Fixed head short-term hydrothermal scheduling in presence of solar and wind power
Tài liệu tham khảo
Brannud, 1986, Optimal short term operation planning ofa large hydrothermal power system based on a nonlinear network flowconcept, IEEE Trans PWRS, 1, 75
Salam Nor, 1998, Hydrothermal scheduling based Lagrangian relaxation approach to hydrothermal coordination, IEEE Trans. Power Syst., 13, 226, 10.1109/59.651640
Nilsson, 1996, Mixed-integer programming applied to short-term lanning of a hydrothermal system, IEEE Trans. Power Syst., 11, 281, 10.1109/59.486107
Wood, 1984
Engles, 1976
Wong, 1994, Short-term hydrothermal scheduling Part I: simulated annealing approach, ProcInstElectrEng Gen TransmDistrib, 141, 497
Wong, 1994, Short-term hydrothermal scheduling Part II: parallel simulated annealing approach, ProcInstElectrEng Gen TransmDistrib, 141, 502
Sinha, 2003, Fast evolutionary programming techniques for short-term hydrothermal scheduling, Elec. Power Syst. Res., 66, 97, 10.1016/S0378-7796(03)00016-6
Mandal, 2008, Differential evolution technique-based short-term economic generation scheduling of hydrothermal systems, Elec. Power Syst. Res., 78, 1972, 10.1016/j.epsr.2008.04.006
Orero, 1998, A genetic algorithm modeling framework and solution technique for short term optimal hydrothermal scheduling, IEEE Trans PWRS, 13, 501
Mandal, 2008, Particle swarm optimization technique based short-term hydrothermal scheduling, Appl. Soft Comput., 8, 1392, 10.1016/j.asoc.2007.10.006
Zhang, 2012, Small population-based particle swarm optimization for short-term hydrothermal scheduling, IEEE Trans. Power Syst., 27, 142, 10.1109/TPWRS.2011.2165089
Rasoulzadeh-akhijahani, 2015, Short-term hydrothermal generation scheduling by modified dynamic neighborhood learning based particle swarm optimization, Int. J. Electr. Power Energy Syst., 67, 350, 10.1016/j.ijepes.2014.12.011
Basu, 2011, Artificial immune system for fixed head hydrothermal power system, Energy, 36, 606, 10.1016/j.energy.2010.09.057
Bhattacharjee, 2014, Real coded chemical reaction based optimization for short-term hydrothermal scheduling, Appl. Soft Comput., 24, 962, 10.1016/j.asoc.2014.08.048
Roy, 2013, Teaching learning based optimization for short-term hydrothermal scheduling problem considering valve point effect and prohibited discharge constraint, Int J Elec Power, 53, 10, 10.1016/j.ijepes.2013.03.024
Nguyen, 2014, Cuckoo search algorithm for short-term hydrothermal scheduling, Appl. Energy, 132, 276, 10.1016/j.apenergy.2014.07.017
Gouthamkumar, 2015, Disruption based gravitational search algorithm for short term hydrothermal scheduling, Expert Syst. Appl., 42, 7000, 10.1016/j.eswa.2015.05.017
Das, 2016, Symbiotic organism search algorithm for short-term hydrothermal scheduling, Ain Shams Engineering journal, 10.1016/j.asej.2016.04.002
Esmaeily, 2017, Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate, Energy, 122, 182, 10.1016/j.energy.2017.01.089
Nazari-Heris, 2018, Improved harmony search algorithm for the solution of non-linear non-convex short-term hydrothermal scheduling, Energy, 151, 226, 10.1016/j.energy.2018.03.043
Feng, 2017, Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling, Energy, 131, 165, 10.1016/j.energy.2017.05.013
Nazari-Heris, 2017, Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation, Energy, 128, 77, 10.1016/j.energy.2017.04.007
Patwal, 2017, A novel TVAC-PSO based mutation strategies algorithm for generation scheduling of pumped storage hydrothermal system incorporating solar units, Energy, 142, 822, 10.1016/j.energy.2017.10.052
http://www.bp.com.
https://mnre.gov.in.
Banerjee, 2016, Short-term hydro-wind-thermal scheduling based on particle swarm optimization technique, Int. J. Electr. Power Energy Syst., 81, 275, 10.1016/j.ijepes.2016.01.031
Yuan, 2015, An extended NSGA-III for solution multi-objective hydrothermal-wind scheduling considering wind power cost, Energy Convers. Manag., 96, 568, 10.1016/j.enconman.2015.03.009
Zhou, 2016, Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm, Energy Convers. Manag., 123, 116, 10.1016/j.enconman.2016.05.073
Liang, 2017, A virus-evolutionary differentiated-PSO approach for short-term generation scheduling with uncertainties, Int. Trans. Electr. Energ. Syst, 26, 2288, 10.1002/etep.2202
Dubey, 2016, Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index, Renew. Energy, 99, 18, 10.1016/j.renene.2016.06.039
Singh, 2017, Impact of large-scale rooftop solar PV integration: an algorithm for hydrothermal-solar scheduling (HTSS), Sol. Energy, 157, 988, 10.1016/j.solener.2017.09.021
Wang, 2017, Improved multi-objective model and analysis of the coordinated operation of a hydro -wind-photovoltaic system, Energy, 134, 813, 10.1016/j.energy.2017.06.047
Zhang, 2017, Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power, Energy, 122, 748, 10.1016/j.energy.2017.01.083
Hemmati, 2018, Optimal cogeneration and scheduling of hybrid hydro-thermal-wind-solar system incorporating energy storage systems, J. Renew. Sustain. Energy, 10, 1, 10.1063/1.5017124
Somma, 2018, Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects, Renew. Energy, 116, 272, 10.1016/j.renene.2017.09.074
Damodaran, 2018, Hydro-thermal-wind generation scheduling considering economic and environmental factors using heuristic algorithms, Energies, 11, 1, 10.3390/en11020353
Rosenblueth, 1975, Point estimation for probability moments, Proc Nat AcadSci, 72, 3812, 10.1073/pnas.72.10.3812
Rubinstein, 1981
Hong, 1998, An efficient point estimate method for probabilistic analysis, Reliab. Eng. Syst. Saf., 59, 261, 10.1016/S0951-8320(97)00071-9
Su, 2005, Probabilistic load-flow computation using point estimate method, IEEE Trans. Power Syst., 20, 1843, 10.1109/TPWRS.2005.857921
Malekpour, 2011, A probabilistic multi-objective daily Volt/Varcontrol at distribution networks including renewable energy sources, Energy, 36, 3477, 10.1016/j.energy.2011.03.052
Soroudi, 2011, A probabilistic modeling of photo voltaic modules and wind power generation impact on distribution networks, IEEE systems journal, 6, 254, 10.1109/JSYST.2011.2162994
Mohammadi, 2013, An adaptive modified firefly optimization algorithm based on Hong's point estimate method to optimal operation management in a microgrid with consideration of uncertainties, Energy, 51, 339, 10.1016/j.energy.2012.12.013
Niknam, 2012, Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational search algorithm, Energy, 43, 427, 10.1016/j.energy.2012.03.064
Alavi, 2015, Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method, Energy Convers. Manag., 95, 314, 10.1016/j.enconman.2015.02.042
Abarghooee, 2012, Probabilistic multi objective wind-thermal economic emission dispatch based on point estimated method, Energy, 37, 322, 10.1016/j.energy.2011.11.023
Zhang, 2004, Probabilistic load flow computation using the method of combined cumulants and Grame Charlier expansion, IEEE Trans. Power Syst., 19, 676, 10.1109/TPWRS.2003.818743
Askarzadeh, 2016, A novel metaheuristic method for solving constrained engineering optimization problems, Crow search algorithm, 169, 1
Mirjalili, 2015, Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm, Knowl. Base Syst., 89, 228, 10.1016/j.knosys.2015.07.006
Mirjalili, 2016, Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems, Neural Computing & Appplications, 27, 1053, 10.1007/s00521-015-1920-1