A distribution network scheduling method and system based on renewable energy output forecast data

Abstract

The application discloses a power distribution network scheduling method and system based on new energy output prediction data, relates to the technical field of power grid scheduling, and comprises the following steps: formulating a day-ahead scheduling plan according to regional predicted power consumption data and regional predicted new energy power generation data; predicting the power generation power change trend of each new energy generator set in a short term according to regional real-time weather data; acquiring the power grid system load change trend in a short term; and formulating an intra-day short-term scheduling plan according to the power generation power change trend of each new energy generator set and the power grid system load change trend. When the day-ahead scheduling is performed, the power cleaning degree, start-stop cost and other factors of the conventional generator set are considered, the start-stop time of the conventional generator set is reasonably arranged, and the carbon emission amount is reduced, and when the intra-day short-term scheduling is performed, the randomness and intermittence of the new energy generator set power generation are considered, and the power generation capacity of the new energy generator set is reasonably distributed according to the power grid load demand.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid dispatching, in particular to a power distribution network dispatching method based on new energy output prediction data. BACKGROUND

[0002] With the development of economy and technology, the problem of carbon emissions caused by the combustion of fossil fuels is prominent. In order to cope with the problem of carbon emissions, the scale of renewable energy power generation in various countries is continuously expanding, but compared with conventional energy, the output power of new energy such as wind power and photovoltaic power has the characteristics of randomness and volatility. Large-scale grid-connected power generation of new energy brings new challenges to power grid dispatching operation and control.

[0003] After introducing new energy power generation schemes such as wind power and photovoltaic power, relevant prediction models need to be used to predict the power generation and power generation of new energy generating units, so as to better carry out day-ahead dispatching of power grid. However, the existing prediction models only consider the influence of weather and environment on new energy generating units, and do not consider the influence of mechanical wear and tear of generating units on their power generation, resulting in inaccurate prediction results, which leads to inaccurate allocation of power generation and start-stop time of each conventional generating unit during day-ahead dispatching. On the basis of prediction, in order to reduce the influence of unstable power generation of new energy generating units on power grid, the combination of new energy and energy storage devices is often used to absorb or release electric energy, and to adjust the power of new energy grid-connected. However, due to the inaccurate prediction results of power generation capacity of new energy generating units, it is difficult to accurately dispatch energy storage devices to absorb or supplement electric energy, which greatly affects the stability and efficient work of power grid. SUMMARY

[0004] To solve the above technical problems, a power distribution network dispatching method and system based on new energy output prediction data are provided. The technical solution solves the problem of inaccurate prediction of new energy power generation capacity and the problem of inaccurate dispatching of energy storage devices to absorb or supplement electric energy, which affects the stable and efficient work of power grid.

[0005] To achieve the above purpose, the technical solution adopted by the present application is as follows:

[0006] A power distribution network dispatching method based on new energy output prediction data, specifically comprising:

[0007] Obtain regional historical power consumption data, regional historical weather data and regional tomorrow weather forecast data of the power distribution network coverage area;

[0008] According to the regional historical power consumption data and the regional historical weather data, query the historical power consumption data of similar weather of tomorrow, and obtain the regional tomorrow predicted power consumption data according to the query result;

[0009] Obtain the historical power generation data of the regional conventional generator set and the historical power generation data of the regional new energy generator set;

[0010] Train and adjust the existing model using the historical power generation data of the regional new energy generator set and the historical weather data of the region, and obtain a new energy generator set power generation power prediction model;

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

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

[0013] According to the regional tomorrow predicted power consumption data and the regional tomorrow predicted new energy power generation data, a day-ahead dispatching plan is made;

[0014] Obtain the real-time weather data of the region;

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

[0016] According to the latest prediction message of the power dispatching center, the load change trend of the power grid system in the short term is obtained;

[0017] According to the power generation power change curve of each new energy generator set and the load change trend of the power grid system, a short-term dispatching plan in the day is made.

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

[0019] Obtain the maintenance information of the generator set, and sort it according to the time sequence as [T1, T2...T n ];

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

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

[0022] According to the historical power generation data and the historical predicted power generation data of each new energy generator set, the loss coefficient of each generator set is obtained based on a linear regression model.

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

[0024] Preferably, the day-ahead scheduling plan is formulated according to the regional tomorrow predicted power consumption data and the regional tomorrow predicted new energy power generation data, and specifically includes:

[0025] The time of a day is divided into 24 segments, each segment being 1 hour;

[0026] According to the regional historical power consumption data and the regional historical weather data, the historical power consumption data of similar weather of tomorrow is queried, and the regional predicted power consumption data of the segment is obtained according to the query result;

[0027] According to the weather data of the segment and the new energy generator set power generation prediction model, the power generation data of each new energy generator set in the segment is predicted, the power generation of each generator set is integrated to obtain the total power generation of each generator set, and the total power generation of each generator set is added to obtain the total predicted power generation of the segment;

[0028] The upper limit data of the daily power generation of each conventional generator set and the stable power generation data are obtained;

[0029] The power generation data of each conventional generator set at the beginning of the segment is obtained;

[0030] According to the upper limit data of the daily power generation of each conventional generator set and the power generation data of each conventional generator set, the upper limit of the remaining daily power generation of each conventional generator set is determined;

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

[0032] The pollution emission historical data of each conventional generator set is obtained;

[0033] The environmental protection coefficient of each conventional generator set is calculated according to the pollution emission historical data, and the environmental protection coefficient represents the average carbon emission per unit of electricity generated by the conventional generator set;

[0034] The daily carbon emission amount of the conventional generator set is obtained, and the remaining emission amount of the conventional generator set is determined according to the daily carbon emission amount of the conventional generator set and the emission amount of the conventional generator set;

[0035] The second power generation upper limit of each conventional generator set is obtained according to the remaining emission amount of each conventional generator set and the environmental protection coefficient of each conventional generator set;

[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] The power generation of the conventional generator set in the period is determined according to the period area power consumption data and the new energy predicted total power generation data;

[0038] The conventional generator sets are arranged in descending order according to the upper limit of power generation, and the predicted total power generation of the conventional generator set in the period is distributed according to the arrangement priority;

[0039] The distribution scheme of the conventional generator set in each period is determined by processing other periods according to the above steps;

[0040] The overall distribution scheme is determined by comprehensively determining the distribution scheme of the conventional generator set in each period.

[0041] Preferably, the overall distribution scheme is determined by comprehensively determining the distribution scheme of the conventional generator set in each period, and specifically includes:

[0042] The generator set generating power in each period is determined according to the distribution scheme of the conventional generator set 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 in the period;

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

[0045] The distribution scheme of the conventional generator set in each period is adjusted considering the high priority group, the low priority group and the upper limit of power generation priority in each period, and the overall distribution scheme is determined.

[0046] Preferably, the short-term scheduling plan is formulated according to the power generation power curve of each new energy generator set and the load change trend of the power grid system, and specifically includes:

[0047] The power generation power change trend of each new energy generator set is determined according to the power generation power curve of each new energy generator set and the load change trend of the power grid system;

[0048] If the power grid load demand is met, the electric energy of each new energy generator set is input into the power grid;

[0049] If the grid load demand is not met, the specifications of each new energy generator set and each grid-connected inverter are obtained, and the upper threshold and lower threshold of the power output of each new energy generator set are determined according to the specifications of each new energy generator set and each grid-connected inverter and the load of the grid system connected by each grid-connected inverter.

[0050] The power output mode of each new energy generator set is determined according to the upper threshold and lower threshold of the power output of each new energy generator set and the predicted power generation data of each new energy generator set.

[0051] The determined short-term power output mode of each new energy generator set is sent to the control center, and the control center performs short-term power dispatching according to the information.

[0052] Preferably, the upper threshold and lower threshold of the power output of each new energy generator set are determined according to the specifications of each new energy generator set and each grid-connected inverter and the load of the grid system connected by each grid-connected inverter, specifically including:

[0053] The rated power of each grid-connected inverter is determined according to the specifications of each grid-connected inverter.

[0054] The rated power of the grid-connected inverter is taken as the upper threshold of the output power of the new energy generator set connected thereto.

[0055] The stable operation power of each new energy generator set is obtained according to the specifications of each new energy generator set.

[0056] The minimum input power required for the grid-connected inverter to maintain matching with the grid voltage, frequency and phase is evaluated according to the specifications of each grid-connected inverter and the load of the grid system connected by each grid-connected inverter.

[0057] The stable operation power of each new energy generator set and the minimum input power required for the grid-connected inverter connected thereto to maintain matching with the grid voltage, frequency and phase are compared, and the larger one is taken as the lower threshold of the output power of the new energy generator set.

[0058] Preferably, the power output mode of the new energy generator set is determined according to the upper threshold and lower threshold of the power output of the new energy generator set and the predicted power generation data of the new energy generator set, specifically including:

[0059] The grid load prediction trend is obtained and plotted as a grid load change curve.

[0060] The lower threshold of the new energy unit power output is obtained according to the grid load change curve.

[0061] The predicted power generation of the new energy generator set and the upper threshold and lower threshold of its power output are compared.

[0062] When the power output of the new energy unit is lower than the lower threshold of the power output, input the power of the generator set into the energy storage device connected with the generator set; when the power output of the generator set is higher than the lower threshold of the power output, judge whether the power output of the generator set is greater than the grid load, if yes, input the part greater than the load into the energy storage device of the grid, if not, use the energy storage device or the conventional generator set to supplement the power of the new energy generator set;

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

[0064] Preferably, the judgment of whether the power output of the generator set is greater than the grid load, if yes, input the part greater than the load into the energy storage device of the grid, if not, use the energy storage device or the conventional generator set to supplement the power of the new energy generator set, specifically includes:

[0065] Inputting the part greater than the load into the energy storage device of the grid includes:

[0066] Obtaining the load state of each energy storage device;

[0067] According to the distance from the new energy generator set from small to large, record as [e1, e2...e n ];

[0068] Calculate whether the remaining load of e1 is greater than the excess power of the new energy generator set in the period, if yes, dispatch the excess power to e1, if not, after e1 is loaded, remove e1 from the data set;

[0069] Repeat the above step until the excess power is allocated;

[0070] Using the energy storage device or the conventional generator set to supplement the power of the new energy generator set includes:

[0071] Taking the power output of the selected energy storage device or the conventional generator set meeting the power requirement as a constraint, taking the power output of the selected energy storage device or the conventional generator set being not less than the power requirement as an objective function, and solving the energy storage device or the conventional generator set providing power;

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

[0073]

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

[0075] The target 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 required power of the power grid.

[0078] Further, a power distribution network dispatching system based on new energy output prediction data is proposed, which is used to realize the power distribution network dispatching method based on new energy output prediction data as described above. The system includes a data acquisition module, a day-ahead dispatching module, an intra-day short-term dispatching module, and a control center.

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

[0080] The day-ahead dispatching module is used to formulate a day-ahead dispatching plan according to the regional tomorrow predicted power consumption data and the regional tomorrow predicted new energy power generation data.

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

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

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

[0084] The power consumption prediction unit is used to query historical power consumption data of similar weather tomorrow according to regional historical power consumption data and regional historical weather data, and obtain regional tomorrow predicted power consumption data according to the query result.

[0085] The new energy power generation prediction unit is used to predict regional new energy power generation data according to regional new energy generator set historical power generation data, regional historical weather data, and regional tomorrow weather forecast data.

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

[0087] Optionally, the short-term scheduling module comprises a first judging unit, a threshold solving unit, a second judging unit and a scheduling unit.

[0088] The first judging unit is configured to judge whether the power generation power variation trend of each new energy generator unit meets the power grid load demand according to the power grid system load variation trend and the power generation power variation trend of each new energy generator unit.

[0089] The threshold solving unit is configured to solve the upper threshold and the lower threshold of the power output of each new energy generator unit according to the specification information of each new energy generator unit and each grid-connected inverter and the power grid system load connected by each grid-connected inverter.

[0090] The second judging unit is configured to judge the relationship between the upper threshold and the lower threshold of the power output of the new energy generator unit and the predicted power generation power of the new energy generator unit.

[0091] The scheduling unit determines the power scheduling mode of each new energy generator unit according to the judgment result of the second judging unit.

[0092] Compared with the prior art, the present application has the following advantages:

[0093] The power distribution network scheduling method based on new energy output prediction data provided by the present application improves the accuracy of the prediction model by considering the loss rate of each new energy generator unit when predicting the power generation power of new energy, and ensures the accuracy of the prediction of the power generation power and the power generation capacity of new energy. When performing day-ahead scheduling, the resource utilization rate is reduced due to the neglect of the differences between different time periods during unified scheduling, and the upper limit of the power generation capacity is adjusted by the environmental protection coefficient of each conventional generator unit, and the generator unit for power supply is determined according to the upper limit of the power generation capacity of each generator unit, thereby improving the power scheduling efficiency. When performing intra-day scheduling, the output power upper threshold and lower threshold are set, and the power output mode of the new energy generator unit is determined according to the threshold division, thereby avoiding the influence of the normal operation of the equipment caused by the excessively high power generation power or the waste of electric energy caused by the unstable grid connection caused by the excessively low power generation power. BRIEF DESCRIPTION OF DRAWINGS

[0094] Figure 1 The power distribution network scheduling method based on new energy output prediction data provided by the present application improves the accuracy of the prediction model by considering the loss rate of each new energy generator unit when predicting the power generation power of new energy, and ensures the accuracy of the prediction of the power generation power and the power generation capacity of new energy. When performing day-ahead scheduling, the resource utilization rate is reduced due to the neglect of the differences between different time periods during unified scheduling, and the upper limit of the power generation capacity is adjusted by the environmental protection coefficient of each conventional generator unit, and the generator unit for power supply is determined according to the upper limit of the power generation capacity of each generator unit, thereby improving the power scheduling efficiency. When performing intra-day scheduling, the output power upper threshold and lower threshold are set, and the power output mode of the new energy generator unit is determined according to the threshold division, thereby avoiding the influence of the normal operation of the equipment caused by the excessively high power generation power or the waste of electric energy caused by the excessively low power generation power or the unstable grid connection caused by the excessively low power generation power.

[0095] Figure 2 The power distribution network scheduling method based on new energy output prediction data provided by the present application improves the accuracy of the prediction model by considering the loss rate of each new energy generator unit when predicting the power generation power of new energy, and ensures the accuracy of the prediction of the power generation power and the power generation capacity of new energy. When performing day-ahead scheduling, the resource utilization rate is reduced due to the neglect of the differences between different time periods during unified scheduling, and the upper limit of the power generation capacity is adjusted by the environmental protection coefficient of each conventional generator unit, and the generator unit for power supply is determined according to the upper limit of the power generation capacity of each generator unit, thereby improving the power scheduling efficiency. When performing intra-day scheduling, the output power upper threshold and lower threshold are set, and the power output mode of the new energy generator unit is determined according to the threshold division, thereby avoiding the influence of the normal operation of the equipment caused by the excessively high power generation power or the waste of electric energy caused by the excessively low power generation power or the unstable grid connection caused by the excessively low power generation power.

[0096] Figure 3A flow chart for determining a day-ahead overall allocation scheme in a power distribution network dispatching method based on new energy output prediction data according to an embodiment of the present application;

[0097] Figure 4 A flow chart for formulating an intra-day short-term dispatching plan in a power distribution network dispatching method based on new energy output prediction data according to an embodiment of the present application;

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

[0099] The following description is provided to enable any person skilled in the art to make and use the present application. The preferred embodiments in the following description are only examples and other obvious modifications are possible to those skilled in the art.

[0100] Reference Figures 1-4 An embodiment of the present application provides a power distribution network dispatching method based on new energy output prediction data, which specifically comprises the following steps:

[0101] The existing model is trained and adjusted using historical power generation data of regional new energy generator units and historical weather data of the region, to obtain a new energy generator unit power generation prediction model;

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

[0103] Maintenance information of the generator units is obtained and sorted in time sequence as [T1, T2...T n ];

[0104] Data with time after T n is selected from the historical power generation data of new energy generator units and historical weather data;

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

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

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

[0108] In the embodiment, according to historical power generation data and historical predicted power generation data of each new energy generator unit, a loss coefficient of each generator unit is calculated based on a linear regression model, and then the loss coefficient is added to an existing model to obtain a new power generation prediction model of the new energy generator unit, so that the prediction accuracy of the prediction model for the power generation of each new energy generator unit is effectively improved.

[0109] In the embodiment, the specific method for calculating the loss coefficient is as follows: a function of historical predicted power generation, loss coefficient and corresponding historical power generation is constructed, and a least square method is used to find the best function matching of the historical predicted power generation data and the corresponding historical power generation data, that is, the value of the loss coefficient is calculated.

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

[0111] P=P0(1-λ);

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

[0113] The time of one day is divided into 24 segments, each for 1 hour;

[0114] According to the historical power consumption data and the historical weather data of the region, the historical power consumption data with similar weather as tomorrow is queried, and the regional predicted power consumption data of the period is obtained according to the query result;

[0115] Exemplarily, a method for obtaining regional predicted power consumption data of tomorrow is as follows:

[0116] The historical power consumption data with similar weather as tomorrow is obtained, and the mean value of the historical power consumption data is taken as the predicted power consumption data of tomorrow;

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

[0118] The daily power generation upper limit data and the stable power generation data of each conventional generator unit are obtained;

[0119] The power generation data of each conventional generator unit at the beginning of the period is obtained;

[0120] According to the daily power generation upper limit data of each conventional generator unit and the power generation data of each conventional generator unit, the daily remaining power generation upper limit of each conventional generator unit is determined;

[0121] determining the available power generation capacity of each conventional generator set according to the stable power generation data of each conventional generator set, taking the smaller value between the upper limit of the remaining power generation capacity and the available power generation capacity of each conventional generator set as the first power generation upper limit of each conventional generator set;

[0122] obtaining the pollution emission historical data of each conventional generator set;

[0123] calculating the environmental protection coefficient of each conventional generator set according to the pollution emission historical data, the environmental protection coefficient representing the average carbon emission of each conventional generator set per unit of power generation;

[0124] obtaining the daily carbon emission baseline of each conventional generator set and the amount of carbon emission of each conventional generator set, and determining the remaining carbon emission capacity of each conventional generator set;

[0125] obtaining the second power generation upper limit of each conventional generator set according to the remaining carbon emission capacity of each conventional generator set and the environmental protection coefficient of each conventional generator set;

[0126] if the second power generation upper limit is higher than the first power generation upper limit, taking the first power generation upper limit as the power generation upper limit of each conventional generator set, otherwise, taking the second power generation upper limit as the power generation upper limit of each conventional generator set;

[0127] determining the predicted total power generation of each conventional generator set in the time period according to the regional predicted power consumption data and the predicted total power generation data of new energy in the time period;

[0128] arranging each conventional generator set in descending order of the power generation upper limit to obtain the power supply priority of each conventional generator set;

[0129] obtaining the start-stop state of each conventional generator set;

[0130] if the generator set is in a running state at the beginning of the time period, the generator set is classified into a high-priority group in the time period;

[0131] if the generator set is not in a running state at the beginning of the time period, the generator set is classified into a low-priority group in the time period;

[0132] considering the high-priority group, the low-priority group and the power generation upper limit priority in the time period, the conventional generator sets in the time period are allocated;

[0133] other time periods are processed according to the above steps to determine the allocation scheme of the conventional generator sets in each time period in the day-ahead;

[0134] the allocation schemes of the conventional generator sets in each time period in the day-ahead are integrated to determine the overall allocation scheme in the day-ahead.

[0135] In the embodiment, the second power generation upper limit of each conventional generator set is determined according to the remaining dischargeable amount and the environmental protection coefficient of each conventional generator set, the influence of the carbon emission capacity of the conventional generator set on the environment is considered when the conventional generator set is allocated, the conventional generator set with less carbon emission is selected under the same condition, which is beneficial to realize the goal of carbon emission reduction, and the started generator set is preferentially considered when the conventional generator set is allocated, so that the cost of starting and stopping the generator set can be effectively reduced.

[0136] It should be noted that the daily carbon emission amount of the conventional generator set is not a fixed value due to the influence of technological progress and policy changes, and the daily carbon emission amount of the conventional generator set may exceed the preset standard in special cases due to carbon trading.

[0137] After entering the second day, the power generation power data of each new energy generator set in the short term is predicted by using a new energy generator set power generation power prediction model according to real-time weather data of the region, and a curve of power generation power changing with time is drawn;

[0138] According to the latest prediction message of the power dispatching center, the load change trend of the power grid system in the short term is obtained;

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

[0140] If the load demand of the power grid is met, the electric energy of each new energy generator set is input into the power grid;

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

[0142] The power output mode of each new energy generator set is determined according to the upper threshold and the lower threshold of the power output of each new energy generator set and the predicted power generation power data of each new energy generator set;

[0143] The determined short-term power output mode of each new energy generator set is sent to the control center, and the control center performs short-term power dispatching according to the information.

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

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

[0146] According to the specification information of each grid-connected inverter, the rated power of each grid-connected inverter is determined;

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

[0148] According to the specification information of each new energy generator set, the stable operation 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 connected to each grid-connected inverter, the minimum input power required for the grid-connected inverter to maintain matching with the grid voltage, frequency and phase is evaluated;

[0150] The stable operation 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 of the output power of the new energy generator set.

[0151] In the embodiment, according to the specification information of each grid-connected inverter, the rated power of each grid-connected inverter is determined, and the rated power of the grid-connected inverter is taken as the upper threshold of the output power of the new energy generator set connected thereto. The output power upper threshold is set considering the specification of the grid-connected inverter, so as to prevent excessive output power from affecting the normal work of the grid-connected inverter. Meanwhile, the stable operation 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 of the output power of the new energy generator set. The output power lower threshold set by the 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 output power upper threshold and the output power lower threshold 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 as follows:

[0153] The predicted change trend of the grid load is obtained, and the grid load change curve is drawn;

[0154] According to the grid load change curve, the lower threshold of the power output of the new energy generator set is obtained;

[0155] The predicted power generation power of the new energy generator set is compared with the upper threshold and the lower threshold of the power output thereof;

[0156] When the power output of the new energy unit is lower than the lower threshold, the power generated by the unit is input into the energy storage device connected to the unit; when the power output of the unit is higher than the lower threshold, it is determined whether the power output of the unit is greater than the load of the power grid, if yes, the part greater than the load is input into the energy storage device of the power grid, if no, the new energy unit is supplemented with power by the energy storage device or the conventional power unit;

[0157] When the power output of the new energy unit is higher than the upper threshold, the part higher than the upper threshold is input into the energy storage device directly connected to the unit.

[0158] In the embodiment, when the power output of the new energy unit is higher than the upper threshold, i.e. the power output is higher than the rated power of the grid-connected inverter, the grid-connected inverter connected to the unit may be damaged, therefore, the power higher than the upper threshold is input into the energy storage device directly connected to the unit; when the power output of the new energy unit is lower than the lower threshold, the unit cannot operate stably and the power of the unit cannot support stable grid connection, resulting in that the generated power cannot be input into the power grid and is wasted, therefore, the power lower than the lower threshold is input into the energy storage device directly connected to the unit.

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

[0160] The load state of each energy storage device is obtained;

[0161] Each energy storage device is sorted according to the distance from the new energy unit from small to large, denoted as [e1, e2...en]; n ];

[0162] It is determined whether the remaining load of e1 is greater than the excess power of the new energy unit in the period, if yes, the excess power is dispatched to e1, if no, e1 is removed from the data set after the load of e1 is satisfied;

[0163] The above step is repeated until the excess power is dispatched.

[0164] It can be understood that the cost of power transmission should also be considered when selecting the energy storage device, if the selected energy storage device is far away from the unit, resulting in large transmission loss and high cost, the excess power can be consumed by encouraging the increase of power consumption in the area near the unit.

[0165] Exemplarily, the specific method of supplementing the new energy unit with power by the energy storage device or the conventional power unit is as follows:

[0166] The power generation of the selected energy storage device or the conventional generator set meets 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 is not less than the power requirement as an objective function, so as to solve the energy storage device or the conventional generator set providing power;

[0167] The constraint condition that the power generation of the selected energy storage device or the 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 of the selected energy storage device or the 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 required power of the grid.

[0173] In the embodiment, the objective function solves multiple schemes, and the power dispatching center can select the scheme with the minimum power transmission loss and power generation cost as the optimal scheme according to the power transmission loss of each energy storage device and conventional generator set and the power generation cost of the conventional generator set;

[0174] It can be understood that when the power supply device is selected, the power demand may not be met by a single power supply device, at which time multiple energy storage devices or conventional generator sets should be considered for power supplement, and the carbon emission of the conventional generator set should also be considered when the conventional generator set is selected.

[0175] Referring to Figure 5 An embodiment of the present application also provides a power distribution network dispatching system based on new energy output prediction data, which adopts the above-mentioned power distribution network dispatching method based on new energy output prediction data to distribute and dispatch power energy, and comprises a data acquisition module, a day-ahead dispatching module, an intra-day short-term dispatching module and a control center.

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

[0177] The day-ahead scheduling module is configured to formulate a day-ahead scheduling plan according to the regional next-day predicted power consumption data and the regional next-day predicted new energy power generation data.

[0178] The intra-day short-term scheduling module is configured to formulate an intra-day short-term scheduling plan according to the power generation power change trend of each new energy generator set and the power grid system load change trend.

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

[0180] The day-ahead scheduling module includes a power consumption prediction unit, a new energy power generation prediction unit, and a scheduling unit.

[0181] The power consumption prediction unit is configured to query historical power consumption data of similar weather of the next day according to regional historical power consumption data and regional historical weather data, and obtain regional next-day predicted power consumption data according to the query result.

[0182] The new energy power generation prediction unit is configured to predict regional new energy power generation data according to regional new energy generator set historical power generation power data, regional historical weather data, and regional next-day weather forecast data.

[0183] The scheduling unit is configured to formulate a day-ahead scheduling plan according to the regional next-day predicted power consumption data and the regional next-day predicted new energy power generation data.

[0184] The intra-day 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 configured to judge whether the power generation power change trend of each new energy generator set meets the power grid load demand according to the power grid system load change trend and the power generation power change trend of each new energy generator set.

[0186] The threshold solving unit is configured to solve the upper threshold and the lower threshold of the power output of each new energy generator set according to the specification information of each new energy generator set and each grid-connected inverter and the power grid system load connected with each grid-connected inverter.

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

[0188] The scheduling unit determines the power scheduling mode of each new energy generator set according to the judgment result of the second judgment unit.

[0189] In summary, the application has the advantages that: when the new energy power generation power is predicted, the loss rate of each new energy generator set is considered, the accuracy of the prediction model is improved, and the accuracy of the new energy power generation power and the power generation capacity prediction is ensured; when the day-ahead scheduling is performed, the time period is adjusted for the generator set, the resource utilization rate caused by the difference of the time period is avoided, the upper limit of the power generation capacity is adjusted through the environmental protection coefficient of each conventional generator set, and the generator set for power supply is determined according to the upper limit of the power generation capacity of each generator set, so that the power dispatching efficiency is improved; when the day-ahead scheduling is performed, the output power upper threshold and lower threshold are set, the power output mode of the new energy generator set is determined according to the threshold, the normal operation of the equipment is avoided when the power generation power is too high, or the waste of electric energy caused by the unstable grid connection when the power generation power is too low is avoided.

[0190] The basic principle, main features and advantages of the application are shown and described above. It should be understood by those skilled in the art that the application is not limited by the above examples, and the above examples and descriptions in the specification are only the principles of the application. Without departing from the spirit and scope of the application, various changes and improvements can be made to the application, and these changes and improvements all fall within the scope of the claimed application. The scope of protection claimed by the application is defined by the appended claims and their equivalents.

Claims

1. A distribution network scheduling 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 distribution network coverage area; Based on the historical electricity consumption data and historical weather data of the region, query the historical electricity consumption data of 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 regional historical weather data to train and adjust the existing model to obtain a power generation prediction model for new energy generators; Based on the regional weather forecast data for tomorrow and the power generation prediction model of the new energy generator sets, the power generation data of each new energy generator set for tomorrow is predicted, a curve of power generation changing with time is plotted, and the predicted daily power generation of each new energy generator set is obtained by integration; The predicted daily power generation of each generator set is added together to obtain the regional predicted new energy power generation for tomorrow; Formulate a day-ahead dispatch plan based on the regional tomorrow's forecast electricity consumption data and the regional tomorrow's forecast renewable energy power generation data; Get real-time weather data for the region; 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; Obtain short-term load change trends of the power grid system based on the latest forecast information from the power dispatching center; Formulate a short-term daily dispatch plan based on the power generation curves of each renewable energy generator and the load change trend of the power grid system; The day-ahead dispatch 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; Based on the historical electricity consumption data and 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 based on the query results; Based on the weather data for that period and the power generation prediction model of the new energy generator sets, the power generation data of each new energy generator set for that period is predicted, the power generation of each generator set is obtained by integration, and the power generation of each generator set is added up to obtain the total predicted power generation of the new energy for that period; Obtain daily power generation limit data and stable power generation data for 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 generator set based on the upper limit data of the daily power generation of each conventional generator set and the power generation data of each conventional generator set; Determine the available power generation capacity of each conventional generator set during the period based on the stable power generation data of each conventional generator set, and take the smaller value of the upper limit of the daily remaining power generation capacity and the available power generation capacity during the period as the first power generation capacity upper limit of the conventional generator set; Obtain historical pollution emission data for each conventional power generation unit; Calculating an environmental protection coefficient for each conventional power generation unit based on the pollution emission historical data, wherein the environmental protection coefficient represents the average carbon emissions per kilowatt-hour of electricity produced by the conventional power generation unit; Obtain the daily carbon emission baseline of a conventional power generation unit and the emissions already emitted by the conventional power generation unit, and determine the remaining emissions of the conventional power generation unit; Obtaining a second upper limit of power generation of each conventional generator set according to the remaining dischargeable amount of each conventional generator set and the environmental protection coefficient of each conventional generator set; 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 used as the upper limit of power generation of the generator set; otherwise, the second upper limit of power generation is used as the upper limit of power generation of the generator set; Determine the predicted total power generation of conventional generators during the period based on the regional predicted power consumption data and the predicted total power generation data of new energy sources during the period; Arrange the conventional generator sets from high to low according to their upper limits of power generation, and allocate the predicted total power generation of the conventional generator sets during the period according to the priority of the arrangement; Process other time periods according to the above steps to determine the allocation plan of conventional generator sets for each time period on the previous day; The overall allocation plan for the day ahead is determined by integrating the allocation plans of the conventional power generation units in each period of the day ahead; The allocation plan of the conventional power generation units in each period of the day before is comprehensively considered to determine the overall allocation plan of the day before, specifically including: Determine the generator sets for each period based on the allocation plan of the conventional generator sets for each period on the previous day; If the generator set is in the running state at the beginning of the period, the generator set is classified as the high priority group of the period; If a generator set is not in operation at the beginning of a time period, the generator set is classified as a low priority group for that time 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 ahead.

2. A distribution network scheduling 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 regional new energy generators and the historical weather data of the region to train and adjust the existing model to obtain the power generation prediction model of the new energy generators specifically includes: Get the maintenance information of the generator set and sort it in time series as ; Select the time from the historical power generation data and historical weather data of new energy generators The data after that; The selected historical weather data is input into the prediction model as a data set to obtain the historical predicted 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 scheduling method based on renewable energy output forecast data according to claim 1, characterized in that: The above-mentioned short-term scheduling plan is formulated according to the power generation change curve of each renewable energy generator set and the load change trend of the power grid system, 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 electricity 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 calculated based on 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 generator set according to the power output upper and lower thresholds of each new energy generator set and the predicted power generation data of each new energy generator set; The determined short-term power output mode of each new energy generator set is sent to the control center, and the control center performs short-term power dispatch based on the information.

4. A distribution network scheduling method based on renewable energy output forecast data according to claim 3, characterized in that: The step of obtaining the upper and lower thresholds of the power output of each new energy generator set based on the specification information of each new 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 based on its specification information; 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, obtain the stable operating power of each new energy generator set; Based on the specifications 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 for the grid-connected inverter to maintain voltage, frequency, and phase matching with the grid 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.

5. A distribution network scheduling method based on renewable energy output forecast data according to claim 3, characterized in that: The determining of the power output mode of each new energy power generation group according to the power output upper and lower thresholds 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 exceeding 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 generated 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.

6. A distribution network dispatching method based on renewable energy output forecast data according to claim 5, characterized in that: The method of determining whether the power generation of the generator set is greater than the load of the power grid, and if so, inputting the portion exceeding the load into the energy storage device of the power grid, and 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 excess load into the grid include: Obtain the load status of each energy storage device; Sort the energy storage devices by their distance from the new energy generator set from small to large, and record them as ; calculate Is the remaining load greater than the excess power of the renewable energy generators during this period? If so, the excess power will be dispatched to If not, then After the load is satisfied, Remove the dataset; 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 power is determined by taking the power generated by the selected energy storage device or conventional generator set meeting the power requirement as the constraint, and the energy stored by the selected energy storage device or the power generated by the conventional generator set not being less than the power requirement as the objective function. The constraints that the power generated by the selected energy storage device or conventional generator set meets the required power are: Where, is the power generation capacity of the new energy generator set, The power generation capacity of the selected energy storage device or conventional generator set, is the grid load; The objective function is: Where, is the power generation of the new energy generator set, For the load of the selected energy storage device or the power generation of the conventional generator set, The electricity required for the grid.

7. A distribution network dispatching system based on renewable energy output forecast data, used to implement the dispatching method according to any one of claims 1 to 6, 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 obtain regional historical electricity consumption data, regional historical weather data, regional tomorrow's weather forecast data, regional conventional generator set historical power generation data, regional new energy generator set 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 scheduling module is used to formulate an intraday short-term scheduling plan based on the power generation change trend of each renewable 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.

8. A distribution network dispatching system based on renewable energy output forecast data according to claim 7, 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 of the weather similar 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 result; The new energy power generation prediction unit is used to predict regional new energy power generation data based on the historical power generation data of regional new energy power generation units, regional historical weather data and 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 new energy generator set meets the power grid load demand based on the power grid system load change trend and the power generation power change trend of each new energy generator set; The threshold value solving unit is used to calculate the upper and lower threshold values ​​of the power output of each new energy generator set according to the specification information of each new energy generator 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 power 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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