BhandariBLeeKLeeC, et al. (2014) A novel off-grid hybrid power system comprised of solar photovoltaic, wind, and hydro energy sources. Applied Energy133(22): 236–242.
2.
BhattacharyaAChattopadhyayP (2011) Application of biogeography-based optimisation to solve different optimal power flow problems. IET Generation, Transmission & Distribution5(1): 70–80.
3.
BiswasPSuganthanPAmaratungaG (2017) Optimal power flow solutions incorporating stochastic wind and solar power. Energy Conversion and Management148(18): 1194–1207.
4.
BoukettayaG.KrichenL (2014) A dynamic power management strategy of a grid connected hybrid generation system using wind, photovoltaic and flywheel energy storage system in residential applications. Energy71(14): 148–159.
5.
BuscemaMGrossiESnowdonDAntuonoP (2008) Auto-contractive maps: An artificial adaptive system for data mining. An application to Alzheimer disease. Current Alzheimer Research5(5): 481–498.
6.
CaiHChungCWongK (2008) Application of differential evolution algorithm for transient stability constrained optimal power flow. IEEE Transactions on Power Systems23(2): 719–728.
7.
ChaibABouchekaraHMehasniRAbidoM (2016) Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm. International Journal of Electrical Power & Energy Systems81(8): 64–77.
8.
ChakrabortyFRoyPNandiD (2019) Oppositional elephant herding optimization with dynamic Cauchy mutation for multilevel image thresholding. Evolutionary Intelligence12(3): 445–467.
9.
de la TorreSSanchez-RaceroAAguadoJ, et al. (2015) Optimal sizing of energy storage for regenerative braking in electric railway systems. IEEE Transactions on Power Systems30(3): 1492–1500.
10.
Dufo-LópezRBernal-AgustínJ (2008) Multi-objective design of PV–wind–diesel–hydrogen–battery systems. Renewable Energy33(12): 2559–2572.
11.
GonzálezARibaJRiusAPuigR (2015) Optimal sizing of a hybrid grid-connected photovoltaic and wind power system. Applied Energy154(18): 752–762.
12.
JuraszJ (2017) Modeling and forecasting energy flow between national power grid and a solar–wind–pumped-hydroelectricity (PV–WT–PSH) energy source. Energy Conversion and Management136(8): 382–394.
13.
KaurAKaurSDhimanG (2018) A quantum method for dynamic nonlinear programming technique using Schrödinger equation and Monte Carlo approach. Modern Physics Letters B32(30): 1850374.
14.
KokoSKusakanaKVermaakH (2017) Optimal energy management of a grid-connected micro-hydrokinetic with pumped hydro storage system. Journal of Energy Storage14(6): 8–15.
15.
KusakanaK (2015) Optimal scheduled power flow for distributed photovoltaic/wind/diesel generators with battery storage system. IET Renewable Power Generation9(8): 916–924.
16.
KusakanaK (2018) Optimal operation scheduling of grid-connected PV with ground pumped hydro storage system for cost reduction in small farming activities. Journal of Energy Storage16(2): 133–138.
17.
LingamuthuRMariappanR (2019) Power flow control of grid connected hybrid renewable energy system using hybrid controller with pumped storage. International Journal of Hydrogen Energy44(7): 3790–3802.
18.
LogeshR (2017) Resources, configurations, and soft computing techniques for power management and control of PV/wind hybrid system. Renewable and Sustainable Energy Reviews69(4): 129143.
19.
MaTYangHLuLPengJ (2015) Pumped storage-based standalone photovoltaic power generation system: Modeling and techno-economic optimization. Applied Energy137(1): 649–659.
20.
MahendranKPrabhaS (2019) Optimal control strategies for a hybrid renewable energy system: an ALANN/RNN technique. Soft Computing23(24): 13459–13475.
21.
MajidiMNojavanSNourani EsfetanajN, et al. (2017) A multi-objective model for optimal operation of a battery/PV/fuel cell/grid hybrid energy system using weighted sum technique and fuzzy satisfying approach considering responsible load management. Solar Energy144(4): 79–89.
22.
MbunguNNaidooRBansalRBipathM (2017) Optimisation of grid connected hybrid photovoltaic–wind–battery system using model predictive control design. IET Renewable Power Generation11(14): 1760–1768.
23.
MythiliSThiyagarajahKRajeshPShajinFH (2020) Ideal position and size selection of unified power flow controllers (UPFCs) to upgrade the dynamic stability of systems: An antlion optimiser and invasive weed optimisation Algorithm. HKIE Transactions27(1): 25–37.
24.
PankovitsPAbbesDSaudemontC, et al. (2016) Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations. Mathematics and Computers in Simulation130(12): 236–250.
25.
Praveen KumarTSubrahmanyamNSyduluM (2018) CMBSNN for power flow management of the hybrid renewable energy – Storage system-based distribution generation. IETE Technical Review36(3): 303–314.
26.
ReddySMomohJ (2015) Realistic and transparent optimum scheduling strategy for hybrid power system. IEEE Transactions on Smart Grid6(6): 3114–3125.
27.
RouholaminiMMohammadianM (2016) Heuristic-based power management of a grid-connected hybrid energy system combined with hydrogen storage. Renewable Energy96(12): 354–365.
28.
RoumilaZRekiouaDRekiouaT (2017) Energy management based fuzzy logic controller of hybrid system wind/photovoltaic/diesel with storage battery. International Journal of Hydrogen Energy42(30): 19525–19535.
29.
RoyKKrishna MandalKChandra MandalANarayan PatraS (2018) Analysis of energy management in micro grid – A hybrid BFOA and ANN approach. Renewable and Sustainable Energy Reviews82(3): 4296–4308.
30.
SerirCRekiouaDMezzaiNBachaS (2016) Supervisor control and optimization of multi-sources pumping system with battery storage. International Journal of Hydrogen Energy41(45): 20974–20986.
31.
ShabaniMMahmoudimehrJ (2018) Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system. Applied Energy212(2): 84–108.
32.
SimõesMBusarelloTBubshaitA, et al. (2015) Interactive smart battery storage for a PV and wind hybrid energy management control based on conservative power theory. International Journal of Control89(4): 850–870.
33.
StoppatoABenatoADestroNMirandolaA (2016) A model for the optimal design and management of a cogeneration system with energy storage. Energy and Buildings124(14): 241–247.
34.
StoppatoACavazziniGArdizzonGRossettiA (2014) A PSO (particle swarm optimization)-based model for the optimal management of a small PV(Photovoltaic)-pump hydro energy storage in a rural dry area. Energy76(22): 168–174.
35.
SureshkumarKPonnusamyV (2019) Power flow management in micro grid through renewable energy sources using a hybrid modified dragonfly algorithm with bat search algorithm. Energy181(16): 1166–1178.
36.
TeganiIAboubouAAyadM, et al. (2017) Experimental validation of differential flatness-based control applied to stand alone using photovoltaic/fuel cell/battery hybrid power sources. International Journal of Hydrogen Energy42(2): 1510–1517.
VenkatesanKGovindarajanU (2019) Optimal power flow control of hybrid renewable energy system with energy storage: A WOANN strategy. Journal of Renewable and Sustainable Energy11(1): 015501–015501.
40.
WangMGooiH (2011) Spinning reserve estimation in microgrids. IEEE Transactions on Power Systems26(3): 1164–1174.
41.
Zare OskoueiMSadeghi YazdankhahA (2015) Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency-based pricing. Energy Conversion and Management105(22): 1105–1114.
