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A day-ahead energy scheduling algorithm for wind-solar-storage microgrid

An energy scheduling and microgrid technology, applied in photovoltaic power generation, power generation forecasting and calculation in AC networks, etc., can solve problems such as increasing system operating costs and reducing microgrid system benefits, reducing operating costs and improving stability. , the effect of improving economic efficiency

Active Publication Date: 2022-05-03
NANTONG UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, although this measure can prolong the service life of the energy storage battery, the grid connection measure will also increase the operating cost of the system and reduce the revenue of the microgrid system

Method used

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  • A day-ahead energy scheduling algorithm for wind-solar-storage microgrid
  • A day-ahead energy scheduling algorithm for wind-solar-storage microgrid
  • A day-ahead energy scheduling algorithm for wind-solar-storage microgrid

Examples

Experimental program
Comparison scheme
Effect test

specific example 1

[0056] Step 3-1. Calculate the initial energy storage state of charge change plan curve according to formula (3) and the energy storage initial power exchange plan sequence. The initial energy storage state of charge change curve is as follows: figure 2 As shown in (c), if the difference between the maximum value and the minimum value of the state of charge in the initial state of charge change curve is less than 60%, enter step 3-2;

[0057] Step 3-2. Scan the entire initial state of charge sequence of the energy storage, and find that the maximum value of the state of charge is 88%. Therefore, it is necessary to correct the peak value of the energy storage, and calculate the corrected charge by formula (2) and formula (3). State of charge plan curve and energy storage power exchange plan sequence, repeat step 3-2 until the maximum state of charge does not exceed 80%;

[0058] Step 3-3. Re-scan the SOC planning curve corrected in step 3-2. At the same time, obtain the sampli...

specific example 2

[0068] Step 3-1, calculate the initial energy storage state of charge change curve according to formula (3) and the energy storage initial power exchange plan sequence, the initial energy storage state of charge change curve is as follows image 3 As shown in (c), if the difference between the maximum value and the minimum value of the state of charge in the initial state of charge change curve is less than 60%, go to step 3-2.

[0069] Step 3-2, scan the entire energy storage initial state of charge sequence, and go to step 3-3 if there is no state of charge exceeding the limit point.

[0070] In step 3-3, re-scan the SOC curve corrected in step 3-2, and at the same time, obtain the time period of the sampling point where the low electricity consumption and the peak electricity consumption are located in the next scheduling cycle. from image 3 It can be seen from (a) that the low power consumption period is between 0:00 and 5:00, and the peak power consumption period is betwe...

specific example 3

[0073] Step 3-1, calculate the initial energy storage state of charge change curve according to formula (3) and the energy storage initial planned power sequence, the initial energy storage state of charge change curve is as follows Figure 4 As shown in (c), if the difference between the maximum value and the minimum value of the state of charge in the initial state of charge change curve is less than 60%, go to step 3-2.

[0074] Step 3-2: Scan the entire initial state of charge sequence of the energy storage, and find that the maximum value of the state of charge is 85.6%. Therefore, the peak value of the energy storage needs to be corrected, and the corrected charge can be calculated by formula (2) and formula (3). Electricity state curve and energy storage power exchange plan sequence. Repeat step 3-2 until the maximum state of charge does not exceed 80%.

[0075] Step 3-3: re-scan the SOC curve corrected in step 3-2, and at the same time, obtain the time period of the s...

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Abstract

The invention discloses a day-ahead energy scheduling algorithm for wind-solar-storage micro-grid, which uses wind-solar forecasted power data and load forecasted demand data to design the energy throughput of the energy storage battery by controlling the charging and discharging power planning behavior of the energy storage battery and setting the grid-connected time period The planned curve ensures that the charging and discharging capacity of the energy storage battery does not exceed the limit during the daily operation, and the microgrid load is reliably supplied. At the same time, taking into account the economic benefits of the microgrid system and the power supply pressure of the public grid during peak load hours, the algorithm combines the predicted changes in the state of charge of the battery to make energy throughput plan corrections. The minimum value of the surplus electricity and the change process of the state of charge comprehensively considers the grid-connected discharge capacity of the energy storage battery, and releases electric energy to the public grid during the peak power consumption at noon and evening. The invention fully considers the utilization of new energy, ensures the normal power supply of micro-grid loads under the premise of healthy energy storage batteries, and reduces the power supply pressure of public power grids.

Description

technical field [0001] The invention relates to the technical field of new energy power generation system control, in particular to a day-ahead energy scheduling algorithm for a wind-solar-storage micro-grid. Background technique [0002] The use of renewable energy such as wind and solar has alleviated the increasingly serious energy crisis and environmental degradation to a certain extent. However, the inherent intermittent and uncertain characteristics of wind and solar energy have a great impact on the stable operation of the load side. The combination of energy storage system and wind-solar hybrid power generation system can improve the utilization rate of new energy, improve the acceptance of new energy by the public grid, and ensure the stable operation of load. However, the energy storage battery in the energy storage system is limited by its inherent life, which increases the operating cost of the microgrid system. In addition, improper charging and discharging be...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q10/04G06Q50/06H02J3/00H02J3/32H02J3/38
CPCG06Q10/06315G06Q10/04G06Q50/06H02J3/003H02J3/004H02J3/381H02J3/32H02J2300/24H02J2300/28Y02E10/56Y02E70/30
Inventor 朱建红任浩锋顾菊平赵佳皓张鹏坤蒋凌
Owner NANTONG UNIVERSITY
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