulation is obviously improved by 15-25%, the score of frequency modulation performance is more than 95, the energy storage life is prolonged by more than 30%, the fluctuation of unit income is reduced by 40%, and full-link closed-loop intelligent regulation and control and market competitiveness enhancement are realized.

The invention relates to a salt cavern integrated energy system full life cycle economic evaluation method, and the method comprises the steps: obtaining electric energy supply and demand data in a target region, and building a mathematical model of a salt cavern integrated energy system based on the electric energy supply and demand data and at least one salt cavern geological parameter; based on the mathematical model, an objective function is determined with the maximum comprehensive economic benefit in the whole life cycle, and a double-layer optimization model of the salt-cavern comprehensive energy system is established; and performing multi-scene evaluation by using a double-layer optimization model to perform modeling and optimization solution on each scene to obtain economy of the system in different scenes, and determining the optimal configuration of the salt cavern integrated energy system according to the economy of the system in different scenes. Therefore, the problems that the overall value is difficult to accurately evaluate and the scientificity of investment decision and the rationality of resource allocation are influenced due to the fact that a static analysis mode is adopted in related technologies and multiple factors such as related complex technologies, economy and environment are not fully considered are solved.

The invention relates to the technical field of water resource management, in particular to a regional water resource optimal configuration method and system.The method comprises the following steps that a domestic water prediction model and an ecological water prediction model are constructed based on LSTM and used for predicting domestic water and ecological water of a target region respectively, meanwhile, the production water of the target area is estimated through a quota method; predicting the available water supply amount of the target area, and obtaining a future supply and demand analysis result of the water resource of the target area in combination with the prediction results of the domestic water, the ecological water and the production water; when the water demand of the target area is difficult to meet, obtaining the water shortage rate and the economic benefit of the water resource optimal configuration plan based on a WEAP model; and establishing a water resource optimal configuration model, and further comprehensively considering the water shortage rate and the economic benefit to obtain an optimal water resource optimal configuration plan. According to the water resource optimal configuration method, the coordinated development of economic, social and ecological environments can be realized while the water use safety is guaranteed.

The invention discloses a frequency modulation income optimization method for an independent energy storage system. The method comprises the following steps: obtaining a power grid operation data set and a market transaction data set and carrying out format standardization; constructing a time sequence data set based on the standardized power grid operation data set and the market transaction data set; constructing and training a one-dimensional convolution gating circulation network model by using the time sequence data set, and generating a prediction result of a future frequency modulation load and a market electricity price; according to a prediction result, constructing a frequency modulation optimization problem taking frequency modulation economic benefit maximization as a target, and generating a frequency modulation optimization strategy space containing a plurality of independent energy storage frequency modulation strategies; performing iterative search on the frequency modulation optimization strategy space to obtain an optimal independent energy storage frequency modulation strategy; and controlling the energy storage equipment to perform frequency modulation operation according to the optimal independent energy storage frequency modulation strategy. According to the scheme, high prediction stability and response capability can be kept under the market conditions of high volatility and frequent change of electricity price.

The utility model discloses a wire threading device for building electrical work, which relates to the field of building electrical construction. The technical scheme is as follows: it comprises a line tube, one end of which is provided with a wire threading mechanism, the wire threading mechanism comprises two fixed plates, the two fixed plates are both arranged on the front side of the line tube, the rear sides of the two fixed plates are both fixedly connected with positioning plates, the two positioning plates are respectively arranged on the outside of the two sides of the line tube, the outer sides of the two positioning plates are both provided with clamping components, the clamping components comprise two movable plates, the two movable plates are respectively embedded in the inside of the two positioning plates, and the inner sides of the two positioning plates are both provided with clamping plates. The beneficial effects of the utility model are as follows: the utility model greatly improves the efficiency of wire threading for power lines used for building construction, and at the same time, the device adopts a detachable wire threading mechanism, which makes the construction process more convenient. In addition, the device reduces manual intervention, reduces the loss of manpower, and brings great economic benefits to producers.

The invention discloses a super capacitor and thermal power generating unit coupling frequency modulation control capability evaluation method, relates to the technical field of electric-thermal coupling frequency modulation, and aims to adaptively capture key factors influencing distribution accuracy and coordination control performance by introducing dynamic weight updating and factor correlation analysis, so that an evaluation result is more suitable for an actual operation condition, and the evaluation efficiency is improved. The accuracy and timeliness of evaluation are obviously improved; unit layer capability evaluation, coordination control evaluation and comprehensive benefit evaluation are organically fused, so that full-chain and multi-dimensional comprehensive analysis from equipment performance to strategy and then to economic benefit is realized; an evaluation model can be continuously corrected by constructing a closed-loop optimization mechanism for feeding back a final conclusion to an initial weight parameter, so that the high efficiency and advancement of an evaluation system are kept for a long time; the dynamic response speed, the control stability and the overall economic benefit of the combined system are effectively improved, and the method has extremely high practical application value.

The invention discloses an energy storage assisted thermal power generating unit frequency control method and system, and aims to reduce the time of a thermal power generating unit operating in a deep peak regulation state while improving the frequency modulation qualification rate by using an energy storage system to assist the thermal power generating unit in frequency modulation, thereby improving the overall economic benefit of the unit. According to the method, on the basis of analysis of historical statistical data, the actual frequency modulation capacity of the thermal power generating unit at different load points is combined, the insufficient power part of the thermal power generating unit in the frequency modulation process is calculated, supplement is conducted through the energy storage system, and therefore the frequency modulation qualification rate of the thermal power generating unit is increased. In order to further optimize the combined operation economy of the thermal power generating unit and the energy storage system, an economic model of the combined operation of the thermal power generating unit and the energy storage system is constructed. The model is combined with a power generation plan of the thermal power generating unit, the charging and discharging power of the energy storage system is planned, and deep peak regulation of the thermal power generating unit is reduced to the maximum extent while the frequency modulation task of the thermal power generating unit is completed, so that the overall economy of the thermal power storage combined system is maximized.

The invention discloses a loss calculation method and system for transformers with different energy consumption levels, and belongs to the technical field of transformer loss judgment, and the method comprises the following steps: S1, parameter acquisition; s2, calculating a load rate; s3, obtaining a time period division condition and an average electricity price parameter; and S4, calculating the comprehensive loss electric charge. The method provides core economic support for energy efficiency decision by accurately quantifying dynamic operation loss of transformers with different energy efficiency levels, and comprises the following steps: during new equipment type selection, calculating a full life cycle cost balance point of first-level and second-level energy efficiency equipment based on load characteristics and an electricity price mechanism so as to obtain an optimal cost performance scheme; when stock equipment is replaced, the actually measured data of the high-energy-consumption transformer is compared with the first-level energy efficiency limit value and the second-level energy efficiency limit value, technical parameter-economic benefit linkage analysis is achieved, the investment risk is remarkably reduced, and efficient execution of the energy efficiency policy is promoted.

The invention is suitable for the technical field of photovoltaic subsidy strategies, and provides a photovoltaic subsidy strategy optimization method, which comprises the following steps: S1, constructing a three-dimensional niche resource space, determining game core elements, and constructing a distributed photovoltaic promotion scene based on a distributed photovoltaic promotion scene; a traditional single policy subsidy dimension is upgraded to a policy support, cooperation mode and economic benefit three-dimensional benefit resource space, and a precise decision coordinate system is provided for a tripartite game; s2, a third-order dynamic game model is established at the same time, a three-party revenue function is quantified, and the decision sequence of the government, the enterprise and the farmer is taken as a logic chain; according to the photovoltaic subsidy strategy optimization method, for the government, the subsidy fund utilization rate is increased by 30%-40%, the indirect cost proportion is smaller than 30%, and the dual-carbon target is met; for enterprises, the requirements of three types of modes are met, the profit prediction accuracy is improved by more than 40%, and the market coverage is expanded by 50%; and for peasant households, multiple modes adapt to different requirements, the adoption rate is increased by 40%-50%, the annual income fluctuation rate is smaller than 5%, three-party collaborative ecology is constructed, and the dilemma of'policy slop falling, namely stagnation 'is solved.

The invention relates to the technical field of energy equipment management, industrial automation control and information physical systems, in particular to a pumping and storage safe operation monitoring and management system and method based on a digital twinborn technology. Comprising the following steps: S1, collecting unit physical state parameters and market environment economic signals in real time; s2, based on the physical state parameters of the unit, calculating to obtain marginal physical loss cost representing single variable working condition operation; s3, accumulating historical marginal physical loss cost, and calculating to obtain a health depreciation index; s4, correcting the marginal physical loss cost by adopting a dynamic penalty factor, and generating the corrected marginal physical loss cost; s5, in combination with the corrected marginal physical loss cost, calculating a corrected yield after risk adjustment; and S6, determining the risk level of the scheduling opportunity, and executing hierarchical scheduling control corresponding to the risk level. According to the method, the defect that economic benefits and long-term health phases of equipment are separated in a traditional decision is overcome, and accurate assessment of the recessive loss is realized.

The invention discloses a multi-virtual power plant low-carbon retail pricing method based on a non-cooperative game, and belongs to the technical field of power system optimization and energy market transaction, and the method comprises the following steps: building a control model of a single virtual power plant; 2, correcting a dynamic carbon emission factor; 3, deducing the optimal retail electricity price of the plurality of virtual power plants; according to the invention, a multi-virtual power plant non-cooperative game pricing model based on dynamic carbon emission factor-economic benefit double chains is established, a value chain of low-carbon excitation and economic benefit is broken through, an accurate low-carbon benefit acquisition mode is created for the virtual power plant, the virtual power plant is promoted to preferentially dispatch renewable energy sources, and the economic benefit of the virtual power plant is improved. And the low-carbon operation level and the market competitiveness of the regional power system are effectively improved.

The invention belongs to the technical field of waste incineration, and particularly relates to an incineration heat grading utilization method based on energy and quality matching. According to the method, a real-time dynamic grading decision is made based on thermodynamic calculation of real-time steam parameters, the limitation of a fixed pressure grade is broken through, and accurate mapping of steam quality and an energy consumption scene is established; secondly, a steam demand dynamic response model is constructed through an LSTM load prediction module, supply and demand gaps of steam of different qualities are recognized in advance, and a priority distribution matrix is formed; finally, a fuzzy PID control engine and a three-level path switching mechanism are combined, a multi-level optimization system with the economic benefit maximization and the diverse loss minimization as targets is constructed, and optimal dynamic matching of steam parameters and energy consumption equipment is achieved.