Economic Analysis by Optimal Placing of DGs in Distribution Networks by Particle Swarm Optimisation and Gravitational Search Optimisation Algorithm
DOI:
https://doi.org/10.13052/dgaej2156-3306.3839Keywords:
PSOGSA, method of PLI (power loss index), DG siting, radial network, reduction of lossesAbstract
The particle swarm optimisation and gravitational search optimisation algorithm (PSOGSA) is a hybrid algorithm which is used to determine size of optimal Distributed Generation (DG) in this paper. The PSOGSA integrates the social thinking ability (gbest) in PSO to capability of local search in GSA. The algorithm combines the searching capability of PSO and with enhanced exploration ability of GSA. Distributed generations are connected in distribution systems to consumers to reduce losses, enhance the voltage profile, reliability and economic benefits. DG optimal positioning and loss minimisation have a significant role for economic operation and overall reduction of energy costs. For evaluation of proposed algorithm, the test bus sets IEEE15, 33 and 69 are chosen. For considered objectives i.e., optimal DG sizing and economic analysis, this PSOGSA algorithm gives better results as compared to other methods and better outcomes has been achieved when DG unit of type III operates at power factor of 0.9 lag
Downloads
References
Wang, C., Nehrir, M., 2004 “Analytical approaches for optimal placement of distributed generation sources in power systems” IEEE Transactions on Power Systems 19, 2068–2076.
Gzel, T., Hocaoglu, M., 2009 “ An analytical method for the sizing and siting of distributed generators in radial systems” Electric Power Systems Research 79, 912–918.
Rashedi, E., Nezamabadi-pour, H., Saryazdi, S., 2009 “GSA: A gravitational search algorithm” Information Sciences 179, 2232–2248.
Masoum, M., Ladjevardi, M., Jafarian, A., Fuchs, E., 2004 “Optimal placement, replacement and sizing of capacitor banks in distorted distribution networks by genetic algorithms” IEEE Transactions on Power Delivery 19, 1794–1801.
Mirjalili, S., Hashim, S.Z.M., 2010 “A new hybrid PSOGSA algorithm for function optimization” International Conference on Computer and Information Application, IEEE.
Moshtagh, J., Jalali, A., Karimizadeh, K., 2010 “Optimum placement and sizing of dg using binary pso algorithm to achieve the minimum electricity cost for consumers”International Review of Electrical Engineering 5, 2873–2881.
Mousavi, S., Mohammadi, M., 2011 “Economic analysis of optimal planning of distribution system in presence of dgs with considering power quality indices with fuzzy logic algorithm (FLA)” Australian Journal of Basic and Applied Sciences 5, 889–898.
Niknam, T., Taheri, S., Aghaei, J., Tabatabaei, S., Nayeripour, M., 2011 “A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources” Applied Energy 88, 4817–4830.
Murthy, V., Kumar, A., 2013 “Comparison of optimal dg allocation methods in radial distribution systems based on sensitivity approaches” International Journal of Electrical Power & Energy Systems 53, 450–467.
El-Zonkoly, A., 2011 “Optimal placement of multi-distributed generation units including different load models using particle swarm optimization” Swarm and Evolutionary Computation 1, 50–59.
Aman, M., Jasmon, G., Bakar, A., Mokhlis, H., 2013 “A new approach for optimum dg placement and sizing based on voltage stability maximization and minimization of power losses” Energy Conversion and Management 70, 202–210.
GopiyaNaik, S., Khatod, D., Sharma, M., 2013 “Optimal allocation of combined dg and capacitor for real power loss minimization in distribution networks” International Journal of Electrical Power and Energy Systems 53, 967–973.
Kansal, S., Kumar, V., Tyagi, B., 2013 “Optimal placement of different type of dg sources in distribution networks” International Journal of Electrical Power and Energy Systems 53, 752–760.
MartnGarca, J., Gil Mena, A., 2013 “Optimal distributed generation location and size using a modified teaching-learning based optimization algorithm” International Journal of Electrical Power and Energy Systems 50, 65–75.
Kalambe, S., Agnihotri, G., 2014 “Loss minimization techniques used in distribution network: Bibliographical survey” Renewable and Sustainable Energy Reviews 29, 184–200.
Aman, M., Jasmon, G., Bakar, A., Mokhlis, H., 2014 “A new approach for optimum simultaneous multi-dg distributed generation units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm” Energy 66, 202–215.
Bohre, A., Agnihotri, G., Dubey, M., 2016 “Optimal sizing and sitting of dg with load models using soft computing techniques in practical distribution system” IET Generation, Transmission and Distribution 10, 2606–2621.
Kansal, S., Tyagi, B., Kumar, V., 2017 “Costbenefit analysis for optimal distributed generation placement in distribution systems” International Journal of Ambient Energy 38, 45–54.
Mahesh, K., Nallagownden, P., Elamvazuthi, I., 2017 “Multi-objective pso based optimal placement of solar power dg in radial distribution system”. Journal of Electrical Systems 13, 322–331
Mohammadi, M., Rozbahani, A., Bahmanyar, S., 2017 “Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework” Journal of Central South University 24, 90–103.
Bhattacharya, M., Sivasubramani, S., Roy, A., 2018 “Multiobjective placement and sizing of distributed generations in distribution system using global criterion method” International Transactions on Electrical Energy Systems.
Penangsang, O., Amanullah, M., Aryani, N., 2018 “Distributed generation (dg) placement for reducing power losses on radial distribution system using k-means clustering method” ARPN Journal of Engineering and Applied Sciences 13, 1570–1577.
Saha, G., George Fernandez, S., 2016 “Optimal placement of distributed generation in a distribution system using hybrid big brunch and big crunch algorithm” International Journal of Control Theory and Applications 9, 7789–7799.
Singh, A., Parida, S., 2016 “Novel sensitivity factors for dg placement based on loss reduction and voltage improvement” International Journal of Electrical Power and Energy Systems 74, 453–456.
Sudabattula, S., Kowsalya, M., 2016 “Flower pollination algorithm based optimal placement of solar based distributed generators in distribution system” International Journal of Renewable Energy Research 6, 1232–1241.
Yammani, C., Maheswarapu, S., Matam, S., 2016 “A multi-objective shuffled bat algorithm for optimal placement and sizing of multi distributed generations with different load models” International Journal of Electrical Power and Energy Systems 79, 120–131
Warid, W., Hizam, H., Mariun, N., Abdul-Wahab, N., 2017 “A sensitivity based methodology for optimal placement of distributed generation in meshed power ystems” International Journal of Simulation: Systems, Science and Technology 17, 44.1–44.8.
Suresh, M.C.V., Belwin, E.J., 2018. “Optimal dg placement for benefit max imization in distribution networks by using dragonfly algorithm”. Renewables: Wind, Water, and Solar.
Baran, M.E., Wu, F.F., 1989 “Optimal sizing of capacitors placed on a radial distribution system” IEEE Transaction on Power delivery 4, 735–743.
Zhaang, C., Li, J., Zhaang, Y., Xu, Z., 2018. “Optimal location planning of renewable distributed generation units in distribution networks: An analytical approach” IEEE Transactions on Power Systems 33, 2742–2753.