CN117638996A

CN117638996A - Layered control photovoltaic micro-grid energy management system and method

Info

Publication number: CN117638996A
Application number: CN202410101128.0A
Authority: CN
Inventors: 李德福; 詹金锭; 黄克毅; 林峰荣
Original assignee: Shenzhen Zhifu New Energy Co ltd
Current assignee: Shenzhen Zhifu New Energy Co ltd
Priority date: 2024-01-25
Filing date: 2024-01-25
Publication date: 2024-03-01
Anticipated expiration: 2044-01-25
Also published as: CN117638996B

Abstract

The invention discloses a layered control photovoltaic micro-grid energy management system and method, and relates to the technical field of power generation and energy storage. The power station energy storage layer comprises a collector side energy storage end and a collector energy storage control unit, and is used for supplying power to a power grid after absorbing power fluctuation of the photovoltaic power station; the power grid energy storage layer comprises a power grid energy storage end and a power grid energy storage control unit and is used for absorbing power fluctuation of the power grid; the power transmission energy storage layer comprises a power transmission side energy storage end and a power transmission energy storage control unit and is used for absorbing power fluctuation of the power utilization end; the main control unit is used for controlling the current collection energy storage control unit, the power grid energy storage control unit and the power transmission energy storage control unit. The invention effectively reduces the fluctuation of the power transmission and transformation of the power grid and improves the operation stability of the photovoltaic micro-grid.

Description

Layered control photovoltaic micro-grid energy management system and method

Technical Field

The invention belongs to the technical field of power generation and energy storage, and particularly relates to a layered control photovoltaic micro-grid energy management system and method.

Background

Under the current energy structure transformation and power system development background, photovoltaic power generation becomes a key power generation mode in a micro-grid system due to the characteristics of cleanliness and reproducibility. The micro-grid is taken as an important component of the power system, can effectively integrate various distributed energy sources, improves the energy utilization efficiency, and has certain autonomous operation capability.

However, as the scale of photovoltaic power generation continues to expand, photovoltaic micro-grids face challenges of complicating operation management. Particularly, under the influence of the instability and intermittence characteristics of the photovoltaic power generation, how to realize the efficient and reliable management of the energy in the micro-grid becomes a key problem.

Disclosure of Invention

The invention aims to provide a layered management and control photovoltaic micro-grid energy management system and method, which are used for analyzing and storing energy by means of electric wave power of a photovoltaic power station and an electric end, and effectively reducing the fluctuation of power transmission and transformation of a power grid and improving the operation stability of the photovoltaic micro-grid on the premise of meeting the requirement of user electricity consumption.

In order to solve the technical problems, the invention is realized by the following technical scheme:

the invention provides a layered control photovoltaic micro-grid energy management method, which comprises the following steps of,

acquiring a history record of the generated power of each photovoltaic power station;

acquiring a history record of the power consumption of each power consumption terminal;

obtaining target networking power of all the photovoltaic power stations at each moment in the day according to the history record of the generated power of each photovoltaic power station;

acquiring the accumulated power of all the photovoltaic power stations at the current moment;

charging and discharging all the photovoltaic power stations according to the difference value of the target network access power and the accumulated power generation power at the current moment, so that the network access power of the power grid at the current moment is the target network access power;

obtaining expected total load power of all the power utilization terminals at each moment in the day according to the history record of the power utilization power of each power utilization terminal;

acquiring accumulated power of all the power utilization terminals at the current moment;

charging and discharging the power grid according to the difference value of the expected total load power and the accumulated electric power of all the electric terminals at the current moment, so that the output power of the power grid at the current moment is the expected total load power;

and charging and discharging the power grid according to the difference value of the target network access power and the expected total load power at the current moment, so that the energy of the power grid is balanced at the current moment.

The invention also discloses a layered control photovoltaic micro-grid energy management method, which comprises the steps of,

receiving a difference value between the target network access power and the accumulated power generation power at the current moment;

and controlling the energy storage end at the collecting side to charge and discharge all the photovoltaic power stations so that the network access power of the power grid at the current moment is the target network access power.

receiving the difference value of the expected total load power and the accumulated power of all the power utilization terminals at the current moment;

and controlling the energy storage end at the power transmission side to charge and discharge the power grid so that the output power of the power grid at the current moment is the expected total load power.

receiving a difference value between the target network access power at the current moment and the expected total load power;

and controlling the power grid energy storage end to charge and discharge the power grid so as to balance the power grid energy at the current moment.

The invention also discloses a layered control photovoltaic micro-grid energy management system, which comprises,

a photovoltaic power plant is provided, which comprises a photovoltaic power plant,

the power station energy storage layer comprises a collector side energy storage end and a collector energy storage control unit and is used for supplying power to a power grid after power fluctuation of the photovoltaic power station is absorbed;

the power grid energy storage layer comprises a power grid energy storage end and a power grid energy storage control unit and is used for absorbing power fluctuation of the power grid;

the power transmission energy storage layer comprises a power transmission side energy storage end and a power transmission energy storage control unit and is used for absorbing power fluctuation of the power utilization end;

the main control unit is used for controlling the current collection energy storage control unit, the power grid energy storage control unit and the power transmission energy storage control unit;

wherein,

the main control unit is used for acquiring the history record of the generated power of each photovoltaic power station;

charging and discharging the power grid according to the difference value between the target network access power and the expected total load power at the current moment, so that the energy of the power grid is balanced at the current moment;

the collecting and energy-storing control unit is used for receiving the difference value between the target network access power and the accumulated power generation power at the current moment;

controlling the energy storage end of the collecting side to charge and discharge all the photovoltaic power stations so that the network access power of the power grid at the current moment is the target network access power;

the power grid energy storage control unit is used for receiving the difference value between the target network access power and the expected total load power at the current moment;

the method comprises the steps of controlling an energy storage end of a power grid to charge and discharge the power grid so as to balance the energy of the power grid at the current moment;

the power transmission energy storage control unit is used for receiving the difference value between the expected total load power and the accumulated power of all the power utilization ends at the current moment;

According to the invention, the control information of the current collection energy storage control unit, the power grid energy storage control unit and the power transmission energy storage control unit is generated by analyzing the power records of the photovoltaic power station and the power utilization end through the main control unit, so that the power fluctuation in the power station energy storage layer, the power grid energy storage layer and the power transmission energy storage layer is restrained, the power transmission and transformation balance of the power grid is realized, the power transmission and transformation fluctuation of the power grid is reduced, and the operation stability of the photovoltaic micro-grid is improved.

Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a layered management system for photovoltaic micro-grid energy management according to an embodiment of the present invention, and a functional module, an electrical energy flow direction, and an information flow direction;

FIG. 2 is a flowchart illustrating steps performed by the master control unit according to an embodiment of the present invention;

FIG. 3 is a flow chart illustrating steps of the current collecting and energy storing control unit according to an embodiment of the present invention;

FIG. 4 is a flowchart illustrating steps performed by the grid energy storage control unit according to an embodiment of the present invention;

FIG. 5 is a flowchart illustrating steps performed by the power transmission and energy storage control unit according to an embodiment of the present invention;

FIG. 6 is a flowchart illustrating the step S3 according to an embodiment of the present invention;

FIG. 7 is a flowchart illustrating the step S37 according to an embodiment of the present invention;

FIG. 8 is a flowchart illustrating the step S6 according to an embodiment of the present invention;

FIG. 9 is a flowchart illustrating the step S63 according to an embodiment of the present invention;

FIG. 10 is a diagram illustrating step S65 according to an embodiment of the present invention;

in the drawings, the list of components represented by the various numbers is as follows:

1-a photovoltaic power station;

2-power station energy storage layers, 21-collector side energy storage ends and 22-collector energy storage control units;

3-an electric network energy storage layer, 31-an electric network energy storage end and 32-an electric network energy storage control unit;

4-a power transmission energy storage layer, 41-a power transmission side energy storage end and 42-a power transmission energy storage control unit;

5-a main control unit;

and 6, an electricity utilization terminal.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like herein are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.

The photovoltaic micro-grid is a small independent power system formed by combining a solar photovoltaic power generation system with a local power grid. It is typically composed of photovoltaic cells, powered by converting solar energy into electrical energy. The photovoltaic micro-grid can be connected with a traditional power grid and can also independently operate. However, due to the instability of photovoltaic power generation and the uncertainty of electricity consumption of users, the power grid is in a fluctuation state, and damage to power transformation and power transmission systems of the power grid can be caused. In view of this, the present invention provides the following.

Referring to fig. 1 to 5, the present invention provides a layered management and control photovoltaic micro-grid energy management system, which may include, from functional modules, a photovoltaic power station 1, a power station energy storage layer 2, a grid energy storage layer 3, a power transmission energy storage layer 4, a main control unit 5, and a power utilization terminal 6. Specifically, the power station energy storage layer 2 comprises a collector side energy storage end and a collector energy storage control unit, and is used for supplying power to a power grid after power fluctuation of the photovoltaic power station is absorbed. The power grid energy storage layer 3 comprises a power grid energy storage end and a power grid energy storage control unit and is used for absorbing power fluctuation of the power grid. The power transmission energy storage layer 4 includes a power transmission side energy storage end and a power transmission energy storage control unit for absorbing power fluctuation of the power utilization end. The main control unit 5 is used for controlling the current collection energy storage control unit, the power grid energy storage control unit and the power transmission energy storage control unit.

In a specific operation process, step S1 is first performed by the main control unit 5 to obtain a history of the generated power of each photovoltaic power station. Step S2 may be performed to obtain a history of the power consumption of each power consumption terminal. Step S3 may be performed to obtain a target network access power of all photovoltaic power plants at each time in the current day according to the history of the generated power of each photovoltaic power plant. Step S4 may be performed to obtain the accumulated generated power of all the photovoltaic power plants at the current time. Step S5 can be executed to charge and discharge all photovoltaic power stations according to the difference value of the target network access power and the accumulated power generation power at the current moment, so that the network access power of the power grid at the current moment is the target network access power. Step S6 may be performed to obtain the desired total load power of all the power consumers at each moment in the day according to the history of the power consumption of each power consumer. Step S7 may be performed to obtain the accumulated power of all the power consuming terminals at the current time. Step S8 can be executed to charge and discharge the power grid according to the difference value between the expected total load power and the accumulated electric power of all the electric terminals at the current moment, so that the output power of the power grid at the current moment is the expected total load power. And finally, step S9 can be executed to charge and discharge the power grid according to the difference value between the target network access power and the expected total load power at the current moment, so that the energy of the power grid is balanced at the current moment.

For each energy storage layer, the collecting and energy storage control unit 22 may first perform step S011 to receive the difference between the target network access power and the accumulated generated power at the current time during operation. Step S012 may be executed to control the collector-side energy storage terminal 21 to charge and discharge all the photovoltaic power plants so that the grid-access power of the grid at the current moment is the target grid-access power.

During operation, the grid energy storage control unit 32 may first perform step S021 to receive the difference between the target grid access power at the current time and the desired total load power. Step S022 may then be performed to control the grid energy storage terminal 31 to charge and discharge the grid such that the grid energy is balanced at the present moment.

During operation, the power transmission and storage control unit 42 may first perform step S031 to receive the difference between the expected total load power and the accumulated power at all the power usage terminals at the present moment. Step S032 may then be performed to control the power transmitting-side energy storage terminal 41 to charge and discharge the power grid so that the output power of the power grid at the present moment is the desired total load power.

In the process, power fluctuation in the photovoltaic power station 1, the power grid 2 and the power utilization end 6 is simultaneously absorbed, so that steady-state operation of the photovoltaic micro-grid is realized.

Referring to fig. 6, since the illumination has periodicity, the photovoltaic power generation status every day has similarity with the reference day having similar illumination conditions. In view of this, in order to obtain the target network access power of all photovoltaic power plants at each time in the current day, the above-mentioned step S3 may be performed in the course of operation to obtain the interval duration from sunrise to sunset of the current day as the total daily sunlight duration at first. Step S32 may be performed next to acquire a plurality of natural days as same as the total daily sunlight duration of the current date as reference days, and step S33 may be performed next to acquire the generated power of the photovoltaic power plant at each acquisition time in the plurality of reference days from the history of the generated power of each photovoltaic power plant. Step S34 may be performed next to acquire a time period from sunrise to the next time as a target sunshine duration. Next, step S35 may be performed to take, as the reference time of the reference day, the time from the sunrise start to the end of the target solar duration within each reference day. Step S36 may be performed to obtain the generated power of the photovoltaic power station at the corresponding reference time on the multiple reference days according to the generated power of the photovoltaic power station at each collection time in the multiple reference days. Step S37 may be performed to obtain estimated power of the photovoltaic power plant at the next time according to the power of the photovoltaic power plant at the corresponding reference time on the basis of the plurality of reference days. And finally, performing steps S34 to S38 to repeatedly and continuously update the estimated power generation power at the next moment to obtain the estimated power generation power of all the photovoltaic power stations at each moment in the current day as the target network access power.

To supplement the above-described implementation procedures of step S31 to step S38, source codes of part of the functional modules are provided, and a comparison explanation is made in the annotation section. In order to avoid data leakage involving trade secrets, a desensitization process is performed on portions of the data that do not affect implementation of the scheme, as follows.

#include <iostream>

#include <vector>

#include <algorithm> // std::transform, std::accumulate

#include <numeric> // std::iota

Data structure and constant

Const int NUM_PV_STATIONS=5;// photovoltaic plant count

Const int NUM_REFERENCE_DAYS=3;// REFERENCE number of DAYS

Vector for storing the generated power of a photovoltaic power plant at each instant

struct PowerData {

std::vector<double> powerPerStation[NUM_PV_STATIONS];

};

Power generation power history acquisition function of/(photovoltaic power station

PowerData getHistoricalPowerData(int day) {

PowerData data;

Where in practice it should be a code to obtain data from a database or sensor etc

The following are merely exemplary data

for (int i = 0; i < NUM_PV_STATIONS; ++i) {

for (int j=0; j < 24;++j) {// 24 hours data

Power Perstation [ i ]. Push_Back (10.0+ (i.j)% 10);// generating Power

}

return data;

}

Function of time duration of sunrise-sunset interval

int getDaylightDuration() {

In practice it may be necessary to call the geolocation service API

return 12;// sunlight duration is 12 hours

}

Function of/(and acquisition of sunrise time

int getSunriseTime() {

Time service API calls may be required in a// implementation

return 6;// sunrise time is 6 a.m

}

Per principal algorithm logic

int main() {

Time for obtaining sunshine duration and sunrise time

int daylightDuration = getDaylightDuration();

int sunriseTime = getSunriseTime();

Storing/storing target network access power at each instant

std::vector<double> targetGridPower(24, 0.0);

For each reference day//

for (int day = 0; day < NUM_REFERENCE_DAYS; ++day) {

Data of/acquisition history power

PowerData historicalData = getHistoricalPowerData(day);

For each photovoltaic power plant

for (int station = 0; station < NUM_PV_STATIONS; ++station) {

For every moment from sunrise to sunset

for (int hour = sunriseTime; hour < sunriseTime + daylightDuration; ++hour) {

Obtaining/obtaining historical power of electricity generation at the current time

double power = historicalData.powerPerStation[station][hour];

/(and/or added to target network access power)

targetGridPower[hour] += power;

}

Averaging/processing target network access power

std::transform(

targetGridPower.begin(), targetGridPower.end(),

targetGridPower.begin(),

[NUM_REFERENCE_DAYS](double totalPower) {

return totalPower / NUM_REFERENCE_DAYS;

}

);

Output target network access power

for (int hour = 0; hour < 24; ++hour) {

std::cout << "Hour " << hour << ": " << targetGridPower[hour] << " kW" << std::endl;

}

return 0;

}

The basic idea of the code is that firstly, the sunshine duration and sunrise time are obtained through a function. Then, for each reference day, the historical power generation power of each photovoltaic station is obtained. And accumulating the power data in the period from sunrise to sunset, and averaging the accumulated power data to obtain the target network access power. And outputting the finally calculated target network access power at each moment.

Referring to fig. 7, in order to select estimated power that most likely matches the actual value from the power generated by the photovoltaic power plants at the plurality of reference moments, step S37 may be implemented by first executing step S371 to take the power generated by the photovoltaic power plants at the corresponding reference moments on the plurality of reference days as the reference power. Step S372 may then be performed to sort the plurality of reference powers by the number of values to obtain a reference power array. Step S373 may then be performed to calculate the average of the differences between each reference power and the adjacent reference powers in the obtained reference power series as the average interval power. Next, step S374 may be performed to form a plurality of reference powers with differences between adjacent powers less than the average interval power into reference power groups, resulting in a plurality of reference power groups. Step S375 may then be performed to calculate the number and average of all reference powers within each set of reference powers. Finally, step S376 may be executed to calculate the weighted average of the average of all the reference powers in each reference power group by taking the number of all the reference powers in the reference power group as the weight, so as to obtain the estimated power of the photovoltaic power station at the next moment.

To supplement the above-described implementation procedures of step S371 to step S376, source codes of part of the functional modules are provided, and a comparison explanation is made in the annotation section.

#include <iostream>

#include <vector>

#include <algorithm> // std::sort, std::adjacent_find

Data structure of// reference power

struct ReferencePower {

double power;

int count;

};

Calculating an average value of the difference between two adjacent values

double calculateAverageInterval(const std::vector<double>& powers) {

double totalInterval = 0.0;

for (size_t i = 1; i < powers.size(); ++i) {

totalInterval += powers[i] - powers[i - 1];

}

return totalInterval / (powers.size() - 1);

}

Weighted average of// calculation

double calculateWeightedAverage(const std::vector<ReferencePower>& powerGroups) {

double totalPower = 0.0;

int totalWeight = 0;

for (const auto& group : powerGroups) {

totalPower += group.power * group.count;

totalWeight += group.count;

}

return totalWeight > 0 ? totalPower / totalWeight : 0.0;

}

Per principal algorithm logic

int main() {

Power values for multiple reference days

std::vector<double> referencePowers = {30.5, 28.7, 32.8, 29.1, 31.2, 27.9, 30.0};

Sequencing of reference Power array

std::sort(referencePowers.begin(), referencePowers.end());

Calculating average spacing between adjacent reference powers

double averageInterval = calculateAverageInterval(referencePowers);

The reference powers of adjacent intervals less than the average interval constitute a reference power group

std::vector<ReferencePower> powerGroups;

for (size_t i = 0; i < referencePowers.size(); ) {

The use of std: adjacency find a position where the adjacent element spacing is less than the average spacing

auto it = std::adjacent_find(referencePowers.begin() + i, referencePowers.end(),

[averageInterval](double a, double b) {

return (b - a) < averageInterval;

});

if (it == referencePowers.end()) {

Break;// does not find, the loop is ended

}

Calculating the number and value within the reference power group

double sum = *it;

int count = 1;

auto next = it + 1;

while (next != referencePowers.end() && (*next - *it) < averageInterval) {

sum += *next;

++count;

++next;

}

Addition of the reference power set to vector

powerGroups.push_back({sum / count, count});

i=next-referencepowers. Begin ();// update cycle start position

}

Calculating weighted average to obtain estimated power

double estimatedPower = calculateWeightedAverage(powerGroups);

Output estimated power generation

std::cout << "Estimated Power for Next Time Slot: " << estimatedPower << " kW" << std::endl;

return 0;

}

This code first defines a simulated reference power array referencePowers, which is then sorted by size. Next, by calculating average interval averageInterval, those reference powers with adjacent power values smaller than the average interval are found and are combined into a reference power group. The number of all reference powers in each reference power group is used as a weight, and the average value of the reference powers is used to calculate the weighted average value of each group. And finally, calculating the total weighted average value of the weighted averages of all the reference power groups, so as to obtain the estimated power generation power of the photovoltaic power station at the next moment.

The code simulates the power generated by the photovoltaic power station on different reference days, and estimates the power generated at the next moment based on the data. First the code ranks the reference powers by a ranking algorithm. The average interval power is then calculated and based thereon the close reference powers are clustered into groups. Next, the weight (the number of reference powers in the group) and the average value of each group are calculated, and the weighted average value is calculated by using these weights, so as to be used as the estimated power to be generated at the next time, and finally the estimated power to be generated is output.

Referring to fig. 8, the electricity usage habit of the user has certain rules, so as to mine the rules and predict the expected total load power at each time in the day according to the rules. In the specific implementation process of step S6, step S61 may be executed first to obtain the electricity duration of the current date electricity end. Step S62 may be performed to obtain the electricity consumption from the zero point of the current date to the current time of the electricity consumption end as the calibration electricity according to the history of the electricity consumption power of each electricity consumption end. Step S63 may be executed, where a reference day and a corresponding reference time are selected from the history of the power consumption of each power consumption terminal according to the power consumption time and the calibration power. Step S64 may be performed next to take the electric power of the electric terminal at the next time of reference time of day as the reference power. Step S65 may be performed to obtain the desired total load power of all the power consuming terminals at the next moment in the day according to each reference power and the corresponding reference day. Step S66 may then be performed to iteratively and continuously update the desired total load power at the next time to obtain the desired total load power for all the utility terminals at each time of the day.

To supplement the above-described implementation procedures of step S61 to step S66, source codes of part of the functional modules are provided, and a comparison explanation is made in the annotation section.

#include <iostream>

#include <vector>

#include <numeric> // for std::accumulate

Recording 24 hours per day of electric power consumption of each electric terminal

struct PowerUsage {

std:: vector < std:: vector < double > > dailyUsage;// each element represents a day of recording of electrical power usage

};

The total electricity consumption of a certain electricity consumption terminal on a certain day is obtained

double getCalibrationPower(const PowerUsage& usage, int dayIndex) {

the/(dailyUsage [ daiyIndex ] contains a 24-hour recording of the power usage on that day

return std::accumulate(usage.dailyUsage[dayIndex].begin(), usage.dailyUsage[dayIndex].end(), 0.0);

}

The total power consumption before the current moment is obtained

double getCurrentTotalPower(std::vector<PowerUsage>& usages, int currentTime) {

double totalPower = 0.0;

for (auto& usage : usages) {

Take record of last day as an example

int lastDayIndex = usage.dailyUsage.size() - 1;

Charge amount/accumulated to current time only

totalPower += std::accumulate(usage.dailyUsage[lastDayIndex].begin(), usage.dailyUsage[lastDayIndex].begin() + currentTime, 0.0);

}

return totalPower;

}

Obtaining/obtaining the desired total load power at the next moment

double getNextTotalExpectedPower(std::vector<PowerUsage>& usages, int currentTime) {

double totalExpectedPower = 0.0;

for (auto& usage : usages) {

int lastDayIndex = usage.dailyUsage.size() - 1;

The reference day is the day before the last day, and the reference time is the current time

if (lastDayIndex > 0 && currentTime < usage.dailyUsage[lastDayIndex - 1].size() - 1) {

The next time of the current time of the reference day is taken as the reference power

totalExpectedPower += usage.dailyUsage[lastDayIndex - 1][currentTime + 1];

}

return totalExpectedPower;

}

int main() {

The example has 3 power utilization terminals, each having a 7 day power utilization history

std::vector<PowerUsage> usages(3, PowerUsage{{ {1.0, 1.2, 1.1}, {1.0, 1.3, 1.1}, {1.1, 1.2, 1.2}, {1.2, 1.1, 1.0}, {1.1, 1.2, 1.1}, {1.2, 1.3, 1.2}, {1.1, 1.0, 1.1} }});

int currenttime=2;// current time is 2 nd hour

For storing the desired total load power at each moment

std::vector<double> expectedTotalPowers;

Obtaining the total power consumption from zero point to current moment as the calibrated power

double calibrationPower = getCurrentTotalPower(usages, currentTime);

Calculating the desired total load power time by time

for (int time = 0; time < 24; ++time) {

double nextTotalExpectedPower = getNextTotalExpectedPower(usages, time);

expectedTotalPowers.push_back(nextTotalExpectedPower);

}

Output of the desired total load power per time instant

for (int i = 0; i < expectedTotalPowers.size(); ++i) {

std::cout << "Hour " << i << ": Expected Total Load Power = " << expectedTotalPowers[i] << std::endl;

}

return 0;

}

A PowerUssage structure is defined in the code to store historical electricity usage records for each electricity usage terminal. Obtaining a calibrated electric quantity through a getCalimation Power function, obtaining a current total electric quantity through a getCurrentTotalPower function, obtaining a desired total load power at the next moment through a getNextTotalExpectedPower function, and iteratively calculating the desired total load power at each moment in a main function. The main function finally prints out the desired total load power at each instant.

The code demonstrates how to predict the expected total load power at each time of day based on the daily electricity usage power history of the electricity usage end. Firstly, calculating the total power consumption before the current moment, then selecting a reference day and a reference moment to estimate the total load power of the next moment, iterating the process to obtain the expected total load power of each moment in the whole day, and finally outputting the result.

Referring to fig. 9, since the number of days with similar electricity consumption habits is greater in history, in order to screen out the reference day and reference time more closely approaching the current electricity consumption habits, step S63 may be executed first in the implementation process to obtain, according to the history of the electricity consumption power of each electricity consumption terminal, the electricity consumption of the electricity consumption terminal from the zero point to the end of the electricity consumption period in history as the reference electricity consumption of each day in history. Step S632 may then be performed to sort the historical daily reference electricity usage by value to obtain a reference electricity usage array. Step S633 may be performed next to calculate the average value of the difference between each reference power consumption and the adjacent reference power consumption in the acquired reference power consumption number series as the average interval power consumption. Next, step S634 may be performed to form a reference electricity consumption group from a plurality of reference electricity consumption groups having adjacent differences smaller than the average interval electricity consumption, so as to obtain a plurality of reference electricity consumption groups. Step S635 may be performed next to acquire a range from the minimum value to the maximum value of the reference electricity consumption amount within each reference electricity consumption amount group as a range of each reference electricity consumption amount group. Step S636 may be performed to select a reference power consumption group covering the calibration power according to the range of each reference power consumption group. Finally, step S637 may be executed to use the date corresponding to each reference electricity consumption in the reference electricity consumption group covering the calibrated electricity consumption and the time from the zero point to the end of the electricity consumption period as the reference date and the corresponding reference time respectively.

To supplement the above-described implementation procedures of step S631 to step S637, source codes of part of the functional modules are provided, and a comparison explanation is made in the annotation section.

#include <iostream>

#include <vector>

#include <algorithm> // for std::sort

#include <numeric> // for std::adjacent_difference

Structure of electric terminal

struct PowerUsage {

std:: vector < std:: vector < double > > dailyUsage;// each element is an hour of day recorded with electrical power

};

Obtaining electricity consumption of electricity utilization end in time period from zero point to electricity utilization time end in daily history

std::vector<double> getReferencePowerValues(const PowerUsage& usage, int duration) {

std::vector<double> referencePowers;

for (const auto& day : usage.dailyUsage) {

double sum = std::accumulate(day.begin(), day.begin() + duration, 0.0);

referencePowers.push_back(sum);

}

return referencePowers;

}

Calculating average interval power consumption

double getAverageInterval(std::vector<double>& sortedPowers) {

std::vector<double> intervals(sortedPowers.size() - 1);

std::adjacent_difference(sortedPowers.begin(), sortedPowers.end(), intervals.begin());

The first element is invalidated, so remove

intervals.erase(intervals.begin());

double sum = std::accumulate(intervals.begin(), intervals.end(), 0.0);

return sum / intervals.size();

}

Selecting reference day and reference time according to the calibrated electric quantity

std::vector<std::pair<int, int>> selectReferenceDaysAndTimes(const PowerUsage& usage, double calibrationPower, int duration) {

std::vector<double> referencePowers = getReferencePowerValues(usage, duration);

std::sort(referencePowers.begin(), referencePowers.end());

double averageInterval = getAverageInterval(referencePowers);

Range for storing reference power usage groups

std::vector<std::pair<double, double>> referenceGroupRanges;

double currentMin = referencePowers.front();

double currentMax = currentMin;

Reference electricity consumption group composed of adjacent difference values smaller than average interval electricity consumption

for (size_t i = 1; i < referencePowers.size(); ++i) {

if (referencePowers[i] - referencePowers[i - 1] < averageInterval) {

currentMax = referencePowers[i];

} else {

referenceGroupRanges.emplace_back(currentMin, currentMax);

currentMin = referencePowers[i];

currentMax = currentMin;

}

The last interval of addition

referenceGroupRanges.emplace_back(currentMin, currentMax);

Selecting/covering reference electricity consumption group of calibration electricity

std::vector<std::pair<int, int>> referenceDaysAndTimes;

for (const auto& range : referenceGroupRanges) {

if (calibrationPower >= range.first && calibrationPower <= range.second) {

Finding all eligible reference days and reference moments within this range

for (size_t day = 0; day < usage.dailyUsage.size(); ++day) {

double dayPower = std::accumulate(usage.dailyUsage[day].begin(), usage.dailyUsage[day].begin() + duration, 0.0);

if (dayPower >= range.first && dayPower <= range.second) {

referenceDaysAndTimes.emplace_back(day, duration);

}

break;// after finding the first eligible group, the loop can be exited

}

return referenceDaysAndTimes;

}

int main() {

Example/: power end history initialization

PowerUssage usage = { { { (1.0, 2.0, 3.0}, {1.5, 2.5, 3.5}, {2.0, 3.0, 4.0} }) }, three-day record, three hours per day// three days

int duration=2;// power duration is two hours

double calibrationPower =4.5;// calibration charge is 4.5

Obtaining a reference day and a reference time according to the calibrated electric quantity and the electricity consumption time length

std::vector<std::pair<int, int>> referenceDaysAndTimes = selectReferenceDaysAndTimes(usage, calibrationPower, duration);

Output result

for (const auto& dayTime : referenceDaysAndTimes) {

std: (cout < <): (reference day: "< < daytime. First <"), reference time: "< < daytime second <" (hour "< < std:: (endl);

}

return 0;

}

this code first uses the getdreencePowerValues function to calculate the total power usage daily from zero to the end of a specified power usage period. These electricity usage amounts are ranked, and then the getAverageInterval function calculates the average difference between adjacent electricity usage amounts. This average difference is then used to group adjacent power usage into a plurality of reference power usage groups. Then the selectReferenceDaysAndTimes function selects the reference electricity consumption group covering the calibrated electricity quantity, and finds out all the reference days and the corresponding reference moments meeting the conditions. Finally, an electricity recording example is initialized in the main function, and a selectreferedaysAndTimes function is called to show how the whole flow is used.

Referring to fig. 10, since the reference power for the near term is more suitable for the current power consumption state, step S651 may be performed to obtain the number of days from each reference day to the current date in the implementation process in step S65. Step S652 may then be performed to calculate the weighted average of each reference power as the expected total load power of all the power consumers at the next time in the day, taking the reciprocal of the number of days from each reference day to the current day as the weight corresponding to each reference power. The reference power which is far from the present time is given a lower weight, so that the accuracy of the expected total load power is improved.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.

It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by hardware, such as circuits or ASICs (application specific integrated circuits, application Specific Integrated Circuit), which perform the corresponding functions or acts, or combinations of hardware and software, such as firmware, etc.

Although the invention is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

The embodiments of the present application have been described above, the foregoing description is exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A layered control photovoltaic micro grid energy management method is characterized by comprising the following steps of,

2. The method of claim 1, wherein the step of deriving the target network access power for each time of day for all of the photovoltaic power plants based on the history of the generated power for each of the photovoltaic power plants comprises,

acquiring the interval time from sunrise to sunset of the current date as the sunshine duration of the whole day;

acquiring a plurality of natural days with the same sunshine duration of the whole day of the current date as reference days;

acquiring the power generation power of the photovoltaic power station at each acquisition time in a plurality of reference days according to the history record of the power generation power of each photovoltaic power station;

acquiring the time length from sunrise to the next moment as a target sunshine time length;

in each reference day, taking the time from the sunrise beginning to the target sunshine duration ending as the reference time of the reference day;

obtaining the power generation power of the photovoltaic power station at the corresponding reference time of a plurality of reference days according to the power generation power of the photovoltaic power station at each acquisition time of the reference days;

obtaining estimated power generation power of the photovoltaic power station at the next moment according to the power generation power of the photovoltaic power station at the corresponding reference moment of the reference days;

and iteratively and continuously updating the estimated power generation power at the next moment to obtain the estimated power generation power of all the photovoltaic power stations at each moment in the day as the target network access power.

3. The method of claim 2, wherein the step of obtaining the estimated generated power of the photovoltaic power plant at the next time based on the generated power of the photovoltaic power plant at the corresponding reference time on the plurality of reference days comprises,

taking the generated power of the photovoltaic power station at the corresponding reference time of a plurality of reference days as reference power;

sequencing a plurality of reference powers according to the values to obtain a reference power sequence;

calculating and obtaining the average value of the difference value between each reference power and the adjacent reference power in the reference power array as average interval power;

forming a plurality of reference powers with the difference value smaller than the average interval power between adjacent power into a reference power group to obtain a plurality of groups of reference power groups;

calculating and obtaining the quantity and the average value of all the reference powers in each group of the reference power groups;

and taking the quantity of all the reference powers in the reference power groups as weights, and calculating the weighted average of the average values of all the reference powers in each group of reference power groups to obtain the estimated power generation power of the photovoltaic power station at the next moment.

4. The method of claim 1, wherein the step of deriving the desired total load power for all of the power consuming terminals at each time of day from the history of the power consumption of each of the power consuming terminals comprises,

acquiring the electricity utilization time length of the electricity utilization terminal on the current date;

obtaining the electricity consumption of the electricity utilization end from the zero point of the current date to the current moment according to the history record of the electricity utilization power of each electricity utilization end as a calibration electricity quantity;

selecting a reference day and a corresponding reference time from the history record of the power consumption of each power consumption end according to the power consumption time and the calibration electric quantity;

taking the electric power of the electric terminal at the next moment of the reference moment in the reference day as reference power;

obtaining expected total load power of all the power utilization terminals at the next moment in the day according to each reference power and the corresponding reference day;

and iteratively and continuously updating the expected total load power at the next moment to obtain the expected total load power of all the power utilization terminals at each moment in the day.

5. The method of claim 4, wherein the step of selecting a reference day and a corresponding reference time from the history of the electric power used at each of the electric terminals based on the electric time period and the calibration electric quantity includes,

obtaining the electricity consumption of the electricity consumption end in a period from a zero point to the end of the electricity consumption duration in a historical manner according to the history record of the electricity consumption power of each electricity consumption end, wherein the electricity consumption of the electricity consumption end is used as a reference electricity consumption in the historical manner;

sequencing the historical daily reference electricity consumption according to the value to obtain a reference electricity consumption number sequence;

calculating and obtaining the average value of the difference value between each reference electricity consumption and the adjacent reference electricity consumption in the reference electricity consumption number series as average interval electricity consumption;

forming a plurality of reference electricity consumption groups with adjacent difference values smaller than the average interval electricity consumption, and obtaining a plurality of groups of reference electricity consumption groups;

acquiring a range from the minimum value to the maximum value of the reference electricity consumption in each reference electricity consumption group as a range of each reference electricity consumption group;

selecting the reference electricity consumption groups covering the calibrated electricity consumption according to the range of each reference electricity consumption group;

and respectively taking the date corresponding to each reference electricity consumption in the reference electricity consumption group covering the calibrated electricity consumption and the time from the zero point to the end of the electricity consumption duration as the reference date and the corresponding reference time.

6. The method of claim 4, wherein the step of obtaining a desired total load power for all of the power consuming terminals at a time next in the day based on each reference power and the corresponding reference day comprises,

acquiring the number of days from each reference day to the current day;

and taking the reciprocal of the number of days from each reference day to the current day as the weight corresponding to each reference power, and calculating the weighted average value of each reference power as the expected total load power of all the electricity utilization terminals at the next moment in the current day.

7. A layered control photovoltaic micro grid energy management method is characterized by comprising the following steps of,

receiving a difference between a target grid access power and an accumulated generated power at a current time in a hierarchically managed photovoltaic microgrid energy management method of any one of claims 1 to 6;

8. A layered control photovoltaic micro grid energy management method is characterized by comprising the following steps of,

receiving the difference value between the expected total load power and the accumulated electric power of all the electric terminals at the current moment in the layered control photovoltaic micro-grid energy management method according to any one of claims 1 to 6;

9. A layered control photovoltaic micro grid energy management method is characterized by comprising the following steps of,

receiving a difference between a current time target grid access power and a desired total load power in a hierarchically managed photovoltaic microgrid energy management method of any one of claims 1 to 6;

10. A layered control photovoltaic micro grid energy management system is characterized by comprising,

wherein,