Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384971
A. Farhadi, A. Zakerian, M. Bina
Matrix converters in high-power applications have certain constraints such as high total harmonic distortion (THD) of the source current as well as significant switching power losses. This study presents an advanced finite control set model predictive control (FCS-MPC) for a three-level indirect matrix converter to address these problems. To do this, a novel constraint is introduced in the cost function of the proposed FCS-MPC method to reduce the switching frequency while improving the quality of the source current. The results show that by decreasing the switching frequency by 3.4 kHz, the proposed method can further diminish the THD of the supply current by approximately 4% compared to the conventional methods. The effectiveness of the proposed method is validated through the simulations in Matlab/Simulink.
{"title":"Enhanced Finite Control Set Model Predictive Control for a Diode-Clamped Indirect Matrix Converter","authors":"A. Farhadi, A. Zakerian, M. Bina","doi":"10.1109/TPEC51183.2021.9384971","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384971","url":null,"abstract":"Matrix converters in high-power applications have certain constraints such as high total harmonic distortion (THD) of the source current as well as significant switching power losses. This study presents an advanced finite control set model predictive control (FCS-MPC) for a three-level indirect matrix converter to address these problems. To do this, a novel constraint is introduced in the cost function of the proposed FCS-MPC method to reduce the switching frequency while improving the quality of the source current. The results show that by decreasing the switching frequency by 3.4 kHz, the proposed method can further diminish the THD of the supply current by approximately 4% compared to the conventional methods. The effectiveness of the proposed method is validated through the simulations in Matlab/Simulink.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133734720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384936
O. Montoya, Luis Rueda, W. Gil-González, A. Molina-Cabrera, H. Chamorro, Milad Soleimani
This paper deals with new power flow formulations for AC distribution networks. The power flow problem is approximated using Laurent's series expansion method over the product between voltage variables in the power balance equations, which proportionates a mathematical structure similar to the conventional Newton-Raphson method. The proposed model is developed in complex variables, which decreases the number of calculations needed and prevents the transformation of the load flow model into polar coordinates. Numerical results confirm that the proposed method is faster regarding computational time and the total number of iterations required; besides, one of the main advantages of this approach is dealing with radial or mesh grids. All simulations are conducted in the programming environment in MATLAB software.
{"title":"On the Power Flow Solution in AC Distribution Networks Using the Laurent's Series Expansion","authors":"O. Montoya, Luis Rueda, W. Gil-González, A. Molina-Cabrera, H. Chamorro, Milad Soleimani","doi":"10.1109/TPEC51183.2021.9384936","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384936","url":null,"abstract":"This paper deals with new power flow formulations for AC distribution networks. The power flow problem is approximated using Laurent's series expansion method over the product between voltage variables in the power balance equations, which proportionates a mathematical structure similar to the conventional Newton-Raphson method. The proposed model is developed in complex variables, which decreases the number of calculations needed and prevents the transformation of the load flow model into polar coordinates. Numerical results confirm that the proposed method is faster regarding computational time and the total number of iterations required; besides, one of the main advantages of this approach is dealing with radial or mesh grids. All simulations are conducted in the programming environment in MATLAB software.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134640505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384975
Salahaldein Ahmed, Zhong Chen
Compared to conventional Buck, the automatic current sharing mechanism is one technical advantage of the two-phase series capacitor buck converter (2-pscB), but this benefit is generally not enough to justify the limitation of output load potential. The other very important advantage is the simplified control scheme with fewer current sensing loops, as claimed in the previous publication. To fill in the gap and better understand the differences between these two topologies, this paper provides a complete comparison. Theoretical and experimental analysis of 2-pscB with a signal-variation model and the parasitic component linearization are developed to design a robust controller and to satisfy the stability and performance of the converter. The current sharing tolerance mechanism and switching node voltages in the frequency domain were as predicted. Heat distribution was not that good due to the circuit layout.
{"title":"A Comparison between Conventional Buck and 2-pscB DC-DC Converters","authors":"Salahaldein Ahmed, Zhong Chen","doi":"10.1109/TPEC51183.2021.9384975","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384975","url":null,"abstract":"Compared to conventional Buck, the automatic current sharing mechanism is one technical advantage of the two-phase series capacitor buck converter (2-pscB), but this benefit is generally not enough to justify the limitation of output load potential. The other very important advantage is the simplified control scheme with fewer current sensing loops, as claimed in the previous publication. To fill in the gap and better understand the differences between these two topologies, this paper provides a complete comparison. Theoretical and experimental analysis of 2-pscB with a signal-variation model and the parasitic component linearization are developed to design a robust controller and to satisfy the stability and performance of the converter. The current sharing tolerance mechanism and switching node voltages in the frequency domain were as predicted. Heat distribution was not that good due to the circuit layout.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134434080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384940
M. E. Bento, R. Ramos
The operation of power systems requires requirements to ensure a continuous and secure supply of electricity. One of the requirements is the appropriate damping of low-frequency oscillation modes in small-signal stability studies. The expansion and uncertainties of power systems combined with the development of Wide-Area Measurement Systems led to the development of Wide-Area Damping Controllers (WADCs) whose measures are derived from Phasor Measurement Units (PMU) measures. Possible failures in the transmission of data packets from PMUs can compromise the proper operation of the WADC and thus compromise the stability of the system. This research proposes an optimization model for the WADC design considering the minimization of the input-output signals of the controller and the robustness of the loss of a communication channel. Case studies are presented and discussed using a set of Nature-Inspired Meta-Heuristic Algorithms applied to the proposed optimization method.
{"title":"Selecting the Input-Output Signals for Fault-Tolerant Wide-Area Damping Control Design","authors":"M. E. Bento, R. Ramos","doi":"10.1109/TPEC51183.2021.9384940","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384940","url":null,"abstract":"The operation of power systems requires requirements to ensure a continuous and secure supply of electricity. One of the requirements is the appropriate damping of low-frequency oscillation modes in small-signal stability studies. The expansion and uncertainties of power systems combined with the development of Wide-Area Measurement Systems led to the development of Wide-Area Damping Controllers (WADCs) whose measures are derived from Phasor Measurement Units (PMU) measures. Possible failures in the transmission of data packets from PMUs can compromise the proper operation of the WADC and thus compromise the stability of the system. This research proposes an optimization model for the WADC design considering the minimization of the input-output signals of the controller and the robustness of the loss of a communication channel. Case studies are presented and discussed using a set of Nature-Inspired Meta-Heuristic Algorithms applied to the proposed optimization method.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127732111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384991
Hesam Mazaheri, Mohammad Khoshiahan, M. Moeini‐Aghtaie, M. Fotuhi‐Firuzabad
Energy storage systems (ESSs) play a vital role in dealing with uncertainties originated from the intermittent power generation of renewable energy sources (RESs) leading to improvement of flexibility and reliability of power systems. Needless to say, a key factor is selecting the best technology of ESSs which yields to maximum leverage of ESSs presence in power systems. On this basis, in this paper, a mixed integer linear programming (MILP) direct-optimization model is proposed to effectively mitigate the impacts of insufficient transmission lines capacities by installation of different ESS technologies using a DC optimal power flow model. Firstly, a precise model for the technical constraints and operational cost of each type of ESSs is developed. Further, the impacts of different ESS technologies on power system total cost and power system reliability are investigated in order to find the best option under the given system circumstances. The proposed model is applied to the modified RTS 24-bus test system with high wind power generation. A sensitivity analysis is performed on the wind power increment based on real historical RESs uncertainties. The numerical results demonstrate the effectiveness of different ESS technologies to overcome the mentioned challenges and justify that battery energy storage system (BESS) is the best fit in our case studies.
{"title":"Investigating the Effects of ESS Technologies on High Wind-Penetration Power Grids Considering Reliability Indices","authors":"Hesam Mazaheri, Mohammad Khoshiahan, M. Moeini‐Aghtaie, M. Fotuhi‐Firuzabad","doi":"10.1109/TPEC51183.2021.9384991","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384991","url":null,"abstract":"Energy storage systems (ESSs) play a vital role in dealing with uncertainties originated from the intermittent power generation of renewable energy sources (RESs) leading to improvement of flexibility and reliability of power systems. Needless to say, a key factor is selecting the best technology of ESSs which yields to maximum leverage of ESSs presence in power systems. On this basis, in this paper, a mixed integer linear programming (MILP) direct-optimization model is proposed to effectively mitigate the impacts of insufficient transmission lines capacities by installation of different ESS technologies using a DC optimal power flow model. Firstly, a precise model for the technical constraints and operational cost of each type of ESSs is developed. Further, the impacts of different ESS technologies on power system total cost and power system reliability are investigated in order to find the best option under the given system circumstances. The proposed model is applied to the modified RTS 24-bus test system with high wind power generation. A sensitivity analysis is performed on the wind power increment based on real historical RESs uncertainties. The numerical results demonstrate the effectiveness of different ESS technologies to overcome the mentioned challenges and justify that battery energy storage system (BESS) is the best fit in our case studies.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117132805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384962
Ramin Tafazzoli Mehrjardi, Nima Farrokhzad Ershad, Babak Rahrovi, M. Ehsani
The Cascaded (Brushless) Doubly-Fed Induction Machine (CDFIM) is a promising substitute for the commonly used Doubly-Fed Induction Machines (DFIM) for wind power application. The CDFIM offers reliable performance and low maintenance due to the absence of slip rings and graphite brushes. In this study, a detailed analytical model for the CDFIM is proposed in order to clearly show the input (i.e., current from inverter side) and output (i.e., total output torque) relationship. The proposed model is expressed in the frequency (Laplace) domain. Field oriented (i.e., vector) control approach is adopted in order to achieve a precise dynamic model for the grid connected CDFIM. Each term of the derived relationship is classified into the possible types of torque based on the term's nature and then is discussed in detail. Then, the steady state and dynamic behavior of these terms are presented and explained individually. The total output torque dynamic response is calculated both analytically and numerically in a simulation environment, and the results are compared.
{"title":"A Precise Analytical Model of the Grid Connected Cascaded Doubly Fed Induction Machine","authors":"Ramin Tafazzoli Mehrjardi, Nima Farrokhzad Ershad, Babak Rahrovi, M. Ehsani","doi":"10.1109/TPEC51183.2021.9384962","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384962","url":null,"abstract":"The Cascaded (Brushless) Doubly-Fed Induction Machine (CDFIM) is a promising substitute for the commonly used Doubly-Fed Induction Machines (DFIM) for wind power application. The CDFIM offers reliable performance and low maintenance due to the absence of slip rings and graphite brushes. In this study, a detailed analytical model for the CDFIM is proposed in order to clearly show the input (i.e., current from inverter side) and output (i.e., total output torque) relationship. The proposed model is expressed in the frequency (Laplace) domain. Field oriented (i.e., vector) control approach is adopted in order to achieve a precise dynamic model for the grid connected CDFIM. Each term of the derived relationship is classified into the possible types of torque based on the term's nature and then is discussed in detail. Then, the steady state and dynamic behavior of these terms are presented and explained individually. The total output torque dynamic response is calculated both analytically and numerically in a simulation environment, and the results are compared.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115692971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384976
A. Ahmed, M. Nadeem, Arooj Tariq Kiani, I. Khan
Proliferation of electric demand and congestion in the existing network intensify challenges and problems for researchers and power system planners. Currently, these problems are mostly solved by Distributed Generation (DG). DG is placed near the customer end to meet the load demand economically, hence reducing the existing network burden. This paper attempts to present an overview of technological development carried out in the DG field. Numerous technical constraints must be considered while integrating DG in the system. The improvement in voltage stability, voltage profile, and reduction in power losses are the main benefits posed by DG integration. This paper also highlights the key issues associated with the DG allocation problem, types of DG, and methodologies for optimal DG units allocation.
{"title":"An Overview on Optimal Planning of Distributed Generation in Distribution System and Key Issues","authors":"A. Ahmed, M. Nadeem, Arooj Tariq Kiani, I. Khan","doi":"10.1109/TPEC51183.2021.9384976","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384976","url":null,"abstract":"Proliferation of electric demand and congestion in the existing network intensify challenges and problems for researchers and power system planners. Currently, these problems are mostly solved by Distributed Generation (DG). DG is placed near the customer end to meet the load demand economically, hence reducing the existing network burden. This paper attempts to present an overview of technological development carried out in the DG field. Numerous technical constraints must be considered while integrating DG in the system. The improvement in voltage stability, voltage profile, and reduction in power losses are the main benefits posed by DG integration. This paper also highlights the key issues associated with the DG allocation problem, types of DG, and methodologies for optimal DG units allocation.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384919
M. Shivaie, Mohammad Mokhayeri, M. Narooie, M. Ansari
With the ever-increasing energy demand and enormous development of generation capacity, modern bulk power systems are mostly pushed to operate with narrower security boundaries. Therefore, timely and reliable assessment of power system security is an inevitable necessity to prevent widespread blackouts and cascading outages. In this paper, a new white-box decision tree-based preventive strategy is presented to evaluate and enhance the power system dynamic security versus the credible N-K contingencies originating from transient instabilities. As well, a competent operating measure is expertly defined to detect and identify the islanding and non-islanding conditions with the aid of a wide-area phasor measurement system. The newly developed strategy is outlined by a three-level simulation with the aim of guaranteeing the power system dynamic security. In the first-level, six hundred islanding and non-islanding scenarios are generated using an enhanced version of the ID3 algorithm, referred to as the C4.5 algorithms. In the second-level, optimal C4.5 decision trees are offline trained based on operating parameters achieved by the reduction error pruning method. In the third level, however, all trained decision trees are rigorously investigated offline and online; and then, the most accurate and reliable decision tree is selected. The newly developed strategy is examined on the IEEE New England 39-bus test system, and its effectiveness is assured by simulation studies.
{"title":"A White-Box Decision Tree-Based Preventive Strategy for Real-Time Islanding Detection Using Wide-Area Phasor Measurement","authors":"M. Shivaie, Mohammad Mokhayeri, M. Narooie, M. Ansari","doi":"10.1109/TPEC51183.2021.9384919","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384919","url":null,"abstract":"With the ever-increasing energy demand and enormous development of generation capacity, modern bulk power systems are mostly pushed to operate with narrower security boundaries. Therefore, timely and reliable assessment of power system security is an inevitable necessity to prevent widespread blackouts and cascading outages. In this paper, a new white-box decision tree-based preventive strategy is presented to evaluate and enhance the power system dynamic security versus the credible N-K contingencies originating from transient instabilities. As well, a competent operating measure is expertly defined to detect and identify the islanding and non-islanding conditions with the aid of a wide-area phasor measurement system. The newly developed strategy is outlined by a three-level simulation with the aim of guaranteeing the power system dynamic security. In the first-level, six hundred islanding and non-islanding scenarios are generated using an enhanced version of the ID3 algorithm, referred to as the C4.5 algorithms. In the second-level, optimal C4.5 decision trees are offline trained based on operating parameters achieved by the reduction error pruning method. In the third level, however, all trained decision trees are rigorously investigated offline and online; and then, the most accurate and reliable decision tree is selected. The newly developed strategy is examined on the IEEE New England 39-bus test system, and its effectiveness is assured by simulation studies.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123407829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384944
Sadegh Vejdan, K. Mason, S. Grijalva
Increased penetration of behind-the-meter (BTM) PV installations can cause numerous challenges in planning and operation of distribution systems. Utilities must accurately record the installed PVs in their territory and keep their PV database updated. However, many utilities do not have enough visibility on the actual installed PVs due the growing number of unauthorized PV installations as well as the complexity of data tracking and updating the databases even for authorized PVs. In this paper, a data-driven classification method is proposed for detecting BTM PV installation using convolutional neural networks and synthetic net load profiles generated from AMI data. The network is trained and tested on 50 folds of the dataset and the testing classification accuracy per each fold is calculated. Results show that the median of per-fold testing accuracies is 98.9%. In terms of average error, only 0.7% of the customers with PV are not detected. This is significantly less than the 6% error in the next best method. The impact of training data parameters, such as the size of dataset and label errors on the accuracy and computational time of the method is also studied and characterized. Using only the available AMI data, the proposed method can help utilities accurately monitor BTM PV systems and keep their databases updated and thus avoid the costs of operation and planning errors.
{"title":"Detecting Behind-the-Meter PV Installation Using Convolutional Neural Networks","authors":"Sadegh Vejdan, K. Mason, S. Grijalva","doi":"10.1109/TPEC51183.2021.9384944","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384944","url":null,"abstract":"Increased penetration of behind-the-meter (BTM) PV installations can cause numerous challenges in planning and operation of distribution systems. Utilities must accurately record the installed PVs in their territory and keep their PV database updated. However, many utilities do not have enough visibility on the actual installed PVs due the growing number of unauthorized PV installations as well as the complexity of data tracking and updating the databases even for authorized PVs. In this paper, a data-driven classification method is proposed for detecting BTM PV installation using convolutional neural networks and synthetic net load profiles generated from AMI data. The network is trained and tested on 50 folds of the dataset and the testing classification accuracy per each fold is calculated. Results show that the median of per-fold testing accuracies is 98.9%. In terms of average error, only 0.7% of the customers with PV are not detected. This is significantly less than the 6% error in the next best method. The impact of training data parameters, such as the size of dataset and label errors on the accuracy and computational time of the method is also studied and characterized. Using only the available AMI data, the proposed method can help utilities accurately monitor BTM PV systems and keep their databases updated and thus avoid the costs of operation and planning errors.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121816102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384923
M. A. Hannan, R. Mohamed, Maher G. M. Abdolrasol, A. Al-Shetwi, P. Ker, R. A. Begum, K. Muttaqi
This paper reports of an artificial neural network (ANN) based binary backtracking search algorithm (BBSA) for optimal scheduling controller applied in IEEE 14-bus system for controlling microgrids (MGs) formed virtual power plant (VPP) The model was simulated and validated on actual parameters and load data. The algorithm deals with best binary fitness function to find the best cell and creates the optimum scheduling using the actual data for wind speed, solar radiation, fuel conditions, battery charging/discharging, and specific hour demand. The goal is to regulate the power-sharing via prioritizing the utilization of renewable sources in lieu of the national grid purchases. The developed ANN-based BBSA controller predicts the optimal schedules of the sources via ON and OFF status. The 25 DGs showed the enhancement of ANN-BBSA gives a mean absolute error (MAE) of 6.2e−3 with a correlation coefficient of 0.99993, which is closed to 1. The results showed a significant reduction in the cost and emission by 41.88% and 40.7%, respectively. The developed algorithms reduced the energy cost while delivered reliable power towards grid decarbonization.
{"title":"ANN based binary backtracking search algorithm for virtual power plant scheduling and cost-effective evaluation","authors":"M. A. Hannan, R. Mohamed, Maher G. M. Abdolrasol, A. Al-Shetwi, P. Ker, R. A. Begum, K. Muttaqi","doi":"10.1109/TPEC51183.2021.9384923","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384923","url":null,"abstract":"This paper reports of an artificial neural network (ANN) based binary backtracking search algorithm (BBSA) for optimal scheduling controller applied in IEEE 14-bus system for controlling microgrids (MGs) formed virtual power plant (VPP) The model was simulated and validated on actual parameters and load data. The algorithm deals with best binary fitness function to find the best cell and creates the optimum scheduling using the actual data for wind speed, solar radiation, fuel conditions, battery charging/discharging, and specific hour demand. The goal is to regulate the power-sharing via prioritizing the utilization of renewable sources in lieu of the national grid purchases. The developed ANN-based BBSA controller predicts the optimal schedules of the sources via ON and OFF status. The 25 DGs showed the enhancement of ANN-BBSA gives a mean absolute error (MAE) of 6.2e−3 with a correlation coefficient of 0.99993, which is closed to 1. The results showed a significant reduction in the cost and emission by 41.88% and 40.7%, respectively. The developed algorithms reduced the energy cost while delivered reliable power towards grid decarbonization.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133478845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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