Power distribution network scheduling method and system based on new energy output prediction data

Abstract

The invention discloses a new energy output prediction data-based power distribution network scheduling method and system, and relates to the technical field of power grid scheduling, and the method comprises the steps: making a day-ahead scheduling plan according to regional prediction power consumption data and regional prediction new energy power generation data; according to the regional real-time weather data, predicting the generation power change trend of each new energy generator set in a short period; obtaining a power grid system load change trend in a short period; and making an intra-day short-term scheduling plan according to the power generation power change trend of each new energy generator set and the load change trend of the power grid system. According to the method, factors such as the electric power cleaning degree and the start-stop cost of the conventional generator set are considered during day-ahead scheduling, the carbon emission is reduced while the start-stop time of the conventional generator set is reasonably arranged, and the randomness and the intermittency of power generation of the new energy generator set are considered during day-ahead short-term scheduling; and the power generation capacity is reasonably distributed according to the demand of the power grid load.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid dispatching, and in particular to a distribution network dispatching method based on renewable energy output prediction data. Background Art

[0002] With the development of economy and technology, the carbon emission problem caused by the combustion of fossil fuels has become prominent. In order to deal with the carbon emission problem, the scale of renewable energy power generation in various countries is constantly expanding. However, compared with conventional energy, the output power of new energy such as wind power and photovoltaic power is random and volatile. The large-scale grid-connected power generation of new energy has brought new challenges to the dispatching, operation and control of the power grid.

[0003] After the introduction of new energy power generation solutions such as wind power and photovoltaic power, it is necessary to use relevant prediction models to predict the power generation and power generation of new energy generators in order to better dispatch the power grid on the day before. However, most of the existing prediction models only consider the impact of weather and environment on new energy generators, and do not consider the impact of factors such as mechanical wear of generators on their power generation, resulting in inaccurate prediction results. As a result, it is impossible to accurately allocate the power generation and start and stop time of each conventional generator when scheduling on the day before. On the basis of prediction, in order to reduce the impact of unstable power generation of new energy generators on the power grid, it is often combined with new energy and energy storage equipment to absorb or release electric energy and adjust the power of new energy grid-connected. However, due to the inaccurate prediction results of the power generation capacity of new energy generators, it is difficult to accurately dispatch energy storage equipment to absorb or supplement electric energy, which greatly affects the stability and efficient operation of the power grid. Summary of the invention

[0004] In order to solve the above technical problems, a distribution network scheduling method and system based on renewable energy output forecast data are provided. This technical solution solves the problem of inaccurate prediction of renewable energy power generation capacity and the resulting inability to accurately schedule energy storage equipment to absorb or supplement electric energy, which affects the stable and efficient operation of the power grid.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A distribution network dispatching method based on renewable energy output forecast data, specifically comprising:

[0007] Obtain regional historical electricity consumption data, regional historical weather data and regional tomorrow's weather forecast data for the area covered by the distribution network;

[0008] According to the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data with weather similar to tomorrow, and obtain the regional forecast electricity consumption data for tomorrow based on the query results;

[0009] Obtain historical power generation data of regional conventional power generation units and historical power generation data of regional new energy power generation units;

[0010] Use the historical power generation data of regional new energy generators and the historical weather data of the region to train and adjust the existing model to obtain a power generation prediction model for new energy generators;

[0011] According to the regional weather forecast data for tomorrow and the power generation prediction model of the new energy power generation units, the power generation data of each new energy power generation unit tomorrow is predicted, and the curve of power generation changing with time is drawn. The predicted daily power generation of each new energy power generation unit is obtained by integration;

[0012] The predicted daily power generation of each generator set is added together to obtain the predicted renewable energy power generation of the region tomorrow;

[0013] Formulate a day-ahead dispatch plan based on the regional forecasted electricity consumption data for tomorrow and the regional forecasted renewable energy generation data for tomorrow;

[0014] Get regional real-time weather data;

[0015] According to the real-time weather data of the region, the power generation prediction model of the new energy generator set is used to predict the power generation data of each new energy generator set in the short term, and a curve of power generation changing with time is drawn;

[0016] According to the latest forecast information from the power dispatching center, obtain the short-term load change trend of the power grid system;

[0017] Formulate a short-term daily dispatch plan based on the power generation change curve of each renewable energy generator set and the load change trend of the power grid system.

[0018] Preferably, the use of historical power generation data of regional new energy power generation units and historical weather data of the region to train and adjust the existing model to obtain a power generation prediction model of the new energy power generation units specifically includes:

[0019] Get the maintenance information of the generator set and sort it in time series as [T1,T2...T n ];

[0020] Select the time T from the historical power generation data and historical weather data of the new energy generator set n The data after that;

[0021] The selected historical weather data is input into the prediction model as a data set to obtain the historical prediction power generation data of each generator set;

[0022] According to the historical power generation data and historical predicted power generation data of each new energy power generation unit, the loss coefficient of each power generation unit is calculated based on the linear regression model;

[0023] The loss coefficient is added to the existing model to obtain the power generation prediction model of the new energy generator set.

[0024] Preferably, the step of formulating a day-ahead dispatching plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data specifically includes:

[0025] Divide a day into 24 segments, each lasting 1 hour;

[0026] According to the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data with weather similar to tomorrow, and obtain the regional forecast electricity consumption data for the period according to the query results;

[0027] According to the weather data of the period and the power generation prediction model of the new energy power generation unit, the power generation data of each new energy power generation unit in the period is predicted, the power generation of each power generation unit is obtained by integration, and the power generation of each power generation unit is added to obtain the total predicted power generation of new energy in the period;

[0028] Obtain daily power generation upper limit data and stable power generation data of each conventional generator set;

[0029] Obtain the power generation data of each conventional generator set at the beginning of the time period;

[0030] Determine the upper limit of the daily remaining power generation of each conventional power generation unit according to the upper limit data of the daily power generation of each conventional power generation unit and the power generation data of each conventional power generation unit;

[0031] According to the stable power data of each conventional generator set, the available power generation of each conventional generator set in this period is determined, and the smaller value between the upper limit of the daily remaining power generation and the available power generation in this period is taken as the first power generation upper limit of the conventional generator set;

[0032] Obtain historical pollution emission data of each conventional power generation unit;

[0033] Calculate the environmental protection coefficient of each conventional power generation unit according to the pollution emission historical data, wherein the environmental protection coefficient represents the average carbon emission per kilowatt-hour of electricity produced by the conventional power generation unit;

[0034] Obtain the daily carbon emission benchmark of the conventional power generation unit and the emissions of the conventional power generation unit, and determine the remaining emissions of the conventional power generation unit;

[0035] According to the remaining discharge amount of each conventional power generation unit and the environmental protection coefficient of each conventional power generation unit, a second upper limit of power generation of each conventional power generation unit is obtained;

[0036] If the second upper limit of power generation is higher than the first upper limit of power generation, the first upper limit of power generation is taken as the upper limit of power generation of the generator set; otherwise, the second upper limit of power generation is taken as the upper limit of power generation of the generator set;

[0037] Determine the predicted total power generation of conventional generators during this period based on the regional predicted power consumption data and the predicted total power generation data of new energy sources during this period;

[0038] Arrange the conventional generator sets from high to low according to the upper limit of power generation, and allocate the predicted total power generation of the conventional generator sets in the said period according to the priority of the arrangement;

[0039] Process other time periods according to the above steps to determine the allocation plan of conventional generators for each time period on the previous day;

[0040] The overall allocation plan for the day before is determined by comprehensively considering the allocation plans of conventional power generating units in each period of the day before.

[0041] Preferably, the allocation scheme of conventional power generation units in each period of the previous day is comprehensively determined to determine the overall allocation scheme of the previous day, which specifically includes:

[0042] According to the allocation plan of conventional generators in each period of the day before, determine the generators to be used for power generation in each period;

[0043] If the generator set is in operation at the beginning of the period, the generator set is classified as a high priority group for the period;

[0044] If a generator set is not in operation at the beginning of the period, the generator set is classified as a low priority group for the period;

[0045] Taking into account the high-priority group, low-priority group and power generation upper limit priority in each time period, the allocation plan of conventional power generation units in each time period is adjusted to determine the overall allocation plan for the day before.

[0046] Preferably, the formulation of a daily short-term dispatching plan based on the power generation change curve of each renewable energy power generation unit and the load change trend of the power grid system specifically includes:

[0047] According to the power generation change curve of each renewable energy generator set and the load change trend of the power grid system, determine whether the power generation change trend of each renewable energy generator set meets the load demand change trend of the power grid;

[0048] If the grid load demand is met, the electric energy from each renewable energy generator set will be fed into the grid;

[0049] If the grid load demand is not met, the specification information of each renewable energy generator set and each grid-connected inverter is obtained, and the upper and lower thresholds of the power output of each renewable energy generator set are obtained according to the specification information of each renewable energy generator set and each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected;

[0050] Determine the power output mode of each new energy power generation unit according to the power output upper threshold value and lower threshold value of each new energy power generation unit and the predicted power generation data of each new energy power generation unit;

[0051] The determined short-term power output mode of each new energy generating unit is sent to the control center, and the control center performs short-term power dispatch based on the information.

[0052] Preferably, the step of obtaining the upper and lower thresholds of the power output of each renewable energy generator set according to the specification information of each renewable energy generator set and each grid-connected inverter and the load of the power grid system to which each grid-connected inverter is connected specifically includes:

[0053] Determine the rated power of each grid-connected inverter according to the specification information of each grid-connected inverter;

[0054] The rated power of the grid-connected inverter is used as the upper threshold of the output power of the new energy generator set connected to it;

[0055] According to the specification information of each new energy generator set, the stable operating power of each new energy generator set is obtained;

[0056] According to the specification information of each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected, the minimum input power required by the grid-connected inverter to maintain matching with the grid voltage, frequency and phase is evaluated;

[0057] Compare the stable operating power of each new energy generator set and the minimum input power required for the grid-connected inverter connected to the new energy generator set to maintain voltage, frequency and phase matching with the grid, and take the larger one as the lower output power threshold of the new energy generator set.

[0058] Preferably, the method of determining the power output mode of the new energy power generation set according to the power output upper threshold value and the lower threshold value of the new energy power generation set and the predicted power generation data of the new energy power generation set specifically includes:

[0059] Obtain the predicted change trend of power grid load and draw it as a power grid load change curve;

[0060] According to the grid load change curve, obtain the lower threshold of the power output of the new energy unit;

[0061] Compare the predicted power generation of the new energy generator set with its power output upper threshold and lower threshold;

[0062] When the power generation of the new energy generator set is lower than the lower power output threshold, the electric energy of the generator set is input into the energy storage device connected to the generator set; when the power generation of the generator set is higher than the lower power output threshold, it is determined whether the power generation of the generator set is greater than the load of the power grid. If so, the part greater than the load is input into the energy storage device of the power grid. If not, the energy storage device or the conventional generator set is used to supplement the power of the new energy generator set.

[0063] When the power generation power of the new energy generator set is higher than the upper threshold value of the power output, the portion higher than the upper threshold value is input into the energy storage device directly connected to the generator set.

[0064] Preferably, the method of judging whether the power generation power of the generator set is greater than the load of the power grid, if so, inputting the part greater than the load into the energy storage device of the power grid, if not, using the energy storage device or the conventional generator set to supplement the power of the new energy generator set, specifically includes:

[0065] Energy storage devices that feed the portion of energy that is greater than the load into the grid include:

[0066] Obtain the load status of each energy storage device;

[0067] Sort the energy storage devices according to their distance from the new energy generator set from small to large, and record them as [e1,e2...e n ];

[0068] Calculate whether the remaining load of e1 is greater than the excess power of the renewable energy generators during this period. If so, dispatch the excess power to e1. ​​If not, remove e1 from the data set after the load of e1 is satisfied.

[0069] Repeat the previous step until the excess power is distributed;

[0070] Using energy storage equipment or conventional generators to supplement the power of new energy generators includes:

[0071] The energy storage device or conventional generator set that provides electricity is solved by taking the power generated by the selected energy storage device or conventional generator set meeting the power requirement as a constraint, and the energy storage of the selected energy storage device or the power generation of the conventional generator set not being less than the power requirement as an objective function;

[0072] The constraint condition that the power generation power of the selected energy storage device or conventional generator set meets the required power is:

[0073]

[0074] In the formula, P0 is the power generation of the new energy generator set, P n is the power generation capacity of the selected energy storage device or conventional generator set, and P is the grid load;

[0075] The objective function is:

[0076]

[0077] In the formula, E0 is the power generation of the new energy generator set, E n is the load of the selected energy storage device or the power generation of the conventional generator set, and E is the power required by the grid.

[0078] Furthermore, a distribution network dispatching system based on renewable energy output forecast data is proposed, which is used to implement a distribution network dispatching method based on renewable energy output forecast data as described above, and the system includes a data acquisition module, a day-ahead dispatching module, an intraday short-term dispatching module and a control center;

[0079] The data acquisition module interacts with the control center to acquire regional historical electricity consumption data, regional historical weather data, regional tomorrow's weather forecast data, regional conventional generator historical power generation data, regional new energy generator historical power generation data and regional power grid system load change data;

[0080] The day-ahead scheduling module is used to formulate a day-ahead scheduling plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data;

[0081] The intraday short-term dispatch module is used to formulate an intraday short-term dispatch plan according to the power generation change trend of each new energy generator set and the load change trend of the power grid system;

[0082] The control center is connected to the above modules to obtain real-time information to assist in real-time dispatching of the power grid.

[0083] Optionally, the day-ahead scheduling module includes a power consumption prediction unit, a new energy power generation prediction unit, and a scheduling unit;

[0084] The power consumption prediction unit is used to query the historical power consumption data with similar weather conditions to tomorrow based on the regional historical power consumption data and the regional historical weather data, and obtain the regional predicted power consumption data for tomorrow based on the query results;

[0085] The new energy power generation prediction unit is used to predict the regional new energy power generation data based on the historical power generation data of the regional new energy power generation units, the regional historical weather data and the regional tomorrow's weather forecast data;

[0086] The dispatching unit is used to formulate a day-ahead dispatching plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data.

[0087] Optionally, the intraday short-term scheduling module includes a first judgment unit, a threshold solving unit, a second judgment unit, and a scheduling unit;

[0088] The first judgment unit is used to judge whether the power generation change trend of each renewable energy generator set meets the load demand of the power grid according to the load change trend of the power grid system and the power generation change trend of each renewable energy generator set;

[0089] The threshold value solving unit is used to obtain the upper and lower threshold values ​​of the power output of each new energy generating set according to the specification information of each new energy generating set and each grid-connected inverter and the load of the power grid system to which each grid-connected inverter is connected;

[0090] The second judgment unit is used to judge the relationship between the upper and lower thresholds of the power output of the new energy generator set and the predicted power generation of the new energy generator set;

[0091] The dispatching unit determines the power dispatching mode of each new energy power generation group according to the judgment result of the second judgment unit.

[0092] Compared with the prior art, the present invention has the following beneficial effects:

[0093] The invention provides a distribution network dispatching method based on new energy output prediction data. When predicting the new energy power generation, the loss rate of each new energy power generation unit is taken into account, so as to improve the accuracy of the prediction model and ensure the accuracy of the prediction of the new energy power generation and power generation. When performing day-ahead dispatching, the power generation units are adjusted in time periods to avoid the reduction of resource utilization caused by ignoring the differences in different time periods during unified dispatching, the upper limit of power generation is adjusted by the environmental protection coefficient of each conventional power generation unit, and the power generation unit to be supplied is determined according to the upper limit of power generation of each power generation unit, so as to improve the power dispatching efficiency. When performing intraday dispatching, the upper and lower thresholds of output power are set, and the power output mode of the new energy power generation unit is determined according to the threshold division, so as to avoid affecting the normal operation of the equipment when the power generation is too high or failing to be stably connected to the grid when the power generation is too low, so as to avoid the waste of electric energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 A flow chart of a distribution network dispatching method based on renewable energy output prediction data according to an embodiment of the present invention;

[0095] Figure 2 A flow chart of a method for obtaining a power generation prediction model of a new energy generator set in a distribution network scheduling method based on new energy output prediction data according to an embodiment of the present invention;

[0096] Figure 3A flow chart of determining a day-ahead overall allocation plan in a distribution network dispatching method based on renewable energy output forecast data according to an embodiment of the present invention;

[0097] Figure 4 A flow chart of formulating a short-term dispatching plan within a day in a distribution network dispatching method based on renewable energy output forecast data according to an embodiment of the present invention;

[0098] Figure 5 The system block diagram of a distribution network dispatching system based on renewable energy output prediction data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0099] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0100] Reference Figure 1-4 As shown, an embodiment of the present invention provides a distribution network scheduling method based on renewable energy output prediction data, the method specifically comprising the following steps:

[0101] Use the historical power generation data of regional new energy generators and the historical weather data of the region to train and adjust the existing model to obtain a power generation prediction model for new energy generators;

[0102] Exemplarily, the specific method for training and adjusting the existing model is:

[0103] Get the maintenance information of the generator set and sort it in time series as [T1,T2...T n ];

[0104] Select the time T from the historical power generation data and historical weather data of the new energy generator set n The data after that;

[0105] The selected historical weather data is input into the prediction model as a data set to obtain the historical prediction power generation data of each generator set;

[0106] According to the historical power generation data and historical predicted power generation data of each new energy power generation unit, the loss coefficient of each power generation unit is calculated based on the linear regression model;

[0107] The loss coefficient is added to the existing model to obtain the power generation prediction model of the new energy generator set.

[0108] In this embodiment, according to the historical power generation data and historical predicted power generation data of each new energy power generation group, based on the linear regression model, the loss coefficient of each power generation group is obtained, and then the loss coefficient is added to the existing model to obtain the power generation prediction model of the new energy power generation group, which can effectively improve the prediction accuracy of the prediction model for the power generation of each new energy power generation group;

[0109] In this embodiment, the specific method for obtaining the loss coefficient is: constructing a function of the historical predicted power generation, the loss coefficient and the corresponding historical power generation, and using the least squares method to find the best function match between the historical predicted power generation data and the corresponding historical power generation data, that is, obtaining the value of the loss coefficient;

[0110] The function of the predicted power generation, loss coefficient and corresponding historical power generation is expressed as:

[0111] P = P0(1-λ);

[0112] Where P0 is the historical predicted power generation, λ is the loss coefficient, and P is the corresponding historical power generation.

[0113] Divide a day into 24 segments, each lasting 1 hour;

[0114] According to the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data with weather similar to tomorrow, and obtain the regional forecast electricity consumption data for the period according to the query results;

[0115] Exemplarily, a method for obtaining regional tomorrow's predicted electricity consumption data is:

[0116] Obtain the historical electricity consumption data with similar weather conditions to tomorrow, and take the average of these historical electricity consumption data as the predicted electricity consumption data for tomorrow;

[0117] The weather data of the period is input into the power generation prediction model of the new energy power generation unit, the power generation data of each new energy power generation unit in the period is predicted, the power generation of each power generation unit is obtained by integration, and the power generation of each power generation unit is added to obtain the predicted total power generation of new energy in the period;

[0118] Obtain daily power generation upper limit data and stable power generation data of each conventional generator set;

[0119] Obtain the power generation data of each conventional generator set at the beginning of the time period;

[0120] Determine the upper limit of the daily remaining power generation of each conventional power generation unit according to the upper limit data of the daily power generation of each conventional power generation unit and the power generation data of each conventional power generation unit;

[0121] According to the stable power data of each conventional generator set, the available power generation of each conventional generator set in this period is determined, and the smaller value between the upper limit of the daily remaining power generation and the available power generation in this period is taken as the first power generation upper limit of the conventional generator set;

[0122] Obtain historical pollution emission data of each conventional power generation unit;

[0123] Calculate the environmental protection coefficient of each conventional power generation unit according to the pollution emission historical data, wherein the environmental protection coefficient represents the average carbon emission per kilowatt-hour of electricity produced by the conventional power generation unit;

[0124] Obtain the daily carbon emission benchmark of the conventional power generation unit and the emissions of the conventional power generation unit, and determine the remaining emissions of the conventional power generation unit;

[0125] According to the remaining discharge amount of each conventional power generation unit and the environmental protection coefficient of each conventional power generation unit, a second upper limit of power generation of each conventional power generation unit is obtained;

[0126] If the second upper limit of power generation is higher than the first upper limit of power generation, the first upper limit of power generation is taken as the upper limit of power generation of the generator set; otherwise, the second upper limit of power generation is taken as the upper limit of power generation of the generator set;

[0127] Determine the predicted total power generation of conventional generators during this period based on the regional predicted power consumption data and the predicted total power generation data of new energy sources during this period;

[0128] Arrange the conventional generator sets from high to low according to their upper limits of power generation as the power supply priority of each conventional generator set;

[0129] Get the start and stop status of each conventional generator set;

[0130] If the generator set is in operation at the beginning of the period, the generator set is classified as a high priority group for the period;

[0131] If a generator set is not in operation at the beginning of the period, the generator set is classified as a low priority group for the period;

[0132] Considering the high priority group, low priority group and upper limit priority of power generation in this period, the conventional power generation groups in this period are allocated;

[0133] Process other time periods according to the above steps to determine the allocation plan of conventional generators for each time period on the previous day;

[0134] The overall allocation plan for the day before is determined by comprehensively considering the allocation plans of conventional power generating units in each period of the day before.

[0135] In this embodiment, the second upper limit of power generation of each conventional generator set is determined based on the remaining emission capacity of each conventional generator set and the environmental protection coefficient of each conventional generator set. When allocating conventional generator sets, the impact of the carbon emission capacity of the conventional generator sets on the environment is taken into consideration. Under the same circumstances, conventional generator sets with lower carbon emissions are selected, which is conducive to achieving the goal of carbon emission reduction. When allocating conventional generator sets, priority is given to generator sets that have been started, which can effectively reduce the cost of starting and stopping the generator sets.

[0136] It should be noted that the daily carbon emissions benchmark of conventional power generation units is affected by technological progress and policy changes and is not a fixed value. In addition, since carbon trading can be carried out, under special circumstances, the daily carbon emissions of conventional power generation units may exceed their preset standards.

[0137] On the second day, based on the real-time weather data of the region, the power generation prediction model of the new energy generator set is used to predict the power generation data of each new energy generator set in the short term, and a curve of power generation changing over time is drawn;

[0138] According to the latest forecast information from the power dispatching center, obtain the short-term load change trend of the power grid system;

[0139] According to the power generation change curve of each renewable energy generator set and the load change trend of the power grid system, determine whether the power generation change trend of each renewable energy generator set meets the load demand change trend of the power grid;

[0140] If the grid load demand is met, the electric energy from each renewable energy generator set will be fed into the grid;

[0141] If the grid load demand is not met, the specification information of each renewable energy generator set and each grid-connected inverter is obtained, and the upper and lower thresholds of the power output of each renewable energy generator set are obtained according to the specification information of each renewable energy generator set and each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected;

[0142] Determine the power output mode of each new energy power generation unit according to the power output upper threshold value and lower threshold value of each new energy power generation unit and the predicted power generation data of each new energy power generation unit;

[0143] The determined short-term power output mode of each new energy generating unit is sent to the control center, and the control center performs short-term power dispatch based on the information.

[0144] It should be noted that the standard for judging whether the power generation change trend of each new energy power generation group meets the power grid load demand change trend is that the overlap rate between the power generation change curve of the power generation group and the power grid load demand change curve is above 90%.

[0145] Exemplarily, the specific method for obtaining the upper and lower thresholds of the power output of each new energy generator set is:

[0146] Determine the rated power of each grid-connected inverter according to the specification information of each grid-connected inverter;

[0147] The rated power of the grid-connected inverter is used as the upper threshold of the output power of the new energy generator set connected to it;

[0148] According to the specification information of each new energy generator set, the stable operating power of each new energy generator set is obtained;

[0149] According to the specification information of each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected, the minimum input power required by the grid-connected inverter to maintain matching with the grid voltage, frequency and phase is evaluated;

[0150] Compare the stable operating power of each new energy generator set and the minimum input power required for the grid-connected inverter connected to the new energy generator set to maintain voltage, frequency and phase matching with the grid, and take the larger one as the lower output power threshold of the new energy generator set.

[0151] In this embodiment, the rated power of each grid-connected inverter is determined according to the specification information of each grid-connected inverter, and the rated power of the grid-connected inverter is used as the upper threshold value of the output power of the new energy generator set connected thereto. The upper threshold value of the output power is set in consideration of the specifications of the grid-connected inverter to prevent excessive output power from affecting the normal operation of the grid-connected inverter. At the same time, the stable operating power of each new energy generator set and the minimum input power required for the grid-connected inverter connected to the new energy generator set to maintain matching with the grid voltage, frequency and phase are compared, and the larger one is taken as the lower threshold value of the output power of the new energy generator set. The lower threshold value of the output power set by this scheme can ensure that the electric energy generated by the generator set will not be wasted due to insufficient power generation when connected to the grid, and the electric energy between the upper threshold value and the lower threshold value of the output power can be safely and stably input into the grid.

[0152] Exemplarily, the specific method for determining the power output mode of each new energy generator set is:

[0153] Obtain the predicted change trend of power grid load and draw it as a power grid load change curve;

[0154] According to the grid load change curve, obtain the lower threshold of the power output of the new energy unit;

[0155] Compare the predicted power generation of the new energy generator set with its power output upper threshold and lower threshold;

[0156] When the power generation of the new energy generator set is lower than the lower power output threshold, the electric energy of the generator set is input into the energy storage device connected to the generator set; when the power generation of the generator set is higher than the lower power output threshold, it is determined whether the power generation of the generator set is greater than the load of the power grid. If so, the part greater than the load is input into the energy storage device of the power grid. If not, the energy storage device or the conventional generator set is used to supplement the power of the new energy generator set.

[0157] When the power generation power of the new energy generator set is higher than the upper threshold value of the power output, the portion higher than the upper threshold value is input into the energy storage device directly connected to the generator set.

[0158] In this embodiment, when the power generation of the new energy generator set is higher than the upper threshold value of the power output, that is, the power generation is higher than the rated power of the grid-connected inverter, the grid-connected inverter connected to the generator set may be damaged. Therefore, the electric energy higher than the upper threshold value is input into the energy storage device directly connected to the generator set. When the power generation of the new energy generator set is lower than the lower threshold value of the power output, the generator set cannot operate stably, and the power of the generator set cannot support stable grid connection, resulting in the generated electric energy being unable to be input into the power grid and being wasted. Therefore, the electric energy lower than the lower threshold value is input into the energy storage device directly connected to the generator set.

[0159] Exemplarily, the specific method of inputting the portion greater than the load into the energy storage device of the power grid is:

[0160] Obtain the load status of each energy storage device;

[0161] Sort the energy storage devices according to their distance from the new energy generator set from small to large, and record them as [e1,e2...e n ];

[0162] Calculate whether the remaining load of e1 is greater than the excess power of the renewable energy generators during this period. If so, dispatch the excess power to e1. ​​If not, remove e1 from the data set after the load of e1 is satisfied.

[0163] Repeat the previous step until the excess power is distributed.

[0164] It is understandable that the cost of power transmission should also be considered when selecting energy storage equipment. If the selected energy storage equipment is far away from the generator set, resulting in large transmission losses and high costs, the excess electricity can be absorbed by encouraging areas near the generator set to increase power consumption.

[0165] Exemplarily, the specific method of using energy storage equipment or conventional generator sets to supplement the power of the new energy generator set is:

[0166] The energy storage device or conventional generator set that provides electricity is solved by taking the power generated by the selected energy storage device or conventional generator set meeting the power requirement as a constraint, and the energy storage of the selected energy storage device or the power generation of the conventional generator set not being less than the power requirement as an objective function;

[0167] The constraint condition that the power generation power of the selected energy storage device or conventional generator set meets the required power is:

[0168]

[0169] In the formula, P0 is the power generation of the new energy generator set, P n is the power generation capacity of the selected energy storage device or conventional generator set, and P is the grid load;

[0170] The objective function is:

[0171]

[0172] In the formula, E0 is the power generation of the new energy generator set, E n is the load of the selected energy storage device or the power generation of the conventional generator set, and E is the power required by the grid.

[0173] In this embodiment, the objective function will solve multiple solutions, and the power dispatching center can select the solution with the minimum transmission loss and power generation cost as the optimal solution based on the transmission loss of each energy storage device and the conventional generator set and the power generation cost of the conventional generator set;

[0174] It is understandable that when selecting power supply equipment, there may be a situation where a single power supply equipment cannot meet the power demand. At this time, you should consider using multiple energy storage devices or conventional generators to supplement the power. When selecting a conventional generator, you should also consider the carbon emissions of the generator.

[0175] Reference Figure 5 As shown, an embodiment of the present invention further provides a distribution network dispatching system based on renewable energy output forecast data, wherein the distribution network dispatching system based on renewable energy output forecast data adopts the distribution network dispatching method based on renewable energy output forecast data to distribute and dispatch electric energy, and the distribution network dispatching system based on renewable energy output forecast data includes a data acquisition module, a day-ahead dispatching module, an intraday short-term dispatching module and a control center;

[0176] The data acquisition module interacts with the control center to acquire regional historical electricity consumption data, regional historical weather data, regional tomorrow's weather forecast data, regional conventional generator historical power generation data, regional new energy generator historical power generation data and regional power grid system load change data;

[0177] The day-ahead scheduling module is used to formulate a day-ahead scheduling plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data;

[0178] The intraday short-term dispatch module is used to formulate an intraday short-term dispatch plan according to the power generation change trend of each new energy generator set and the load change trend of the power grid system;

[0179] The control center is connected to the above modules to obtain real-time information to assist in real-time dispatching of the power grid.

[0180] The day-ahead dispatch module includes a power consumption forecasting unit, a new energy power generation forecasting unit, and a dispatching unit;

[0181] The power consumption prediction unit is used to query the historical power consumption data with similar weather conditions to tomorrow based on the regional historical power consumption data and the regional historical weather data, and obtain the regional predicted power consumption data for tomorrow based on the query results;

[0182] The new energy power generation prediction unit is used to predict the regional new energy power generation data based on the historical power generation data of the regional new energy power generation units, the regional historical weather data and the regional tomorrow's weather forecast data;

[0183] The dispatching unit is used to formulate a day-ahead dispatching plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data.

[0184] The intraday short-term scheduling module includes a first judgment unit, a threshold solving unit, a second judgment unit, and a scheduling unit;

[0185] The first judgment unit is used to judge whether the power generation change trend of each renewable energy generator set meets the load demand of the power grid according to the load change trend of the power grid system and the power generation change trend of each renewable energy generator set;

[0186] The threshold value solving unit is used to obtain the upper and lower threshold values ​​of the power output of each new energy generating set according to the specification information of each new energy generating set and each grid-connected inverter and the load of the power grid system to which each grid-connected inverter is connected;

[0187] The second judgment unit is used to judge the relationship between the upper and lower thresholds of the power output of the new energy generator set and the predicted power generation of the new energy generator set;

[0188] The dispatching unit determines the power dispatching mode of each new energy power generation group according to the judgment result of the second judgment unit.

[0189] In summary, the advantages of the present invention are: when predicting the power generation of renewable energy, the loss rate of each renewable energy generator set is taken into account, the accuracy of the prediction model is improved, and the accuracy of the prediction of renewable energy power generation and power generation is ensured; when performing day-ahead scheduling, the generator sets are adjusted in time periods to avoid the reduction in resource utilization caused by ignoring the differences in different time periods during unified scheduling, the upper limit of power generation is adjusted by the environmental protection coefficient of each conventional generator set, and the generator set to be supplied is determined according to the upper limit of power generation of each generator set, thereby improving the power scheduling efficiency; when performing intraday scheduling, the upper and lower thresholds of the output power are set, and the power output mode of the renewable energy generator set is determined according to the threshold division, so as to avoid affecting the normal operation of the equipment when the power generation power is too high or failing to be stably connected to the grid when the power generation power is too low, resulting in waste of electric energy.

[0190] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A distribution network dispatching method based on renewable energy output forecast data, characterized in that: include: Obtain regional historical electricity consumption data, regional historical weather data and regional tomorrow's weather forecast data for the area covered by the distribution network; According to the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data with weather similar to tomorrow, and obtain the regional forecast electricity consumption data for tomorrow based on the query results; Obtain historical power generation data of regional conventional power generation units and historical power generation data of regional new energy power generation units; Use the historical power generation data of regional new energy generators and the historical weather data of the region to train and adjust the existing model to obtain a power generation prediction model for new energy generators; According to the regional weather forecast data for tomorrow and the power generation prediction model of the new energy power generation units, the power generation data of each new energy power generation unit tomorrow is predicted, and the curve of power generation changing with time is drawn. The predicted daily power generation of each new energy power generation unit is obtained by integration; The predicted daily power generation of each generator set is added together to obtain the predicted renewable energy power generation of the region tomorrow; Formulate a day-ahead dispatch plan based on the regional electricity consumption data and the regional renewable energy power generation data for tomorrow; Get regional real-time weather data; According to the real-time weather data of the region, the power generation prediction model of the new energy generator set is used to predict the power generation data of each new energy generator set in the short term, and a curve of power generation changing with time is drawn; According to the latest forecast information from the power dispatching center, obtain the short-term load change trend of the power grid system; Formulate a short-term daily dispatch plan based on the power generation change curve of each renewable energy generator set and the load change trend of the power grid system.

2. A distribution network dispatching method based on renewable energy output forecast data according to claim 1, characterized in that: The method of using the historical power generation data of the regional new energy power generation unit and the historical weather data of the regional new energy power generation unit to train and adjust the existing model to obtain the power generation prediction model of the new energy power generation unit specifically includes: Get the maintenance information of the generator set and sort it in time series as [T1,T2...T n ]; Select the time T from the historical power generation data and historical weather data of the new energy generator set n The data after that; The selected historical weather data is input into the prediction model as a data set to obtain the historical prediction power generation data of each generator set; According to the historical power generation data and historical predicted power generation data of each new energy power generation unit, the loss coefficient of each power generation unit is calculated based on the linear regression model; The loss coefficient is added to the existing model to obtain the power generation prediction model of the new energy generator set.

3. A distribution network dispatching method based on renewable energy output forecast data according to claim 1, characterized in that: The day-ahead dispatching plan is formulated based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data, specifically including: Divide a day into 24 segments, each lasting 1 hour; According to the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data with weather similar to tomorrow, and obtain the regional forecast electricity consumption data for the period according to the query results; According to the weather data of the period and the power generation prediction model of the new energy power generation unit, the power generation data of each new energy power generation unit in the period is predicted, the power generation of each power generation unit is obtained by integration, and the power generation of each power generation unit is added to obtain the total predicted power generation of new energy in the period; Obtain daily power generation upper limit data and stable power generation data of each conventional generator set; Obtain the power generation data of each conventional generator set at the beginning of the time period; Determine the upper limit of the daily remaining power generation of each conventional power generation unit according to the upper limit data of the daily power generation of each conventional power generation unit and the power generation data of each conventional power generation unit; According to the stable power data of each conventional generator set, the available power generation of each conventional generator set in this period is determined, and the smaller value between the upper limit of the daily remaining power generation and the available power generation in this period is taken as the first power generation upper limit of the conventional generator set; Obtain historical pollution emission data of each conventional power generation unit; Calculate the environmental protection coefficient of each conventional power generation unit according to the pollution emission historical data, wherein the environmental protection coefficient represents the average carbon emission per kilowatt-hour of electricity produced by the conventional power generation unit; Obtain the daily carbon emission benchmark of the conventional power generation unit and the emissions of the conventional power generation unit, and determine the remaining emissions of the conventional power generation unit; According to the remaining discharge amount of each conventional power generation unit and the environmental protection coefficient of each conventional power generation unit, a second upper limit of power generation of each conventional power generation unit is obtained; If the second upper limit of power generation is higher than the first upper limit of power generation, the first upper limit of power generation is taken as the upper limit of power generation of the generator set; otherwise, the second upper limit of power generation is taken as the upper limit of power generation of the generator set; Determine the predicted total power generation of conventional generators during this period based on the regional predicted power consumption data and the predicted total power generation data of new energy sources during this period; Arrange the conventional generator sets from high to low according to the upper limit of power generation, and allocate the predicted total power generation of the conventional generator sets in the said period according to the priority of the arrangement; Process other time periods according to the above steps to determine the allocation plan of conventional generators for each time period on the previous day; The overall allocation plan for the day before is determined by comprehensively considering the allocation plans of conventional power generating units in each period of the day before.

4. A distribution network dispatching method based on renewable energy output forecast data according to claim 3, characterized in that: The allocation plan of conventional power generation units in each period of the previous day is comprehensively determined to determine the overall allocation plan of the previous day, specifically including: According to the allocation plan of conventional generators in each period of the day before, determine the generators to be used for power generation in each period; If the generator set is in operation at the beginning of the period, the generator set is classified as a high priority group for the period; If a generator set is not in operation at the beginning of the period, the generator set is classified as a low priority group for the period; Taking into account the high-priority group, low-priority group and power generation upper limit priority in each time period, the allocation plan of conventional power generation units in each time period is adjusted to determine the overall allocation plan for the day before.

5. A distribution network dispatching method based on renewable energy output forecast data according to claim 1, characterized in that: According to the power generation change curve of each renewable energy generator set and the load change trend of the power grid system, a short-term dispatching plan is formulated within the day, specifically including: According to the power generation change curve of each renewable energy generator set and the load change trend of the power grid system, determine whether the power generation change trend of each renewable energy generator set meets the load demand change trend of the power grid; If the grid load demand is met, the electric energy from each renewable energy generator set will be fed into the grid; If the grid load demand is not met, the specification information of each renewable energy generator set and each grid-connected inverter is obtained, and the upper and lower thresholds of the power output of each renewable energy generator set are obtained according to the specification information of each renewable energy generator set and each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected; Determine the power output mode of each new energy power generation unit according to the power output upper threshold value and lower threshold value of each new energy power generation unit and the predicted power generation data of each new energy power generation unit; The determined short-term power output mode of each new energy generating unit is sent to the control center, and the control center performs short-term power dispatch based on the information.

6. A distribution network dispatching method based on renewable energy output forecast data according to claim 5, characterized in that: The step of obtaining the upper and lower thresholds of the power output of each renewable energy generator set according to the specification information of each renewable energy generator set and each grid-connected inverter and the load of the power grid system to which each grid-connected inverter is connected specifically includes: Determine the rated power of each grid-connected inverter according to the specification information of each grid-connected inverter; The rated power of the grid-connected inverter is used as the upper threshold of the output power of the new energy generator set connected to it; According to the specification information of each new energy generator set, the stable operating power of each new energy generator set is obtained; According to the specification information of each grid-connected inverter and the load of the grid system to which each grid-connected inverter is connected, the minimum input power required by the grid-connected inverter to maintain matching with the grid voltage, frequency and phase is evaluated; Compare the stable operating power of each new energy generator set and the minimum input power required for the grid-connected inverter connected to the new energy generator set to maintain voltage, frequency and phase matching with the grid, and take the larger one as the lower output power threshold of the new energy generator set.

7. A distribution network dispatching method based on renewable energy output forecast data according to claim 5, characterized in that: The method of determining the power output mode of each new energy power generation group according to the power output upper threshold value and lower threshold value of each new energy power generation group and the predicted power generation data of each new energy power generation group specifically includes: Obtain the predicted change trend of power grid load and draw it as a power grid load change curve; According to the grid load change curve, obtain the lower threshold of the power output of the new energy unit; Compare the predicted power generation of the new energy generator set with its power output upper threshold and lower threshold; When the power generation of the new energy generator set is lower than the lower power output threshold, the electric energy of the generator set is input into the energy storage device connected to the generator set; when the power generation of the generator set is higher than the lower power output threshold, it is determined whether the power generation of the generator set is greater than the load of the power grid. If so, the part greater than the load is input into the energy storage device of the power grid. If not, the energy storage device or the conventional generator set is used to supplement the power of the new energy generator set. When the power generation power of the new energy generator set is higher than the upper threshold value of the power output, the portion higher than the upper threshold value is input into the energy storage device directly connected to the generator set.

8. A distribution network dispatching method based on renewable energy output forecast data according to claim 7, characterized in that: The method of judging whether the power generation of the generator set is greater than the load of the power grid, if so, inputting the part greater than the load into the energy storage device of the power grid, if not, using the energy storage device or the conventional generator set to supplement the power of the new energy generator set, specifically includes: Energy storage devices that feed the portion of energy that is greater than the load into the grid include: Obtain the load status of each energy storage device; Sort the energy storage devices according to their distance from the new energy generator set from small to large, and record them as [e1,e2...e n ]; Calculate whether the remaining load of e1 is greater than the excess power of the renewable energy generators during this period. If so, dispatch the excess power to e1. ​​If not, remove e1 from the data set after the load of e1 is satisfied. Repeat the previous step until the excess power is distributed; Using energy storage equipment or conventional generators to supplement the power of new energy generators includes: The energy storage device or conventional generator set that provides electricity is solved by taking the power generated by the selected energy storage device or conventional generator set meeting the power requirement as a constraint, and the energy storage of the selected energy storage device or the power generation of the conventional generator set not being less than the power requirement as an objective function; The constraint condition that the power generation power of the selected energy storage device or conventional generator set meets the required power is: In the formula, P0 is the power generation of the new energy generator set, P n is the power generation capacity of the selected energy storage device or conventional generator set, and P is the grid load; The objective function is: In the formula, E0 is the power generation of the new energy generator set, E n is the load of the selected energy storage device or the power generation of the conventional generator set, and E is the power required by the grid.

9. A distribution network dispatching system based on renewable energy output forecast data, characterized in that: It includes data acquisition module, day-ahead scheduling module, intraday short-term scheduling module and control center; The data acquisition module interacts with the control center to acquire regional historical electricity consumption data, regional historical weather data, regional tomorrow's weather forecast data, regional conventional generator historical power generation data, regional new energy generator historical power generation data and regional power grid system load change data; The day-ahead scheduling module is used to formulate a day-ahead scheduling plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data; The intraday short-term dispatch module is used to formulate an intraday short-term dispatch plan according to the power generation change trend of each new energy generator set and the load change trend of the power grid system; The control center is connected to the above modules to obtain real-time information to assist in real-time dispatching of the power grid.

10. A distribution network dispatching system based on renewable energy output forecast data according to claim 9, characterized in that: The day-ahead scheduling module includes a power consumption prediction unit, a new energy power generation prediction unit, and a scheduling unit; The power consumption prediction unit is used to query the historical power consumption data with similar weather conditions to tomorrow based on the regional historical power consumption data and the regional historical weather data, and obtain the regional predicted power consumption data for tomorrow based on the query results; The new energy power generation prediction unit is used to predict the regional new energy power generation data based on the historical power generation data of the regional new energy power generation units, the regional historical weather data and the regional tomorrow's weather forecast data; The dispatching unit is used to formulate a day-ahead dispatching plan based on the regional tomorrow's predicted electricity consumption data and the regional tomorrow's predicted new energy power generation data; The intraday short-term scheduling module includes a first judgment unit, a threshold solving unit, a second judgment unit, and a scheduling unit; The first judgment unit is used to judge whether the power generation change trend of each renewable energy generator set meets the load demand of the power grid according to the load change trend of the power grid system and the power generation change trend of each renewable energy generator set; The threshold value solving unit is used to obtain the upper and lower threshold values ​​of the power output of each new energy generating set according to the specification information of each new energy generating set and each grid-connected inverter and the load of the power grid system to which each grid-connected inverter is connected; The second judgment unit is used to judge the relationship between the upper and lower thresholds of the power output of the new energy generator set and the predicted power generation of the new energy generator set; The dispatching unit determines the power dispatching mode of each new energy power generation group according to the judgment result of the second judgment unit.

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