Powiadomienia systemowe
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Warianty tytułu
Analiza pracy lokalnej sieci z uwzględnieniem własnych źródeł energii i możliwości rozbudowy
Języki publikacji
Abstrakty
Based on current developments related to the application of technology and the growth of load demand, power system structure (PSS) has grown into a large, intelligent network by integrating many new systems. At present, many classical systems are being modernized and developed towards smart systems to various technical performances while providing continuously energy from the generating sites to serve load centres as end energy users. On the other hand, protection and attention to the environment and renewable energy sources also affect the power system operation which is intended to reduce emissions and include green energy sources. Furthermore, these works explore an assessment of operations on local interconnection system topologies which are installed captive power plants. These studies are used to develop and evaluate the performance, where solar power plants are also installed as sources of energy suppliers. In this study, operating assessments are approached using a power flow study (PFS) to define structural performance expanded through several scenarios. In addition, the procedure for obtaining optimal conditions is also facilitated by using the Takagi Method (TM) and Thunderstorm Algorithm (TA) for PFS hybrid structures considered an integrated renewable energy source (IRES). Based on the technical scenario set, the results show that the applied scenarios have different performances. In addition, this study also provides various implications. IRES has affected system performance. PSS contributes to the part that is committed to covering the burden. TM and TA can be applied to the hybrid PFS structure.
W artykule przedstawiono metodę PFS (power flow study) do optymalizacji struktury lokalnej sieci zasilającej z zainstalowanymi źródłami fotowoltaicznymi. Zastosowano też metodę Takagi i algorytm burzowy do optymalizacji sieci z różnymi scenariuszami.
Wydawca
Czasopismo
Rocznik
Tom
Strony
75--80
Opis fizyczny
Bibliogr. 48 poz., rys., tab.
Twórcy
autor
- Electrical Engineering, Universitas Negeri Malang, Malang, Indonesia
- Center for Advanced Materials for Renewable Energy, Universitas Negeri Malang, Malang, Indonesia
- Smart Power and Advanced Energy Systems Research Center, Batu, Jawa Timur, Indonesia
autor
- Electrical Engineering, Universitas Negeri Malang, Malang, Indonesia
autor
- Electrical Engineering, Universitas Negeri Malang, Malang, Indonesia
autor
- The IROAST, Kumamoto University, Kumamoto, Japan
Bibliografia
- [1] Z. Q. Bo, X. N. Lin, Q. P. Wang, Y. H. Yi, and F. Q. Zhou, “Developments of power system protection and control,” Prot Control Mod Power Syst, vol. 1, no. 1, p. 7, Dec. 2016.
- [2] P. Cuffe and A. Keane, “Visualizing the Electrical Structure of Power Systems,” IEEE Systems Journal, vol. 11, no. 3, pp. 1810–1821, Sep. 2017.
- [3] A. N. Afandi, “Solving Combined Economic and Emission Dispatch Using Harvest Season Artificial Bee Colony Algorithm Considering Food Source Placements and Modified Rates,” International journal on electrical engineering and informatics, vol. Vol. 6, p. 267, Jul. 2014.
- [4] N. S. da Silva, A. Simões Costa, K. A. Clements, and E. Andreoli, “Simultaneous estimation of state variables and network topology for power system real-time modeling,” Electric Power Systems Research, vol. 133, pp. 338–346, Apr. 2016.
- [5] M. Aien, A. Hajebrahimi, and M. Fotuhi-Firuzabad, “A comprehensive review on uncertainty modeling techniques in power system studies,” Renewable and Sustainable Energy Reviews, vol. 57, pp. 1077–1089, May 2016.
- [6] A. N. Afandi and H. Miyauchi, “Improved artificial bee colony algorithm considering harvest season for computing economic dispatch on power system,” IEEJ Trans Elec Electron Eng, vol. 9, no. 3, pp. 251–257, May 2014.
- [7] S. Hr. A. Kaboli, J. Selvaraj, and N. A. Rahim, “Long-term electric energy consumption forecasting via artificial cooperative search algorithm,” Energy, vol. 115, pp. 857–871, Nov. 2016.
- [8] B. Zakeri and S. Syri, “Electrical energy storage systems: A comparative life cycle cost analysis,” Renewable and Sustainable Energy Reviews, vol. 42, pp. 569–596, Feb. 2015.
- [9] A. N. Afandi, “Weighting Factor Scenarios for Assessing the Financial Balance of Pollutant Productions and Fuel Consumptions on the Power System Operation,” Wseas Transactions On Business And Economics, vol. 14, 2017.
- [10] A. N. Afandi, I. Fadlika, and Y. Sulistyorini, “Solution of dynamic economic dispatch considered dynamic penalty factor,” in 2016 3rd Conference on Power Engineering and Renewable Energy (ICPERE), 2016, pp. 241–246.
- [11] A. N. Afandi et al., “Designed Operating Approach of Economic Dispatch for Java Bali Power Grid Areas Considered Wind Energy and Pollutant Emission Optimized Using Thunderstorm Algorithm Based on Forward Cloud Charge Mechanism,” International Review of Electrical Engineering (IREE), vol. 13, p. 59, Feb. 2018.
- [12] J. Geeganage, U. D. Annakkage, T. Weekes, and B. A. Archer, “Application of Energy-Based Power System Features for Dynamic Security Assessment,” IEEE Transactions on Power Systems, vol. 30, no. 4, pp. 1957–1965, Jul. 2015.
- [13] A. N. Afandi, “Optimal scheduling power generations using HSABC algorithm considered a new penalty factor approach,” in The 2nd IEEE Conference on Power Engineering and Renewable Energy (ICPERE) 2014, 2014, pp. 13–18.
- [14] F. Luo et al., “Advanced Pattern Discovery-based Fuzzy Classification Method for Power System Dynamic Security Assessment,” IEEE Transactions on Industrial Informatics, vol. 11, no. 2, pp. 416–426, Apr. 2015.
- [15] H. Gharavi, M. M. Ardehali, and S. Ghanbari-Tichi, “Imperial competitive algorithm optimization of fuzzy multi-objective design of a hybrid green power system with considerations for economics, reliability, and environmental emissions,” Renewable Energy, vol. 78, pp. 427–437, Jun. 2015.
- [16] A. N. Afandi and Y. Sulistyorini, “Thunderstorm Algorithm for Determining Unit Commitment in Power System Operation,” Journal of Engineering and Technological Sciences, vol. 48, no. 6, pp. 743–752, Dec. 2016.
- [17] M. Pandit, L. Srivastava, and M. Sharma, “Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection,” Applied Soft Computing, vol. 28, pp. 498–510, Mar. 2015.
- [18] A. N. Afandi, Optimal Solution of the EPED Problem Considering Space Areas of HSABC on the Power System Operation, vol. 7. 2015.
- [19] N. Tutkun, O. Can, and A. N. Afandi, “Low cost operation of an off-grid wind-PV system electrifying residential homes through combinatorial optimization by the RCGA,” in 2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 2017, pp. 38–42.
- [20] V. M. More and V. K. Chandrakar, “Power system performances improvement by using static synchronous series compensator,” in 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016, pp. 198–201.
- [21] A. N. Afandi, Y. Sulistyorini, H. Miyauchi, G. Fujita, X. Z. Gao, and M. El-Shimy, “The Penetration of Pollutant Productions on Dynamic Generated Power Operations Optimized Using a Novel Evolutionary Algorithm,” International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, pp. 1825–1831, Oct. 2017.
- [22] G. Lammert et al., “Impact of fault ride-through and dynamic reactive power support of photovoltaic systems on short-term voltage stability,” in 2017 IEEE Manchester PowerTech, 2017, pp. 1–6.
- [23] Z. Liu and Z. Zhang, “Quantifying transient stability of generators by basin stability and Kuramoto-like models,” in 2017 North American Power Symposium (NAPS), 2017, pp. 1–6.
- [24] A. Ganapathy, G. Soman, G. M. VM, and R. Lekshamana, “Online Energy Audit and Renewable Energy Management System,” in 2016 International Conference on Computing Communication Control and automation (ICCUBEA), 2016, pp. 1–6.
- [25] A. N. Afandi, “Thunderstorm Algorithm for Assessing Thermal Power Plants of the Integrated Power System Operation with an Environmental Requirement,” International Journal of Engineering and Technology, vol. 8, pp. 1102–1111, Apr. 2016.
- [26] M. EL-Shimy, N. Mostafa, A. N. Afandi, A. M. Sharaf, and M. A. Attia, “Impact of load models on the static and dynamic performances of grid-connected wind power plants: A comparative analysis,” Mathematics and Computers in Simulation, Feb. 2018.
- [27] D. Arengga, W. Agustin, Y. Rahmawati, S. Sendari, and A. N. Afandi, “SPEKTRA fast and smart software for renewable energy management,” IOP Conf. Ser.: Earth Environ. Sci., vol. 105, no. 1, p. 012077, Jan. 2018.
- [28] W. Liu, R. Cheng, Y. Xu, and Z. Liu, “Fast reliability evaluation method for composite power system based on the improved EDA and double cross linked list,” Transmission Distribution IET Generation, vol. 11, no. 15, pp. 3835–3842, 2017.
- [29] S. Zhao and C. Singh, “A reliability evaluation method for line switching operations in power systems,” in 2016 Power Systems Computation Conference (PSCC), 2016, pp. 1–7.
- [30] S. Chatterjee and S. Mandal, “A novel comparison of gaussseidel and newton- raphson methods for load flow analysis,” in 2017 International Conference on Power and Embedded Drive Control (ICPEDC), 2017, pp. 1–7.
- [31] J.-J. Deng and H.-D. Chiang, “Convergence Region of Newton Iterative Power Flow Method: Numerical Studies,” Journal of Applied Mathematics, 2013. [Online]. Available: https://www.hindawi.com/journals/jam/2013/509496/. [Accessed: 18-Mar-2018].
- [32] A. N. Afandi, Y. Sulistyorini, G. Fujita, N. P. Khai, and N. Tutkun, “Renewable energy inclusion on economic power optimization using thunderstorm algorithm,” in 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2017, pp. 1–6.
- [33] H. M. Hasanien and S. M. Muyeen, “A Taguchi Approach for Optimum Design of Proportional-Integral Controllers in Cascaded Control Scheme,” IEEE Transactions on Power Systems, vol. 28, pp. 1636–1644, May 2013.
- [34] A. N. Afandi and Y. Sulistyorini, “Thunderstorm Algorithm for Determining Unit Commitment in Power System Operation,” Journal of Engineering and Technological Sciences, vol. 48, no. 6, pp. 743–752, Dec. 2016.
- [35] M. El-Shimy, M. A. Attia, N. Mostafa, and A. N. Afandi, “Performance of grid-connected wind power plants as affected by load models: A comparative study,” in 2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 2017, pp. 1–8.
- [36] A. N. Afandi, I. Fadlika, and A. Andoko, “Comparing Performances of Evolutionary Algorithms on the Emission Dispatch and Economic Dispatch Problem,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 13, no. 4, pp. 1187–1193, Dec. 2015.
- [37] M. A. Elizondo, F. K. Tuffner, and K. P. Schneider, “Three-Phase Unbalanced Transient Dynamics and Powerflow for Modeling Distribution Systems With Synchronous Machines,” IEEE Transactions on Power Systems, vol. 31, no. 1, pp. 105–115, Jan. 2016.
- [38] Z. Ren, K. Wang, W. Li, L. Jin, and Y. Dai, “Probabilistic Power Flow Analysis of Power Systems Incorporating Tidal Current Generation,” IEEE Transactions on Sustainable Energy, vol. 8, no. 3, pp. 1195–1203, Jul. 2017.
- [39] X. Luo, J. Wang, M. Dooner, and J. Clarke, “Overview of current development in electrical energy storage technologies and the application potential in power system operation,” Applied Energy, vol. 137, pp. 511–536, Jan. 2015.
- [40] Y. Menchafou, H. E. Markhi, M. Zahri, and M. Habibi, “Impact of distributed generation integration in electric power distribution systems on fault location methods,” in 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), 2015, pp. 1–5.
- [41] F. S. Abu-Mouti and M. E. El-Hawary, “Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm,” IEEE Transactions on Power Delivery, vol. 26, no. 4, pp. 2090–2101, Oct. 2011.
- [42] N. Gupta, A. Swarnkar, and K. R. Niazi, “Distribution network reconfiguration for power quality and reliability improvement using Genetic Algorithms,” International Journal of Electrical Power & Energy Systems, vol. 54, pp. 664–671, Jan. 2014.
- [43] A. Mohamed Imran and M. Kowsalya, “A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm,” International Journal of Electrical Power & Energy Systems, vol. 62, pp. 312–322, Nov. 2014.
- [44] S. R. Karnik, A. B. Raju, and M. S. Raviprakasha, “Genetic Algorithm Based Robust Power System Stabilizer Design Using Taguchi Principle,” in 2008 First International Conference on Emerging Trends in Engineering and Technology, 2008, pp. 887–892.
- [45] “Taguchi’s method for probabilistic three-phase power flow of unbalanced distribution systems with correlated Wind and Photovoltaic Generation Systems - ScienceDirect.” [Online]. Available: https://www.sciencedirect.com/science/article/pii/S096014811731011X. [Accessed: 11-Apr-2018].
- [46] “Improving the quality of an optimal power flow solution by Taguchi method - ScienceDirect.” [Online]. Available: https://www.sciencedirect.com/science/article/pii/014206159591406A. [Accessed: 11-Apr-2018].
- [47] T. Kulworawanichpong, “Simplified Newton–Raphson powerflow solution method,” International Journal of Electrical Power & Energy Systems, vol. 32, no. 6, pp. 551–558, Jul. 2010.
- [48] R. Muzzammel, M. Ahsan, and W. Ahmad, “Non-linear analytic approaches of power flow analysis and voltage profile improvement,” in 2015 Power Generation System and Renewable Energy Technologies (PGSRET), 2015, pp. 1–7.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6b9e9490-5e73-4e55-aa91-e7bfc782049d