34results about How to "Reduce light rejection" patented technology

The invention discloses an electric heating energy storage poly-generation system comprising a heat pump system, a heat and cold storage system, a heat supply system, a refrigeration system and a power generation system. The heat pump system comprises a motor, a compressor, a heat storage heat exchanger and a cold storage heat exchanger. The heat and cold storage system comprises a high-temperature storage tank, a normal-temperature storage tank and a low-temperature storage tank. By means of the system, the renewable energy source electricity or electricity generated when the electrical network load is at the trough can be stored in the form of heat and coldness, and meanwhile, the stored heat or coldness can be used for conducting heating, refrigeration and power generation.

The invention discloses a coordinated scheduling method for an electricity-hydrogen multi-energy complementary DC microgrid, and the method is established based on the electricity-hydrogen multi-energy complementary DC microgrid, and comprises the following steps: initializing each system; performing the day-ahead prediction of the output of a renewable energy power generation system and the localload demand; performing day-ahead economic dispatching based on the predicted power, the electric energy storage system reserve SOC and the hydrogen energy system reserve SOHC; predicting photovoltaic, fan output and local load requirements in real time in an ultra-short period; and carrying out real-time rolling optimization on the day-ahead economic dispatching result according to the ultra-short-term prediction result. According to the invention, through day-ahead and online coordinated scheduling, the normal operation of the electricity-hydrogen multi-energy complementary DC microgrid isensured, the optimal operation of the system is ensured, and the influence caused by uncertainty is reduced; and the economy of the system is improved, and the working efficiency of the microgrid is improved.

The invention discloses a capacity optimization configuration method for an urban rail transit photovoltaic energy storage system. The method comprises the steps: formulating a time-sharing operationstrategy according to the operation characteristics that the morning and evening peak load capacities of urban rail transit are large to determine operation states of photovoltaic, energy storage andpower grid at different time periods; researching a typical daily load curve and a photovoltaic output curve to carry out output adaptability analysis, and establishing an optimization model taking voltage fluctuation and economy as target functions by integrating photovoltaic and energy storage time-sharing operation characteristics and output adaptability analysis; converting multiple targets into a single-target optimization function in a weight assignment mode; carrying out solving through a particle swarm optimization algorithm to obtain optimal configuration of the energy storage capacity of the system. The method facilitates energy conservation and emission reduction of the urban rail system and local photovoltaic absorption, meanwhile, reduces network voltage fluctuation to improvethe traction side electric energy quality; and time-sharing operation is achieved, photovoltaic peak clipping and valley filling and load peak clipping are conducted through energy storage, and the economical efficiency of the system can be improved.

The invention provides an active power coordination control method and system of an optical storage power station. The method comprises the following steps: calculating the reference value of the active power of the optical storage power station according to the frequency of the optical storage power station, the frequency change rate and the active power control instruction of the automatic generation of the electric network; determining The active power coordination control mode of optical storage power station according to the frequency of the optical storage power station. Based on the active power reference value and the active power coordination control mode of the photovoltaic storage power station, obtaining the active power control commands of the photovoltaic unit and the energystorage unit, and carrying out the active power regulation of the photovoltaic storage power station according to the active power control commands of the photovoltaic unit and the energy storage unit. The technical proposal provided by the invention improves the power grid stability support strength by configuring an energy storage system, considering the use of an energy storage unit with maximum capacity, and carrying out centralized active power coordination control on the photovoltaic unit and the energy storage unit.

The invention discloses a reactive power optimization method for a photovoltaic reactive power partition pricing power distribution network, and the method comprises the steps: proposing a controllable photovoltaic reactive power partition pricing model, taking the minimum reactive comprehensive cost and the minimum deviation between active power loss and voltage as optimization targets, and constructing a power distribution network active-reactive power optimization model including response PV inverter reactive partition electricity price, static Var compensator (SVC) dynamic compensation, on-load voltage regulation equipment OLTC tap and capacitor bank switching; and processing nonlinear terms in the model by adopting mathematical means such as second-order cone programming and a large Mmethod, finally obtaining a mixed integer second-order cone programming model of active-reactive coordination optimization of the power distribution network containing controllable photovoltaic in the power market environment, and segmenting and solving the model by adopting a Benders decomposition method. According to the invention, the reactive capacity of a photovoltaic inverter and the reactive support capability of original discrete equipment of a distribution network are reasonably and coordinately utilized, the active power loss is reduced, and the user voltage quality is ensured.

The invention provides a hydrogen-containing energy storage microgrid optimization operation method based on deep reinforcement learning, and the method comprises the steps: building an electrolytic cell efficiency characteristic model through a linear interpolation method, combining the electrolytic cell efficiency characteristic model with a gas turbine model, an electrochemical energy storage model, a hydrogen storage tank model, a fuel cell model and the like, and taking the microgrid operation cost as a target, constructing an optimized operation model of the hydrogen-containing energy storage micro-grid. And finally, solving a sequence decision problem of micro-grid optimization operation by adopting a depth deterministic strategy gradient algorithm. According to the method, the efficiency characteristic of the electrolytic cell is considered, the hydrogen energy storage capacity can be fully utilized, the optimization problem is solved according to the deep reinforcement learning principle, the operation cost of the hydrogen-containing energy storage microgrid is reduced, and good generalization is achieved.

The invention discloses a garden integrated energy system day-ahead economic dispatching method considering wind and light uncertainty. Firstly, a two-stage adjustable robust optimization day-ahead dispatching model considering combined thermoelectric demand response is established by taking minimum basic scene operation cost as an objective function and combining related equipment and operation constraints of a garden system. due to the fact that the CCG method has better calculation efficiency in processing the robust optimization model, the CCG method is used for solving. And finally, a commercial solver Gurobi is applied to perform example simulation, a two-stage robust optimization scheduling strategy considering the combined thermoelectric demand response is obtained, it is verified that the method can better process uncertainty occurring in the system, meanwhile, the operation cost of a park can be reduced, and consumption of new energy is promoted.

The invention relates to a photovoltaic grid-connected inverter control method, in particular to a photovoltaic grid-connected inverter control method for preventing voltage out-of-limit of a low-voltage distribution network by considering the influence of line impedance and operating environments on a photovoltaic inverter. Voltage out-of-limit of a grid connection point of the inverter can be prevented, and light discarding amount can be decreased as far as possible by the aid of the residual capacity of the inverter on the premise of ensuring the voltage quality of the grid connection point when voltage exceeds upper limit. Compared with a traditional method, when the voltage of the grid connection point exceeds the upper limit, an active and reactive power matching method is designed by reverse thinking on the premise of ensuring the voltage quality, and the light discarding amount is decreased by the residual capacity of the inverter.

The invention discloses a multiple flexible resource multi-state risk calculation method. A single flexible resource schedulable potential value evaluation analysis model is established for a power grid comprising an electric automobile, a heat pump, an air conditioner and a distributed power source, and schedulable potential values of the electric automobile, the heat pump, the air conditioner and the distributed power source can be respectively acquired through the single flexible resource schedulable potential value evaluation analysis model; a multiple flexible resource gathering schedulable potential value evaluation model is established, and a schedulable potential value after multiple flexible resource gathering is acquired by calculation, a multiple flexible resource multi-state risk calculation model is established, different probabilities of the multiple flexible resources in multiple states are acquired, and the multiple flexible resource multi-state risk information is acquired through calculation. The method is advantaged in that the flexible resource risk information of the power grid is acquired under the action of multiple uncertain factors, a risk level of the power grid under the action of uncertain factors is identified, bases are provided for bidirectional interaction between the flexible resources and the power grid, and scientific bases are provided for safe operation of an intelligent power grid.

The invention discloses a network source coordination virtual synchronous machine control method of an optical storage integrated system. An optical storage integrated system based on the method is ofa two-stage structure. Photovoltaic and energy storage are connected to a power grid by adopting the same inverter, photovoltaic and energy storage batteries are respectively connected to a direct current bus of the inverter in parallel through respective DC/DC converters, and the two DC/DC converters and the inverter are controlled by adopting a network source coordination virtual synchronous machine control scheme. The inverter realizes inertia control and reactive droop control; a DC/DC converter of the battery realizes active droop control; when the voltage of the direct-current capacitoris not higher than the upper limit value Udcuplimit, the photovoltaic DC/DC converter realizes maximum power output control; and when the voltage of the direct current capacitor exceeds the upper limit value Udcuplimit, the photovoltaic DC/DC converter automatically enters light abandoning control. Inertia and droop support can be provided for the power grid, and the power output to the power grid can be automatically adjusted when the source side power fluctuates, so that light abandoning is reduced, and the requirement for the capacity of an energy storage battery is reduced.

According to the comprehensive energy system operation optimization device considering the user demand response characteristics under the carbon emission cost, based on a computer system, the carbon emission characteristics of a coal-fired power generation unit and a gas-fired boiler are analyzed, a comprehensive energy system carbon dioxide emission model and a stepped carbon emission cost model are constructed, and the user demand response characteristics of the coal-fired power generation unit and the gas-fired boiler are optimized. Calculating the carbon dioxide emission cost of energy consumption at each moment; on the basis, a user demand response model guided by double signals of the carbon emission cost and the energy purchase price is constructed, and an integrated energy system operation scheduling model is constructed with the purpose of minimizing the energy purchase cost and the carbon emission cost of the integrated energy system. The system can fully reflect the environment cost of operation of coal electricity, fuel gas and other equipment, more effectively encourages a user to use more energy in the clean energy output peak period, promotes the consumption of clean energy, reduces the wind and light abandoning conditions of the system, and reduces the degree of dependence on external energy at the same time.

The invention discloses an economic quantitative model for evaluating the improvement degree of a power distribution network project on the operation performance of a power distribution network. The model is used for evaluating the improvement degree of the operation performance of the power distribution network project based on project investment cost so as to help investors to analyze the cost performance of a target power distribution network project and the overall profitability of the society. The model comprises benefit increase brought by power grid performance improvement in four aspects of power distribution network power supply reliability improvement, power grid improvement, power supply capability enhancement and energy utilization enhancement caused by a power distribution network project, and project investment construction cost and later operation and maintenance cost. Economic quantitative analysis is performed on the power grid operation performance improvement broughtby the project based on the economic cost of the distribution network project so that the defect that the actual economic 'benefit' of the distribution network project is difficult to quantify due tothe fact that the performance improvement in the technical aspect of the project and the investment cost in the economic aspect are separately compared by the existing model can be compensated.

The invention discloses a photovoltaic power station bidding optimization method based on consideration of an energy storage demand response effect. The method comprises the steps of obtaining a comprehensive price incentive value of a system operator for a photovoltaic output curve based on preset evaluation index data; calculating the expected electricity selling income of the photovoltaic powerstation based on the photovoltaic output basic rate, the comprehensive price excitation value, the bidding curve and other data, and calculating the cost of purchasing the energy storage resources with the demand response effect; and establishing a photovoltaic power station expected revenue maximization objective function, iteratively searching an expected revenue maximum value through an intelligent optimization algorithm, and obtaining a bidding curve and an energy storage effect demand response resource purchase strategy when the expected revenue maximum value is obtained. The incentive price mechanism is added into the expected revenue maximization objective function of the photovoltaic power station, so that the photovoltaic power station can be forced to purchase the energy storageresource with the demand response effect, the energy storage resource with the demand response effect is reasonably utilized and purchased, and power generation of the photovoltaic power station is more economical.

The invention belongs to the field of electric power automation, and discloses a bidding capacity determination method, system and device for a virtual power plant and a storage medium, and the method comprises the steps of obtaining the predicted power generation power and prediction error distribution of an uncontrollable power supply bidding day in the virtual power plant, and the maximum power generation power of a controllable power supply bidding day in the virtual power plant; according to the prediction error distribution of the uncontrollable power supply bidding day, obtaining a plurality of reserved capacities of the controllable power supply bidding day and deviation power of each reserved capacity; solving a preset generated power determination model to obtain the maximum profit of the virtual power plant participating in the power market and the generated power under the maximum profit under each reserved capacity; and obtaining the reserved capacity with the maximum profit of the virtual power plant participating in the electricity market in all the reserved capacities, and taking the generated power under the reserved capacity as the bidding capacity. The maximum participation of the actual power generation power of the uncontrollable power supply is realized, the wind curtailment amount and the light curtailment amount are greatly reduced, the consumption of clean energy is effectively promoted, and the overall power generation cost is reduced.