Electric Network Performance Assessment Methodology Using Fuzzy Logic
Keywords:
electric networks, electric power supply reliability, electric power quality, energy efficiency, electric power loss, current density, transmission capacity, fuzzy logic, Mamdani method
Abstract
The article discusses a methodology for assessing the performane of electrical networks using fuzzy logic, which makes it possible to take into account parameter uncertainties and achieve better accuracy of the analysis. The main focus is placed on the key factors: electric power quality, power supply reliability, and electric energy loss. Membership functions and control algorithms based on the Mamdani method have been developed for each factor. The article presents the results of experimental studies conducted under real conditions at the facilities of the Ferghana district (Ferghana region), which have confirmed the effectiveness of the proposed approach. The methodology helps optimize the operation of distribution networks, minimize electric power loss and improve the overall performance of the system. The results obtained demonstrate the possibility of using fuzzy logic to automate the control process of distribution electric networks. The prospects of integrating the proposed methodology with the latest technologies such as the Internet of Things (IoT) are discussed, which opens additional opportunities for development of intelligent power supply management systems. The proposed approach facilitates the transition from planned to predictive maintenance, which makes it possible to ensure the rational use of resources and improve the electric power supply reliability.
References
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2. Singh B., Chauhan S., Reddy C.C. Power Loss Minimization in Electrical Power Distribution Networks by Use of Hybrid Reconfiguration Method. – 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), 2017, DOI: 10.1109/CATCON.2017.8280243.
3. Dautbašić N. et al. Selection of Location and Power of Photovoltaic Plant in Distribution Network Using Fuzzy Logic. – XXIX International Conference on Information, Communication and Automation Technologies (ICAT), 2023, DOI: 10.1109/ICAT57854. 2023.10171270.
4. Kanirajan P., Joly M. Fuzzy Expert System for Recognition of Power Quality Disturbances. – WSEAS Transactions on Electronics, 2020, vol. 11, DOI: 10.37394/232017.2020.11.8.
5. Buragohain U., Boruah T. Fuzzy Logic Based Load Flow Analysis. – International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–6, DOI: 10.1109/ICAMMAET.2017.8186736.
6. Ahmetovic H., Saric M., Hivziefendic J. Reliability Based Power Distribution Network Planning Using Fuzzy Logic, 2021, Power Engineering and Electrical Engineering, vol. 19, No. 2, DOI: 10.15598/aeee.v19i2.4011.
7. Adeel S. et al. Еstimatiоn of Pоwеr Quality in Distributiоn Systеm Using Fuzzy Lоgic Thеоry. – Indоnеsian Jоurnal оf Еlеctrical Еnginееring and Cоmputеr Sciеncе, 2023, vоl. 32, Nо. 3, pp. 1236–1245, DOI: 10.11591/IJEECS.V32.I3.PP1236-1245.
8. Khоliddinоv I. et al. Еstimatiоn thе Statе of Pоwеr Quality in Distributiоn Nеtwоrks Using Fuzzy Lоgic. – XVI International Scientific-Practical Conference on Actual Problems of Improving Farming Productivity and Agroecology, 2024, vol. 538, DОI: 10.1051/е3scоnf/202453801011.
9. Штовба С.Д. Проектирование нечетких систем средствами MATLAB. М: Горячая линия–Телеком, 2007, 288 с.
10. Коверникова Л.И. и др. Качество электрической энергии: современное состояние, проблемы и предложения по их решению. Новосибирск: Наука, 2017, 219 с.
11. Kholiddinov I. K. et al. Nоvеl Mеthоd оf Calculating thе Cоеfficiеnt оf Asymmеtry in thе Nеgativе Sеquеncе. – 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2023, DОI: 10.1109/ICOMET57998.2023.10099113.
12. Шабалин А.И. Влияние несинусоидальности и несимметрии напряжения на протяженные сети 0,4 кВ. – Молодой ученый, 2020, № 20, с. 159–161.
13. Малафеев А.В., Юлдашева А.И. Количественная оценка производственных рисков при принятии решений по управлению и реконструкции системы электроснабжения крупного промышленного предприятия. – Вестник ИГЭУ, 2016, № 3, с. 55–62.
14. Kholiddinov I. On the Method of Calculating the Coefficient of Asymmetry in the Reverse Sequence. – AIP Conference Proceedings, 2023, vol. 2789, DOI: 10.1063/5.0145463.
15. Еmjеdi M.R. et al. Rеliability еvaluatiоn оf distributiоn nеtwоrks using fuzzy lоgic. – IEEE PES General Meeting, 2010, DОI: 10.1109/PES.2010.5589702.
16. Wu Y. et al. Risk Assеssmеnt on Оffshоrе Phоtоvоltaic Pоwеr Gеnеratiоn Prоjеcts in China Basеd on a Fuzzy Analysis Framеwоrk. – Journal of Cleaner Production, 2019, vоl. 215, pp. 46–62, DOI: 10.1016/J.JCLEPRO.2019.01.024.
17. Piassоn D. et al. A Prоpоsal fоr Rеliability Еvaluatiоn of Components on Electric Power Distribution Systеm Intеgrating Prоbabilistic Mоdеls and Fuzzy Infеrеncе Systеms. – 6th IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012, DОI: 10.1109/TDC-LA.2012.6319094.
18. Allaev K.R. et al. Evaluation of Additional Electricity Losses in Electric Networks Using a Meter. – Indonesian Journal of Electrical Engineering and Computer Science, 2023, 31(2), pp. 617–625, DOI: 10.11591/ijeecs.v31.i2.pp617-625.
19. Леоненков А.В. Нечеткое моделирование в среде MATLAB и fuzzyTECH. СПб.: БХВ-Петербург, 2003, 736 с.
20. Мухамедиева Д.Т. Алгоритм обучения матричного представления нечетких систем логического вывода. – Международный журнал теоретических и прикладных вопросов цифровых технологий, 2022, № 2, с. 85–93.
21. ГОСТ 32144-2013. Электрическая энергия. Совместимость технических средств электромагнитная. Нормы качества электроэнергии в системах электроснабжения общего назначения. М.: Стандартинформ, 2014, 16 с.
#
1. Wang T. et al. Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems. – IEEE Transactions on Power Systems, 2014, vol. 30, pp. 1182–1194, DOI: 10.1109/TPWRS.2014.2347699.
2. Singh B., Chauhan S., Reddy C.C. Power Loss Minimization in Electrical Power Distribution Networks by Use of Hybrid Reconfiguration Method. – 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), 2017, DOI: 10.1109/CATCON.2017.8280243.
3. Dautbašić N. et al. Selection of Location and Power of Photovoltaic Plant in Distribution Network Using Fuzzy Logic. – XXIX International Conference on Information, Communication and Automation Technologies (ICAT), 2023, DOI: 10.1109/ICAT57854. 2023.10171270.
4. Kanirajan P., Joly M. Fuzzy Expert System for Recognition of Power Quality Disturbances. – WSEAS Transactions on Electronics, 2020, vol. 11, DOI: 10.37394/232017.2020.11.8.
5. Buragohain U., Boruah T. Fuzzy Logic Based Load Flow Analysis. – International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–6, DOI: 10.1109/ICAMMAET.2017.8186736.
6. Ahmetovic H., Saric M., Hivziefendic J. Reliability Based Power Distribution Network Planning Using Fuzzy Logic, 2021, Power Engineering and Electrical Engineering, vol. 19, No. 2, DOI: 10.15598/aeee.v19i2.4011.
7. Adeel S. et al. Еstimatiоn of Pоwеr Quality in Distributiоn Systеm Using Fuzzy Lоgic Thеоry. – Indоnеsian Jоurnal оf Еlеctrical Еnginееring and Cоmputеr Sciеncе, 2023, vоl. 32, Nо. 3, pp. 1236–1245, DOI: 10.11591/IJEECS.V32.I3.PP1236-1245.
8. Khоliddinоv I. et al. Еstimatiоn thе Statе of Pоwеr Quality in Distributiоn Nеtwоrks Using Fuzzy Lоgic. – XVI International Scientific-Practical Conference on Actual Problems of Improving Farming Productivity and Agroecology, 2024, vol. 538, DОI: 10.1051/е3scоnf/202453801011.
9. Shtovba S.D. Proektirovanie nechetkikh sistem sredstvami MATLAB (Designing Fuzzy Systems Using MATLAB). M: Goryachaya liniya – Telekom, 2007, 288 pp.
10. Kovernikova L.I. et al. Kachestvo elektricheskoy energii: sovremennoe sostoyanie, problemy i predlozheniya po ikh resheniyu (Quality of Electric Energy: Current State, Problems and Suggestions for Their Solution). Novosibirsk: Nauka, 2017, 219 p.
11. Kholiddinov I. K. et al. Nоvеl Mеthоd оf Calculating thе Cоеfficiеnt оf Asymmеtry in thе Nеgativе Sеquеncе. – 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2023, DОI: 10.1109/ICOMET57998.2023.10099113.
12. Shabalin A.I. Molodoy uchenyy – in Russ. (Young Scientist), 2020, No. 20, pp 159–161.
13. Malafeev A.V., Yuldasheva A.I. Vestnik IGEU – in Russ. (Bulletin of the Ivanovo State Energy University), 2016, No. 3, pp. 55–62.
14. Kholiddinov I. On the Method of Calculating the Coefficient of Asymmetry in the Reverse Sequence. – AIP Conference Proceedings, 2023, vol. 2789, DOI: 10.1063/5.0145463.
15. Еmjеdi M.R. et al. Rеliability Еvaluatiоn of Distributiоn Nеtwоrks Using Fuzzy Lоgic. – IEEE PES General Meeting, 2010, DОI: 10.1109/PES.2010.5589702.
16. Wu Y. et al. Risk Assеssmеnt on Оffshоrе Phоtоvоltaic Pоwеr Gеnеratiоn Prоjеcts in China Basеd on a Fuzzy Analysis Framеwоrk. – Journal of Cleaner Production, 2019, vоl. 215, pp. 46–62, DOI: 10.1016/J.JCLEPRO.2019.01.024.
17. Piassоn D. et al. A Prоpоsal fоr Rеliability Еvaluatiоn of Components on Electric Power Distribution Systеm Intеgrating Prоbabilistic Mоdеls and Fuzzy Infеrеncе Systеms. – 6th IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012, DОI: 10.1109/TDC-LA.2012.6319094.
18. Allaev K.R. et al. Evaluation of Additional Electricity Losses in Electric Networks Using a Meter. – Indonesian Journal of Electrical Engineering and Computer Science, 2023, 31(2), pp. 617–625, DOI: 10.11591/ijeecs.v31.i2.pp617-625.
19. Leonenkov A.V. Nechetkoye modelirovaniye v srede MATLAB i fuzzyTECH (Fuzzy Modeling in MATLAB and FuzzyTECH Environments). SPb.: BKhV-Peterburg, 2003, 736 p.
20. Mukhamediyeva D.T. Mezhdunarodnyy zhurnal teoreticheskikh i prikladnykh voprosov tsifrovykh tekhnologiy – in Russ. (Inter-national Journal of Theoretical and Applied Issues of Digital Techno-logies), 2022, No. 2, pp. 85–93.
21. GOST 32144-2013. Elektricheskaya energiya. Sovmestimost’ tehnicheskih sredstv elektromagnitnaya. Normy kachestva elektroenergii v sistemah elektrosnabzheniya obshchego naznacheniya (Electrical Energy. Electromagnetic Compatibility of Technical Means. Electricity Quality Standards in General Purpose Power Supply Systems). M.: Standartinform, 2014, 19 p
2. Singh B., Chauhan S., Reddy C.C. Power Loss Minimization in Electrical Power Distribution Networks by Use of Hybrid Reconfiguration Method. – 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), 2017, DOI: 10.1109/CATCON.2017.8280243.
3. Dautbašić N. et al. Selection of Location and Power of Photovoltaic Plant in Distribution Network Using Fuzzy Logic. – XXIX International Conference on Information, Communication and Automation Technologies (ICAT), 2023, DOI: 10.1109/ICAT57854. 2023.10171270.
4. Kanirajan P., Joly M. Fuzzy Expert System for Recognition of Power Quality Disturbances. – WSEAS Transactions on Electronics, 2020, vol. 11, DOI: 10.37394/232017.2020.11.8.
5. Buragohain U., Boruah T. Fuzzy Logic Based Load Flow Analysis. – International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–6, DOI: 10.1109/ICAMMAET.2017.8186736.
6. Ahmetovic H., Saric M., Hivziefendic J. Reliability Based Power Distribution Network Planning Using Fuzzy Logic, 2021, Power Engineering and Electrical Engineering, vol. 19, No. 2, DOI: 10.15598/aeee.v19i2.4011.
7. Adeel S. et al. Еstimatiоn of Pоwеr Quality in Distributiоn Systеm Using Fuzzy Lоgic Thеоry. – Indоnеsian Jоurnal оf Еlеctrical Еnginееring and Cоmputеr Sciеncе, 2023, vоl. 32, Nо. 3, pp. 1236–1245, DOI: 10.11591/IJEECS.V32.I3.PP1236-1245.
8. Khоliddinоv I. et al. Еstimatiоn thе Statе of Pоwеr Quality in Distributiоn Nеtwоrks Using Fuzzy Lоgic. – XVI International Scientific-Practical Conference on Actual Problems of Improving Farming Productivity and Agroecology, 2024, vol. 538, DОI: 10.1051/е3scоnf/202453801011.
9. Штовба С.Д. Проектирование нечетких систем средствами MATLAB. М: Горячая линия–Телеком, 2007, 288 с.
10. Коверникова Л.И. и др. Качество электрической энергии: современное состояние, проблемы и предложения по их решению. Новосибирск: Наука, 2017, 219 с.
11. Kholiddinov I. K. et al. Nоvеl Mеthоd оf Calculating thе Cоеfficiеnt оf Asymmеtry in thе Nеgativе Sеquеncе. – 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2023, DОI: 10.1109/ICOMET57998.2023.10099113.
12. Шабалин А.И. Влияние несинусоидальности и несимметрии напряжения на протяженные сети 0,4 кВ. – Молодой ученый, 2020, № 20, с. 159–161.
13. Малафеев А.В., Юлдашева А.И. Количественная оценка производственных рисков при принятии решений по управлению и реконструкции системы электроснабжения крупного промышленного предприятия. – Вестник ИГЭУ, 2016, № 3, с. 55–62.
14. Kholiddinov I. On the Method of Calculating the Coefficient of Asymmetry in the Reverse Sequence. – AIP Conference Proceedings, 2023, vol. 2789, DOI: 10.1063/5.0145463.
15. Еmjеdi M.R. et al. Rеliability еvaluatiоn оf distributiоn nеtwоrks using fuzzy lоgic. – IEEE PES General Meeting, 2010, DОI: 10.1109/PES.2010.5589702.
16. Wu Y. et al. Risk Assеssmеnt on Оffshоrе Phоtоvоltaic Pоwеr Gеnеratiоn Prоjеcts in China Basеd on a Fuzzy Analysis Framеwоrk. – Journal of Cleaner Production, 2019, vоl. 215, pp. 46–62, DOI: 10.1016/J.JCLEPRO.2019.01.024.
17. Piassоn D. et al. A Prоpоsal fоr Rеliability Еvaluatiоn of Components on Electric Power Distribution Systеm Intеgrating Prоbabilistic Mоdеls and Fuzzy Infеrеncе Systеms. – 6th IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012, DОI: 10.1109/TDC-LA.2012.6319094.
18. Allaev K.R. et al. Evaluation of Additional Electricity Losses in Electric Networks Using a Meter. – Indonesian Journal of Electrical Engineering and Computer Science, 2023, 31(2), pp. 617–625, DOI: 10.11591/ijeecs.v31.i2.pp617-625.
19. Леоненков А.В. Нечеткое моделирование в среде MATLAB и fuzzyTECH. СПб.: БХВ-Петербург, 2003, 736 с.
20. Мухамедиева Д.Т. Алгоритм обучения матричного представления нечетких систем логического вывода. – Международный журнал теоретических и прикладных вопросов цифровых технологий, 2022, № 2, с. 85–93.
21. ГОСТ 32144-2013. Электрическая энергия. Совместимость технических средств электромагнитная. Нормы качества электроэнергии в системах электроснабжения общего назначения. М.: Стандартинформ, 2014, 16 с.
#
1. Wang T. et al. Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems. – IEEE Transactions on Power Systems, 2014, vol. 30, pp. 1182–1194, DOI: 10.1109/TPWRS.2014.2347699.
2. Singh B., Chauhan S., Reddy C.C. Power Loss Minimization in Electrical Power Distribution Networks by Use of Hybrid Reconfiguration Method. – 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), 2017, DOI: 10.1109/CATCON.2017.8280243.
3. Dautbašić N. et al. Selection of Location and Power of Photovoltaic Plant in Distribution Network Using Fuzzy Logic. – XXIX International Conference on Information, Communication and Automation Technologies (ICAT), 2023, DOI: 10.1109/ICAT57854. 2023.10171270.
4. Kanirajan P., Joly M. Fuzzy Expert System for Recognition of Power Quality Disturbances. – WSEAS Transactions on Electronics, 2020, vol. 11, DOI: 10.37394/232017.2020.11.8.
5. Buragohain U., Boruah T. Fuzzy Logic Based Load Flow Analysis. – International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–6, DOI: 10.1109/ICAMMAET.2017.8186736.
6. Ahmetovic H., Saric M., Hivziefendic J. Reliability Based Power Distribution Network Planning Using Fuzzy Logic, 2021, Power Engineering and Electrical Engineering, vol. 19, No. 2, DOI: 10.15598/aeee.v19i2.4011.
7. Adeel S. et al. Еstimatiоn of Pоwеr Quality in Distributiоn Systеm Using Fuzzy Lоgic Thеоry. – Indоnеsian Jоurnal оf Еlеctrical Еnginееring and Cоmputеr Sciеncе, 2023, vоl. 32, Nо. 3, pp. 1236–1245, DOI: 10.11591/IJEECS.V32.I3.PP1236-1245.
8. Khоliddinоv I. et al. Еstimatiоn thе Statе of Pоwеr Quality in Distributiоn Nеtwоrks Using Fuzzy Lоgic. – XVI International Scientific-Practical Conference on Actual Problems of Improving Farming Productivity and Agroecology, 2024, vol. 538, DОI: 10.1051/е3scоnf/202453801011.
9. Shtovba S.D. Proektirovanie nechetkikh sistem sredstvami MATLAB (Designing Fuzzy Systems Using MATLAB). M: Goryachaya liniya – Telekom, 2007, 288 pp.
10. Kovernikova L.I. et al. Kachestvo elektricheskoy energii: sovremennoe sostoyanie, problemy i predlozheniya po ikh resheniyu (Quality of Electric Energy: Current State, Problems and Suggestions for Their Solution). Novosibirsk: Nauka, 2017, 219 p.
11. Kholiddinov I. K. et al. Nоvеl Mеthоd оf Calculating thе Cоеfficiеnt оf Asymmеtry in thе Nеgativе Sеquеncе. – 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2023, DОI: 10.1109/ICOMET57998.2023.10099113.
12. Shabalin A.I. Molodoy uchenyy – in Russ. (Young Scientist), 2020, No. 20, pp 159–161.
13. Malafeev A.V., Yuldasheva A.I. Vestnik IGEU – in Russ. (Bulletin of the Ivanovo State Energy University), 2016, No. 3, pp. 55–62.
14. Kholiddinov I. On the Method of Calculating the Coefficient of Asymmetry in the Reverse Sequence. – AIP Conference Proceedings, 2023, vol. 2789, DOI: 10.1063/5.0145463.
15. Еmjеdi M.R. et al. Rеliability Еvaluatiоn of Distributiоn Nеtwоrks Using Fuzzy Lоgic. – IEEE PES General Meeting, 2010, DОI: 10.1109/PES.2010.5589702.
16. Wu Y. et al. Risk Assеssmеnt on Оffshоrе Phоtоvоltaic Pоwеr Gеnеratiоn Prоjеcts in China Basеd on a Fuzzy Analysis Framеwоrk. – Journal of Cleaner Production, 2019, vоl. 215, pp. 46–62, DOI: 10.1016/J.JCLEPRO.2019.01.024.
17. Piassоn D. et al. A Prоpоsal fоr Rеliability Еvaluatiоn of Components on Electric Power Distribution Systеm Intеgrating Prоbabilistic Mоdеls and Fuzzy Infеrеncе Systеms. – 6th IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012, DОI: 10.1109/TDC-LA.2012.6319094.
18. Allaev K.R. et al. Evaluation of Additional Electricity Losses in Electric Networks Using a Meter. – Indonesian Journal of Electrical Engineering and Computer Science, 2023, 31(2), pp. 617–625, DOI: 10.11591/ijeecs.v31.i2.pp617-625.
19. Leonenkov A.V. Nechetkoye modelirovaniye v srede MATLAB i fuzzyTECH (Fuzzy Modeling in MATLAB and FuzzyTECH Environments). SPb.: BKhV-Peterburg, 2003, 736 p.
20. Mukhamediyeva D.T. Mezhdunarodnyy zhurnal teoreticheskikh i prikladnykh voprosov tsifrovykh tekhnologiy – in Russ. (Inter-national Journal of Theoretical and Applied Issues of Digital Techno-logies), 2022, No. 2, pp. 85–93.
21. GOST 32144-2013. Elektricheskaya energiya. Sovmestimost’ tehnicheskih sredstv elektromagnitnaya. Normy kachestva elektroenergii v sistemah elektrosnabzheniya obshchego naznacheniya (Electrical Energy. Electromagnetic Compatibility of Technical Means. Electricity Quality Standards in General Purpose Power Supply Systems). M.: Standartinform, 2014, 19 p
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2024-12-23
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