40results about How to "Increase Internet power" patented technology

The invention discloses an IGCC power station peak regulating device achieving energy storage through an air separation system and a method. The device comprises a gasification furnace, a synthesis gas purification unit, a gas turbine power generation system, a waste heat boiler system and a steam turbine power generation system; oxygen needed by the gasification furnace is supplied by the air separation system; the air separation system comprises an air cooling and compressing system which supplies cooling air to a rectifying tower and can achieve variable frequency regulation, air in the rectifying tower is separated into nitrogen and oxygen, nitrogen and oxygen are stored in a liquid nitrogen storage tank and a liquid oxygen storage tank respectively, the liquid oxygen storage tank is connected with an oxygen heater through a liquid oxygen pump and a cold box, and high-pressure oxygen coming out from the oxygen heater is delivered to the gasification furnace. According to the device and method, the defects that an IGCC power generation system is low in load varying speed and poor in power grid peak regulating capacity are overcome, the capability of quickly regulating the IGCC output power is achieved through the storage capacity of the air separation system, and the whole-plant output power can be increased and decreased by within 20% most quickly in a short time.

The invention relates to a charge-discharge control method and system of an energy storage system. The method comprises following steps: collecting the scheduling data and theoretical output value ofa photovoltaic power station, determining a light discarding period, a tracing plan period, a light discarding control strategy, and a tracing plan control strategy; during the light discarding period, executing the light discarding control strategy; and during the tracing plan period, executing the tracing plan control strategy. The discharge and charge of an energy storage system is realized. The method can improve the on-grid energy of a photovoltaic power station and reduce the measurement cost generated by insufficient tracing precision and thus greatly increases the profits of the photovoltaic power station.

The invention relates to the technical field of new energy power generation, in particular to a photovoltaic power station optimization control method actively participating in power auxiliary service. The method comprises the following steps: determining a coordinated control strategy of the primary frequency modulation and the secondary frequency modulation of the photovoltaic power station AGC;determining the active power control and distribution mode of a photovoltaic power station; determining the optimal control strategy of reactive power based on AVC photovoltaic power station; determining the reactive power control and distribution mode of the photovoltaic power station. The invention has the advantages of: (1) fully utilizing the non-functional force of the inverter under the steady state condition, reducing the reactive load of the reactive power compensation device SVC / SVG, reducing the power consumption of the reactive power compensation device, reducing the auxiliary power consumption, and increasing the on-grid power quantity of the distributed photovoltaic power station; (2) guaranteeing that the reactive power compensation device SVC / SVG can reserve more reactive power adjustable degree in steady state, and can have enough reactive power compensation ability a in transient process, so as to ensure voltage stability in transient process and avoid inverter disconnection.

The invention discloses a reactive voltage control sensitivity analysis method aiming at scaled wind power. The method comprises the following steps that a system sensitive equation is calculated; a Jacobi matrix including the studied node power or the voltage sensitivity information is calculated; the sensitivity control is carried out by aiming at the response features of each wind power plant. On the premise of ensuring the safe and economic operation of an electric network, the goals of greatly improving the receiving and sending capability of the electricity network on new energy sources, reducing the wind curtailment and improving the new energy online electricity quantity are achieved.

The invention discloses an ultra-short-term wind power prediction method based on an autoregression moving average model. The ultra-short-term wind power prediction method based on the autoregression moving average model comprises the steps that data are input to enable parameters of the autoregression moving average model to be obtained; input data required by wind power prediction are input into the autoregression moving average model determined according to the parameters of the autoregression moving average model, so that a prediction result is obtained. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the wind power generated during wind power generation. The ultra-short-term wind power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses an in-farm reactive power control method for a wind farm. The method includes the steps of evaluating reactive output capacity of a wind farm reactive source; according to the results of evaluation, judging whether or not the wind farm is under emergency running; if not, preferring reactive output of doubly-fed wind turbine units; if yes, preferring adjustment of reactive power of a reactive compensator; distributing reactive powers of the doubly-fed wind turbine units according to the judgment above. The method has the advantages that in-farm reactive voltage control for the wind farm is achieved, operational safety and stability of a power system during connection of large-scale wind power is guaranteed, grid safety is guaranteed, and on-grid energy of new energy resources is increased.

The invention discloses a photovoltaic generation power prediction method based on a self-learning radial basis function. The photovoltaic generation power prediction method based on the self-learning radial basis function comprises the steps that model training is conducted to enable an SVM model to be obtained; data required by photovoltaic generation power prediction are input into the SVM model obtained through training, so that a prediction result is obtained. Key information is provided for new energy power generation real-time scheduling, a new energy power generation plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the photovoltaic generation power generated during photovoltaic generation. The ultra-short-term prediction accuracy is effectively improved by the adoption of a composite data source, and thus high-accuracy short-term photovoltaic generation power prediction is achieved.

The invention discloses a power grid whole-grid reactive power optimization method based on an improved differential evolution algorithm. The method is characterized by including: performing active power grid loss analysis based on load flow calculation; performing whole-grid optimization according to the grid loss analysis result and based on the improved differential evolution algorithm. The method has the advantages that the receiving and outputting capacity of a power grid to new energy is increased greatly while safe and economical operation of the power grid is guaranteed, wind curtailment is reduced, and on-grid energy of the new energy is increased.

The invention discloses a voltage control method of a 330kV wind farm collection substation. The voltage control method of the 330kV wind farm collection substation comprises the following steps: a wind farm collection station is controlled to make a voltage out-of-limit judgment, a control strategy is started when voltage is out of limit, and the control is immediately ended when a set range is satisfied; a capacitive reactor is regulated and controlled; transformer taps are regulated; a subordinate actuating station conducts longitudinal regulation to complete the control. On the premise that a power grid is guaranteed to run safely and economically, the capacity of accepting and delivering new energy of the power grid is realized, the wind curtailment is reduced, and the goal of improving the on-grid energy of the new energy is achieved.

The invention discloses an ultra-short-term photovoltaic generation power prediction method based on a self-learning composite data source. The ultra-short-term photovoltaic generation power prediction method based on the self-learning composite data source comprises the steps that data are input to enable parameters of an autoregression moving average model to be obtained; input data required by photovoltaic generation power prediction are input into the autoregression moving average model determined according to the parameters of the autoregression moving average model, so that a prediction result is obtained, post-evaluation is conducted on the prediction result, namely the error between a predicted value and a measured value is analyzed, and order determination of the model and estimation of the parameters of the model are conducted again if a predicted error is larger than an allowable maximum error. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the photovoltaic generation power generated during photovoltaic generation. The ultra-short-term photovoltaic generation power prediction accuracy is effectively improved due to the fact the composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses an ultra-short-term photovoltaic generation power prediction method based on a composite data source autoregression model. The ultra-short-term photovoltaic generation power prediction method based on the composite data source autoregression model comprises the steps that data are input to enable parameters of the autoregression model to be obtained; input data required by photovoltaic generation power prediction are input into the autoregression model which is determined according to the parameters of the autoregression model, so that a prediction result is obtained; model training basic data are input, order determination is conducted on the autoregression model AR(p) according to a residual variogram method, and the parameters of the model AR(p) with the determined order are estimated according to a moment estimation method. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the photovoltaic generation power generated during photovoltaic generation. The ultra-short-term photovoltaic generation power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses a peak regulation power generation system and method coupled with compressed air energy storage. With the development and utilization of large-scale renewable energy sources, the peak-valley difference of a power grid is increasingly increased, and the bearing capacity is also limited. According to the technical scheme, when the power grid is in a power consumption valley period, air is compressed through power generated by a coal-fired unit and then stored in a storage space, and on the premise that it is guaranteed that the actual generation power of the coal-fired unit is higher than the minimum guaranteed generation power, the on-grid power of the coal-fired unit is effectively reduced; and when the power grid is in a power consumption peak period, the compressed air in the storage space is fed into a gas turbine for power generation, so that the power consumption of a main compressor is reduced, the on-grid power of the gas turbine is improved, and the natural gas consumption is reduced. According to the peak regulation power generation system and method coupled with compressed air energy storage, support can be provided for peak load shifting of the power grid, so that the renewable energy consumption capability is improved, and the usage amount of high-grade energy such as natural gas can be reduced on the premise that the on-grid power of the system meets the power grid adjustment requirement.

The present invention discloses a control method of an energy storage system for a wind turbine generation set and a communication management system which are used to ensure the safe operation of theenergy storage system in a normal condition or an extreme weather. The method comprises the steps that: an energy storage coordination controller obtains related information of a wind power plant andreal-time information of a wind turbine generation set; and the energy storage coordination controller issues a control command to the energy storage system according to the obtained information to control the energy storage system to be operated in a normal operation mode or a typhoon operation mode. The method controls the energy storage system to be switched between the two operation modes according to the information of the wind power plant and the wind turbine generation set to ensure the safe starting and operation of the energy storage system in the extreme condition. During the loss ofthe external power grid electric power support, the control method of an energy storage system for a wind turbine generation set and a communication management system supports normal operation of a power utilization system itself to effectively improve the safety of the wind turbine generation set. In the normal operation state of the wind turbine generation set, the charge-discharge energy storage system is controlled to achieve fan grid-connected power regulation and improve the unit online electric quantity.

The invention provides a system for generating hydrogen through a high-temperature solid electrolytic tank by means of thermal power plant peak load regulation electricity. The system for generating the hydrogen through the high-temperature solid electrolytic tank by means of the thermal power plant peak load regulation electricity comprises a power grid peak load regulation control system, a power transmission and distribution and electrolytic tank power supply system, a high-temperature solid electrolytic tank hydrogen generating system, an electrolytic tank high-temperature steam supplying system and a hydrogen collecting, purifying and outward transmission system. The power transmission and distribution and electrolytic tank power supply system is a newly added interval on an outgoing bus of a power plant. An electric switch is arranged on the interval. The electric switch is connected with a step-down transformer and an inverter on a power transmission network. The other end of the step-down transformer and the other end of the inverter are connected with the high-temperature solid electrolytic tank hydrogen generating system. In the electrolytic tank high-temperature steam supplying system, a power plant main steam bypass guides out high-temperature steam, and the high-temperature steam is supplied to the electrolytic tank. By the adoption of the system for generating the hydrogen through the high-temperature solid electrolytic tank by means of the thermal power plant peak load regulation electricity, electrolysis hydrogen generation is conducted through the thermal power plant peak load regulation electricity, the main steam of the power plant is guided out, electrically overheated and then conveyed into the electrolytic tank, the hydrogen generation efficiency of the solid electrolytic tank is improved, the peak load regulation electricity of the power plant is greatly utilized, and a valuable peak load regulation load is provided for the power plant.

The invention discloses a photovoltaic generation power prediction method based on a self-learning composite data source autoregression model. The photovoltaic generation power prediction method based on the self-learning composite data source autoregression model comprises the steps that data are input to enable parameters of the autoregression model to be obtained; input data required by photovoltaic generation power prediction are input into the autoregression model determined according to the parameters of the autoregression model, so that a prediction result is obtained; post-evaluation is conducted on the prediction result, namely the error between a predicted value and a measured value is analyzed, and order determination of the autoregression model AR(p) and estimation of the parameters of the model AR(p) are conducted again if a predicted error is larger than an allowable maximum error. The ultra-short-term photovoltaic generation power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention relates to a thermal power plant power generator unit with a variable-frequency power generator unit and a steam turbine power generator unit in coaxial arrangement. The thermal power plant power generator unit comprises the steam turbine power generator unit consisting of a steam turbine and a first power generator, wherein the steam turbine drags the first power generator to rotate at a fixed speed to generate electricity, the thermal power plant power generator unit also comprises the variable-frequency power generator unit consisting of a speed regulation gearbox and a second power generator, the rotating speed of the steam turbine is output to the second power generator after the speed regulation by the speed regulation gearbox, and the electricity is supplied to a variable-frequency plant electricity consumption system through the second power generator. According to the thermal power plant power generator unit, industrial frequency electric energy can be generated by the first power generator to be used for on-line sales, and variable-frequency electric energy can also be generated by the second power generator to be used for self plant electricity consumption; compared with a conventional steam turbine power generator unit, the thermal power plant power generator unit has advantages that the output force of the steam turbine is sufficiently utilized, the operation efficiency of the steam turbine is improved, the electric energy is provided for major power loads in the plant through the second power generator, the integrated frequency conversion of the major power loads in the whole plant is realized, the plant electricity consumption rate is reduced, the electric energy is saved, the on-grid electric quantity is increased, and the power generating income of the power plant is improved.

The invention discloses a method for calculating reactive compensation configured capacity for a wind farm. The method includes calculating reactive compensation capacity required by a squirrel-cage asynchronous wind turbine unit belonging to a constant-frequency constant-speed asynchronous generator set; calculating reactive compensation capacity required by the constant-frequency constant-speed asynchronous generator set; calculating reactive compensation capacity required by a permanent magnet direct-driven synchronous generator set; calculating reactive compensation capacity required by the whole wind farm; calculating reactive compensation capacity required by an in-grid substation of the wind farm; acquiring a total required reactive compensation capacity, according to the reactive compensation capacity required by the wind farm, the reactive compensation capacity required by the in-grid substation of the wind farm and reactive compensation capacity required by a line. The method has the advantages that on-grid energy of the wind farm can be effectively increased, wind curtailments are reduced, and operation level of new energy power generation is increased.

The invention discloses a wind power prediction method based on a self-learning composite data source autoregression model. The wind power prediction method based on the self-learning composite data source autoregression model comprises the steps that data are input to enable parameters of the autoregression model to be obtained; input data required by wind power prediction are input into the autoregression model determined according to the parameters of the autoregression model, so that a prediction result is obtained; post-evaluation is conducted on the prediction result, namely the error between a predicted value and a measured value is analyzed, and order determination of the autoregression model AR(p) and estimation of the parameters of the model AR(p) are conducted again if a predicted error is larger than an allowable maximum error. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the wind power generated during wind power generation. The ultra-short-term wind power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses an ultra-short-term photovoltaic generation power prediction method based on an autoregression moving average model. The ultra-short-term photovoltaic generation power prediction method based on the autoregression moving average model comprises the steps that data are input to enable parameters of the autoregression moving average model to be obtained; input data required by photovoltaic generation power prediction are input into the autoregression moving average model determined according to the parameters of the autoregression moving average model, so that a prediction result is obtained. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the photovoltaic generation power generated during photovoltaic generation. The ultra-short-term photovoltaic generation power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses a voltage control method aiming at a 330kV wind power plant collecting transformer substation. The method comprises the following steps that the wind power plant collecting transformer substation is controlled to carry out voltage out-of-limit judgment; a capacitance reactor of the device in the wind power plant is regulated and controlled; a lower stage executing station carries out longitudinal regulation in the regulation process, so that the voltage control on the wind power plant is completed. On the premise of ensuring the safe and economic operation of an electricity network, the goals of greatly improving the receiving and sending capability of the electricity network on new energy sources, reducing the wind curtailment and improving the new energy online electricity quantity are achieved.

The invention discloses a unit steam extraction heat supply energy gradient utilization method. Based on a heating heat network, the heating heat network comprises a backpressure power generator unitand a circulation water pump turbine. Unit steam extraction is at least divided into two paths, and the amount of each path of unit steam extraction is output according to the step level. According toheat energy carried by each path of unit steam extraction, the backpressure power generator unit is utilized for converting energy into electric energy, and the electric energy is input into the heating heat network to be used for input into a power grid. The kinetic energy carried by each path of unit steam extraction does work through the circulation water pump turbine, and the kinetic energy is converted into heat energy. After the method is adopted, all kinetic energy and heat energy of the unit steam extraction can be recycled, the on-grid energy of a power plant can be increased throughthe recycled electric energy, the steps are simple, implementation is easy, and cost is low.

The invention discloses an ultra-short-term wind power prediction method based on a composite data source autoregression model. The ultra-short-term wind power prediction method based on the composite data source autoregression model comprises the steps that data are input to enable parameters of the autoregression model to be obtained; input data required by wind power prediction are input into the autoregression model which is determined according to the parameters of the autoregression model, so that a prediction result is obtained, wherein the method for obtaining the parameters of the autoregression model by inputting the data specifically comprises the steps that model training basic data are input, order determination is conducted on the autoregression model AR(p) according to a residual variogram method, and the parameters of the model AR(p) with the determined order are estimated according to a moment estimation method. Key information is provided for new energy power generation real-time scheduling, a new energy power generation day-ahead plan, a new energy power generation monthly plan, new energy power generation capability evaluation and wind curtailment power estimation by predicting the wind power generated during wind power generation. The ultra-short-term wind power prediction accuracy is effectively improved due to the fact a composite data source is introduced, and thus the on-grid energy of new energy resources is effectively increased on the premise that safe, stable and economical operation of a power grid is guaranteed.

The invention discloses a coal-fired unit peak regulation power generation system and method coupled with thermochemical energy storage. According to the technical scheme, when a power grid is in a power utilization trough period, a part of power generated by a coal-fired unit is used for carrying out a reduction reaction on metal oxide, then the heat storage process is completed, and then the on-grid power of a peak regulation power generation system of the coal-fired unit is rapidly reduced; when the power grid is in the peak period of electricity utilization, the metal oxide is subjected to oxidation reaction to complete the heat release process so as to heat compressed air at an inlet of the air turbine, and then the on-grid power of the peak regulation power generation system of the coal-fired unit is rapidly improved; steam generated by the waste heat boiler can extrude part of extracted steam of the steam turbine to assist in improving the output power of the peak regulation power generation system of the coal-fired unit. According to the method, the deep peak regulation level of the coal-fired unit peak regulation power generation system can be improved, the rapid load change capacity can be improved, support is provided for peak clipping and valley filling of a power grid, and then the renewable energy consumption capacity of the power grid is improved.

The invention discloses a voltage control method of a 330kV wind farm collection substation. The voltage control method of the 330kV wind farm collection substation comprises the following steps: a wind farm collection station is controlled to make a voltage out-of-limit judgment, a control strategy is started when voltage is out of limit, and the control is immediately ended when a set range is satisfied; a capacitive reactor is regulated and controlled; transformer taps are regulated; a subordinate actuating station conducts longitudinal regulation to complete the control. On the premise that a power grid is guaranteed to run safely and economically, the capacity of accepting and delivering new energy of the power grid is realized, the wind curtailment is reduced, and the goal of improving the on-grid energy of the new energy is achieved.

The invention discloses a new energy cross-season energy storage heating system combining a water source heat pump and an air source heat pump. The new energy cross-season energy storage heating system comprises the water source heat pump, a cross-season energy storage device, the air source heat pump, a heating circulating pump and a heating pipeline. The heating pipeline is used for being connected with return water of a heating user, the heating pipeline sequentially passes through the heating circulating pump, the air source heat pump and the hot water end of the water source heat pump, and the heating pipeline is further used for being connected with feed water of the heating user. The system has the technical effects that the low energy efficiency of a pure electric heating system is avoided, the problem that the heating quality of a pure air source heat pump system is difficult to guarantee is avoided, the electricity quantity of abandoned electricity in non-heating seasons and the high energy efficiency of high-temperature weather are fully utilized, and the purposes of absorbing the electricity quantity of the abandoned electricity and reducing electric energy consumption are achieved.

The invention relates to the technical field of thermal power generation, in particular to a double-effect steam turbine power generation system which comprises a first circulation pipeline, a second circulation pipeline, a third circulation pipeline and a fourth circulation pipeline. The second circulating pipeline comprises a first turbine, a reheater, a second turbine, a condenser body, a compressor and a heater body which are in circulating communication; the at least one-stage low-pressure heater and the at least one-stage high-pressure heater are arranged in parallel with the liquid side of the condenser body; the steam turbine set is communicated with a steam pipeline, the hot side of the heater body is installed on the steam pipeline in series, and the hot side of the reheater is installed on at least one steam pipeline communicated with the high-pressure heater in series. The first circulating pipeline and the second circulating pipeline are subjected to coupling heat exchange, so that the temperature of a backflow medium output from the high-pressure heater can be increased, the backheating steam extraction superheat degree is reduced, the heat exchange loss is reduced, and the energy consumption of a turbine unit power generation system is reduced.