A collaborative governance method and system for microgrid power quality global optimization

Abstract

The present application relates to a kind of for microgrid power quality global optimization collaborative governance method and system, comprising the following steps: obtaining the data of each node in microgrid power quality index, the power quality index includes voltage deviation, frequency deviation, three-phase unbalance degree, harmonic distortion rate;The data of each node power quality index is input into power quality evaluation model, and the power quality score of single node is obtained;According to the power quality score of all nodes, the global power quality evaluation result of microgrid is obtained;According to global power quality evaluation result, the result of microgrid is divided, and the result of division includes superior, good, medium, poor;If the result is divided into medium or poor, then through power quality positioning algorithm, microgrid is governed, and the global power quality management optimization of microgrid is realized.The present application realizes the global evaluation of power quality in microgrid, optimizes power quality, and finally reaches the global optimal management of microgrid power quality.

Description

Technical Field

[0001] This invention relates to the field of microgrid power quality technology, and in particular to a collaborative governance method and system for global optimization of microgrid power quality. Background Technology

[0002] A microgrid is a small-scale power supply system composed of multiple distributed power sources, energy storage systems, electrical loads, and protection devices. Microgrids are typically located close to users but far from the main power grid; therefore, power quality within a microgrid is significantly affected by the user side. Furthermore, microgrids contain various power electronic converters, and the specific control methods of these converters and their interactions with loads give the power in a microgrid typical characteristics. While employing specific governance devices or implementing multi-functional governance strategies in inverters often yields good power quality management for specific nodes, it becomes difficult to achieve consistently good power quality across all nodes when the microgrid is large—that is, achieving globally optimal power quality management for the microgrid is challenging. Summary of the Invention

[0003] The purpose of this invention is to achieve global assessment of power quality in microgrids, optimize power quality, and ultimately achieve global optimal governance of power quality in microgrids. This invention provides a collaborative governance method and system for global optimization of power quality in microgrids.

[0004] To achieve the above-mentioned objectives, the embodiments of the present invention provide the following technical solutions:

[0005] A collaborative governance method for global optimization of power quality in microgrids includes the following steps:

[0006] Step S1: Obtain power quality index data for each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate.

[0007] Step S2: Input the power quality index data of each node into the power quality assessment model to obtain the power quality score of a single node; then obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes.

[0008] Step S3: The microgrid is classified according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

[0009] Furthermore, the step of acquiring power quality index data for each node in the microgrid includes:

[0010] Voltage and current data of the nodes are collected by three-phase voltage Hall sensors and three-phase current Hall sensors installed at each node.

[0011] The voltage deviation is obtained by calculating the measured voltage value and the rated voltage value;

[0012] The frequency deviation is obtained by comparing the measured frequency of the voltage with the rated frequency.

[0013] The three-phase imbalance degree of voltage and current is obtained by using the positive and negative sequence decomposition algorithm and the three-phase imbalance calculation formula.

[0014] By performing Fourier decomposition on the collected voltage and current and using the harmonic distortion rate calculation formula, the harmonic distortion rates of the voltage and current at each node of the microgrid are obtained.

[0015] Furthermore, the step of inputting the power quality index data of each node into the power quality assessment model to obtain the power quality score of a single node includes:

[0016] The four power quality indicators of the node are scored and quantified according to the upper limit value in the power quality standard to obtain the score corresponding to each power quality indicator of the node.

[0017] The Poisson process intensity of each power quality indicator is calculated using a Poisson process, and the average number of times a certain event occurs per unit time for each power quality indicator is statistically analyzed.

[0018]

[0019] Among them, the score of a single power quality indicator exceeding the upper limit of the power quality standard is L. U % represents the threshold for the event to occur; Let represent the intensity of the Poisson process occurring in the q-th event among the k-th power quality indicators, where k = 1, 2, 3, 4; This represents the number of times the q-th event occurs per unit of time. Indicates a unit of time;

[0020] The weight of each power quality index is obtained by calculating the Poisson process strength for each power quality index using the Poisson process. :

[0021]

[0022] in, This represents the weight of the k-th power quality indicator;

[0023] Calculate the power quality score for this node based on the weights of the four power quality indicators:

[0024]

[0025] Where nodej represents the j-th node; This represents the power quality score of the j-th node; This represents the score of the k-th power quality indicator in this node.

[0026] Furthermore, the step of obtaining the global power quality assessment result of the microgrid based on the power quality scores of all nodes includes:

[0027] The runtime segments of the microgrid are divided into [n1, n2, ..., n mi ] states;

[0028] The weight of each node in a microgrid under different states is determined by the average power consumption of the node under that state:

[0029]

[0030] in, This represents the average power consumption of the j-th node in the mi-th state of the microgrid. This represents the weight of the j-th node in the mi-th state of the micronetwork;

[0031] Based on the weight of each node, the power quality scores of all nodes are weighted to obtain the global power quality assessment result of the microgrid:

[0032]

[0033] in, This indicates the overall power quality assessment results for the microgrid; This represents the performance quality score of the j-th node in the mi-th state of the microgrid; m represents the total number of nodes. This indicates the number of microgrid operating states.

[0034] Furthermore, the step of classifying the results as medium or poor, and then using a power quality location algorithm to govern the microgrid and achieve global power quality governance optimization for the microgrid, includes:

[0035] When the global power quality assessment result of the microgrid is classified as medium or poor, the power quality positioning algorithm is used to locate the medium or poor node, and then locate the medium power quality index of the medium node, or the poor power quality index of the poor node.

[0036] Based on the positioning results, an inverter control strategy is generated. The inverter control strategy is then sent to the inverters corresponding to the intermediate or poor nodes via communication. By adjusting the inverter strategy, the intermediate or poor nodes in the microgrid are managed, thereby achieving global power quality management and optimization of the microgrid.

[0037] Furthermore, the step of using a power quality location algorithm to manage the microgrid and optimize the global power quality of the microgrid if the results are classified as medium or poor also includes:

[0038] When a microgrid is identified as having voltage or frequency deviations that need to be addressed, the amplitude or frequency of the output voltage of the voltage-source inverter in the microgrid is adjusted to restore the voltage amplitude or frequency and eliminate the corresponding deviation.

[0039] When a microgrid is identified as having three-phase imbalance or harmonic distortion that requires mitigation, the auxiliary mitigation strategy in the inverter of the microgrid is activated, and corresponding compensation current is issued to eliminate the three-phase imbalance or harmonic distortion.

[0040] A collaborative governance system for global optimization of power quality in microgrids, comprising:

[0041] The power quality index acquisition unit is used to acquire power quality index data of each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate.

[0042] The power quality assessment unit is used to calculate the power quality score of a single node based on the power quality index data of each node using the power quality assessment model, and to obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes.

[0043] The power quality positioning unit is used to classify the microgrid according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

[0044] Furthermore, the power quality indicator acquisition unit includes:

[0045] Three-phase voltage Hall sensors are installed at each node to collect voltage data at each node;

[0046] Three-phase current Hall sensors are installed at each node to collect current data at each node;

[0047] The first index calculation unit is used to obtain the voltage deviation by calculating the measured voltage value and the rated voltage value;

[0048] The second index calculation unit is used to obtain the frequency deviation by comparing the measured frequency of the voltage with the rated frequency;

[0049] The third index calculation unit is used to obtain the three-phase unbalance of voltage and current through the positive and negative sequence decomposition algorithm and the three-phase unbalance calculation formula.

[0050] The fourth index calculation unit is used to obtain the harmonic distortion rate of the voltage and current of each node in the microgrid by performing Fourier decomposition and harmonic distortion rate calculation formula on the collected voltage and current.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] This invention uses a power quality assessment model to obtain the global power quality assessment results of the microgrid, and then uses a power quality location algorithm to locate the medium (poor) nodes and medium (poor) power quality indicators in the microgrid. It then sends control strategies to the inverters in the microgrid to change their operating modes, thereby adjusting the power quality of the microgrid and ultimately achieving global power quality governance and optimization of the microgrid. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart of the method of the present invention;

[0055] Figure 2 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0057] It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance, or suggesting any such actual relationship or order between these entities or operations.

[0058] Example:

[0059] The power quality in a microgrid is the result of an overall assessment of the power quality of all nodes in the microgrid. The power quality of each node is affected by the load connected to that node and the status of distributed generation; therefore, different nodes in a microgrid exhibit different power quality issues. This invention is achieved through the following technical solution, such as... Figure 1 As shown, a collaborative governance method for global optimization of power quality in microgrids includes the following steps:

[0060] Step S1: Obtain power quality index data for each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase imbalance, and harmonic distortion rate.

[0061] By collecting voltage and current data at each node using three-phase voltage Hall sensors and three-phase current Hall sensors, and then using a power quality index algorithm, the power quality index data for each node of the microgrid can be obtained. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate.

[0062] Voltage deviation is obtained by calculating the measured voltage value and the rated voltage value; frequency deviation is obtained by comparing the measured voltage frequency with the rated frequency; three-phase unbalance of voltage and current is obtained by using the positive and negative sequence decomposition algorithm and the three-phase unbalance calculation formula; harmonic distortion rate of voltage and current at each node of the microgrid is obtained by performing Fourier decomposition on the collected voltage and current and using the harmonic distortion rate calculation formula.

[0063] Step S2: Input the power quality index data of each node into the power quality assessment model to obtain the power quality score of a single node; then obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes.

[0064] After obtaining the data of each power quality indicator for each node, the four power quality indicators of the node are scored and quantified according to the upper limit values ​​in the power quality standards promulgated by the state as shown in Table 1, so as to obtain the scores corresponding to each power quality indicator of the node.

[0065] Table 1 Power quality standards and scores for each power quality indicator

[0066] Score corresponding to power quality indicators Voltage deviation (%) Frequency deviation (%) Three-phase imbalance (%) Harmonic distortion rate (%) 100 [0,2) [0,0.04) [0,0.4) [0,1) 90 [2,4) [0.04,0.08) [0.4,0.8) [1,2) 80 [4,6) [0.08,0.12) [0.8,1.2) [2,3) 70 [6,8) [0.12,0.16) [1.2,1.6) [3,4) 60 [8,10) [0.16,0.2) [1.6,2) [4,5) 50 ≥10 ≥0.2 ≥2 ≥5

[0067] Table 1 shows the scores for each power quality indicator of a node. For example, if the voltage deviation of a node is 5, the score for the voltage deviation is 80.

[0068] Next, the Poisson process intensity for each power quality indicator is calculated using a Poisson process, and the average number of times a certain event occurs per unit time for each power quality indicator is statistically analyzed.

[0069]

[0070] Among them, the score of a single power quality indicator exceeding the upper limit of the power quality standard is L. U % represents the threshold for the event to occur; Let represent the intensity of the Poisson process occurring in the q-th event among the k-th power quality indicators, where k = 1, 2, 3, 4; This represents the number of times the q-th event occurs per unit of time. Indicates a unit of time;

[0071] The weight of each power quality index is obtained by calculating the Poisson process strength for each power quality index using the Poisson process. :

[0072]

[0073] in, This represents the weight of the k-th power quality indicator;

[0074] Calculate the power quality score for this node based on the weights of the four power quality indicators:

[0075]

[0076] Where nodej represents the j-th node; This represents the power quality score of the j-th node; This represents the score of the k-th power quality indicator in this node.

[0077] Then, the power quality scores of all nodes are combined into the power quality score of the microgrid, thereby obtaining the global power quality assessment result of the microgrid. The weight of each node is determined by the time-sharing factor method, which determines the operating coefficient of the microgrid by judging the operating status of the microgrid at different times, and then obtains the node weight.

[0078] The time-sharing factor method is used to divide the microgrid's runtime segments into [n1, n2, ..., n]. mi ] states;

[0079] The weight of each node in a microgrid under different states is determined by the average power consumption of the node under that state:

[0080]

[0081] in, This represents the average power consumption of the j-th node in the mi-th state of the microgrid. This represents the weight of the j-th node in the mi-th state of the micronetwork;

[0082] Based on the weight of each node, the power quality scores of all nodes are weighted to obtain the global power quality assessment result of the microgrid:

[0083]

[0084] in, This indicates the overall power quality assessment results for the microgrid; This represents the performance quality score of the j-th node in the mi-th state of the microgrid; m represents the total number of nodes. This indicates the number of microgrid operating states.

[0085] Step S3: The microgrid is classified according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

[0086] After obtaining the overall power quality assessment results of the microgrid, the microgrid is divided according to the classification method in Table 2. The classification results include excellent, good, medium and poor, with poor including deviation, poor and worst.

[0087] Table 2 Classification of Microgrid Global Power Quality Assessment Results

[0088] Power quality assessment results (points) 100-90 89-80 79-60 59-50 49-30 30-0 Results Division excellent good middle deviation Poor worst

[0089] If the overall power quality assessment result of the microgrid is classified as excellent or good, the control strategy command for the microgrid inverter remains unchanged. If the overall power quality assessment result of the microgrid is classified as medium or poor, the power quality positioning algorithm includes medium (poor) node positioning and medium (poor) power quality index positioning.

[0090] When the global power quality assessment result of the microgrid is classified as medium or poor, the power quality positioning algorithm is used to locate the medium or poor node, and then locate the medium power quality index of the medium node, or the poor power quality index of the poor node.

[0091] Based on the positioning results, an inverter control strategy is generated. The inverter control strategy is then sent to the inverters corresponding to the intermediate or poor nodes via communication. By adjusting the inverter strategy, the intermediate or poor nodes in the microgrid are managed, thereby achieving global power quality management and optimization of the microgrid.

[0092] When a microgrid is identified as having voltage or frequency deviations requiring mitigation, the amplitude or frequency of the output voltage of the voltage-source inverters in the microgrid is adjusted to restore the voltage amplitude or frequency and eliminate the corresponding deviation. When a microgrid is identified as having three-phase imbalance or harmonic distortion requiring mitigation, the auxiliary mitigation strategy in the inverters of the microgrid is activated, issuing corresponding compensation current to eliminate the three-phase imbalance or harmonic distortion.

[0093] This solution also proposes a collaborative governance system for global optimization of power quality in microgrids. Please refer to [link / reference]. Figure 2 ,include:

[0094] The power quality index acquisition unit is used to acquire power quality index data of each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate.

[0095] The power quality assessment unit is used to calculate the power quality score of a single node based on the power quality index data of each node using the power quality assessment model, and to obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes.

[0096] The power quality positioning unit is used to classify the microgrid according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

[0097] Furthermore, the power quality indicator acquisition unit includes:

[0098] Three-phase voltage Hall sensors are installed at each node to collect voltage data at each node;

[0099] Three-phase current Hall sensors are installed at each node to collect current data at each node;

[0100] The first index calculation unit is used to obtain the voltage deviation by calculating the measured voltage value and the rated voltage value;

[0101] The second index calculation unit is used to obtain the frequency deviation by comparing the measured frequency of the voltage with the rated frequency;

[0102] The third index calculation unit is used to obtain the three-phase unbalance of voltage and current through the positive and negative sequence decomposition algorithm and the three-phase unbalance calculation formula.

[0103] The fourth index calculation unit is used to obtain the harmonic distortion rate of the voltage and current of each node in the microgrid by performing Fourier decomposition and harmonic distortion rate calculation formula on the collected voltage and current.

[0104] The power quality assessment unit includes a node power quality assessment unit and a microgrid power quality assessment unit. The node power quality assessment unit is used to calculate the power quality score of a single node based on the power quality index data of each node using a power quality assessment model. The microgrid power quality assessment unit is used to obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes.

[0105] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A collaborative governance method for global optimization of power quality in microgrids, characterized in that: Includes the following steps: Step S1: Obtain power quality index data for each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate. Step S2: Input the power quality index data of each node into the power quality assessment model to obtain the power quality score of a single node; Then, the global power quality assessment result of the microgrid is obtained based on the power quality scores of all nodes; The step of inputting the power quality index data of each node into the power quality assessment model to obtain the power quality score of a single node includes: The four power quality indicators of the node are scored and quantified according to the upper limit value in the power quality standard to obtain the score corresponding to each power quality indicator of the node. The Poisson process intensity of each power quality indicator is calculated using a Poisson process, and the average number of times a certain event occurs per unit time for each power quality indicator is statistically analyzed. Among them, the score of a single power quality indicator exceeding the upper limit of the power quality standard is L. U % represents the threshold for the event to occur; Let represent the intensity of the Poisson process occurring in the q-th event among the k-th power quality indicators, where k = 1, 2, 3, 4; This represents the number of times the q-th event occurs per unit of time. Indicates a unit of time; The weight of each power quality index is obtained by calculating the Poisson process strength for each power quality index using the Poisson process. : in, This represents the weight of the k-th power quality indicator; Calculate the power quality score for this node based on the weights of the four power quality indicators: Where nodej represents the j-th node; This represents the power quality score of the j-th node; This represents the score of the k-th power quality indicator in this node; Step S3: The microgrid is classified according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

2. The collaborative governance method for global optimization of power quality in microgrids according to claim 1, characterized in that: The steps for obtaining power quality index data for each node in the microgrid include: Voltage and current data of the nodes are collected by three-phase voltage Hall sensors and three-phase current Hall sensors installed at each node. The voltage deviation is obtained by calculating the measured voltage value and the rated voltage value; The frequency deviation is obtained by comparing the measured frequency of the voltage with the rated frequency. The three-phase imbalance degree of voltage and current is obtained by using the positive and negative sequence decomposition algorithm and the three-phase imbalance calculation formula. By performing Fourier decomposition on the collected voltage and current and using the harmonic distortion rate calculation formula, the harmonic distortion rates of the voltage and current at each node of the microgrid are obtained.

3. The collaborative governance method for global optimization of power quality in microgrids according to claim 1, characterized in that: The step of obtaining the global power quality assessment result of the microgrid based on the power quality scores of all nodes includes: The runtime segments of the microgrid are divided into [n1, n2, ..., n mi ] states; The weight of each node in a microgrid under different states is determined by the average power consumption of the node under that state: in, This represents the average power consumption of the j-th node in the mi-th state of the microgrid. This represents the weight of the j-th node in the mi-th state of the micronetwork; Based on the weight of each node, the power quality scores of all nodes are weighted to obtain the global power quality assessment result of the microgrid: in, This indicates the overall power quality assessment results for the microgrid; This represents the performance quality score of the j-th node in the mi-th state of the microgrid; m represents the total number of nodes. This indicates the number of microgrid operating states.

4. The collaborative governance method for global optimization of power quality in microgrids according to claim 1, characterized in that: If the result is classified as medium or poor, the microgrid is then managed using a power quality location algorithm to achieve global power quality management and optimization of the microgrid. This process includes: When the global power quality assessment result of the microgrid is classified as medium or poor, the power quality positioning algorithm is used to locate the medium or poor node, and then locate the medium power quality index of the medium node, or the poor power quality index of the poor node. Based on the positioning results, an inverter control strategy is generated and sent to the inverters corresponding to the intermediate or poor nodes via communication. By adjusting the inverter strategy, the intermediate or poor nodes in the microgrid are managed, thereby achieving global power quality management and optimization of the microgrid.

5. The collaborative governance method for global optimization of power quality in microgrids according to claim 4, characterized in that: The step of classifying the results as medium or poor, and then using a power quality location algorithm to govern the microgrid and achieve global power quality governance optimization of the microgrid, further includes: When a microgrid is identified as having voltage or frequency deviations that need to be addressed, the amplitude or frequency of the output voltage of the voltage-source inverter in the microgrid is adjusted to restore the voltage amplitude or frequency and eliminate the corresponding deviation. When a microgrid is identified as having three-phase imbalance or harmonic distortion that requires mitigation, the auxiliary mitigation strategy in the inverter of the microgrid is activated, and a corresponding compensation current is issued to eliminate the three-phase imbalance or harmonic distortion.

6. A collaborative governance system for global optimization of power quality in microgrids, used to implement the collaborative governance method for global optimization of power quality in microgrids as described in any one of claims 1-5, characterized in that: include: The power quality index acquisition unit is used to acquire power quality index data of each node in the microgrid. The power quality index includes voltage deviation, frequency deviation, three-phase unbalance, and harmonic distortion rate. The power quality assessment unit is used to calculate the power quality score of a single node based on the power quality index data of each node using the power quality assessment model, and to obtain the global power quality assessment result of the microgrid based on the power quality scores of all nodes. The power quality positioning unit is used to classify the microgrid according to the global power quality assessment results. The classification results include excellent, good, medium, and poor. If the result is classified as medium or poor, the microgrid is managed through the power quality positioning algorithm to achieve global power quality management and optimization of the microgrid.

7. A collaborative governance system for global optimization of power quality in microgrids according to claim 6, characterized in that: The power quality indicator acquisition unit includes: Three-phase voltage Hall sensors are installed at each node to collect voltage data at each node; Three-phase current Hall sensors are installed at each node to collect current data at each node; The first index calculation unit is used to obtain the voltage deviation by calculating the measured voltage value and the rated voltage value; The second index calculation unit is used to obtain the frequency deviation by comparing the measured frequency of the voltage with the rated frequency; The third index calculation unit is used to obtain the three-phase unbalance of voltage and current through the positive and negative sequence decomposition algorithm and the three-phase unbalance calculation formula. The fourth index calculation unit is used to obtain the harmonic distortion rate of the voltage and current of each node in the microgrid by performing Fourier decomposition and harmonic distortion rate calculation formula on the collected voltage and current.

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