In this paper, a new optimization methodology to assess the designs of the various renewable generation systems of electrical energy is used. This methodology utilizes Whale Optimization Algorithm (WOA) to minimize the cost of the electrical energy generated. The methodology permits to examine and to combine different sources of energy as to touch base at an optimal configuration of the hybrid system. This system is capable of providing energy to the predefined site in an achievable way as indicated by certain specialized and financial criteria. The system incorporates wind generation, photovoltaic generation and batteries for energy storage. The recreation results have been acquired with the help of MATLAB programming. Moreover, the outcomes of the proposed methodology have been compared with Particle Swarm Optimization (PSO) Algorithm for validation. The recreation results demonstrated the predominance of the proposed methodology.
VafamandN., KhoobanM.H., DragičevićT., Boudjadar J. and AsemaniM.H., Time-delayed stabilizing secondary load frequency control of shipboard microgrids, IEEE Systems Journal (2019).
2.
BatelS. and Devine-WrightP., Towards a better understanding of people’s responses to renewable energy technologies: Insights from Social Representations Theory, Public Understanding of Science24(3) (2015), 311–325.
3.
MohamedM.A., EltamalyA.M., AlolahA.I. and HatataA.Y., A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems, International Journal of Green Energy16(1) (2019), 86–100.
4.
EltamalyA.M. and MohamedM.A., Optimal sizing and designing of hybrid renewable energy systems in smart grid applications, In Advances in Renewable Energies and Power Technologies, Elsevier, (2018), pp. 231–313.
5.
EltamalyA.M., MohamedM.A., Al-SaudM.S. and AlolahA.I., Load management as a smart grid concept for sizing and designing of hybrid renewable energy systems, Engineering Optimization49(10) (2017), 1813–1828.
6.
KhoobanM.H., VafamandN., LiaghatA. and DragicevicT., An optimal general type-2 fuzzy controller for Urban Traffic Network, ISA transactions66 (2017), 335–343.
7.
MoradiM.H., AbediniM., TousiS.R. and HosseinianS.M., Optimal siting and sizing of renewable energy sources and charging stations simultaneously based on Differential Evolution algorithm, International Journal of Electrical Power & Energy Systems73 (2015), 1015–1024.
8.
Kavousi-FardA., NiknamT. and Fotuhi-FiruzabadM., A novel stochastic framework based on cloud theory and θ-modified bat algorithm to solve the distribution feeder reconfiguration, IEEE Transactions on Smart Grid7(2) (2016), 740–750.
9.
KhalghaniM.R., KhoobanM.H., Mahboubi-MoghaddamE., VafamandN. and GoodarziM., A self-tuning load frequency control strategy for microgrids: Human brain emotional learning, International Journal of Electrical Power & Energy Systems75 (2016), 311–319.
10.
VafamandN. and RakhshanM., Dynamic model-based fuzzy controller for maximum power point tracking of photovoltaic systems: A linear matrix inequality approach, Journal of Dynamic Systems, Measurement, and Control139(5) (2017), 051010.
11.
PahnehkolaeiS.M.A., AlfiA., SadollahA. and KimJ.H., Gradient-based water cycle algorithm with evaporation rate applied to chaos suppression, Applied Soft Computing53 (2017), 420–440.
12.
TsaiM.F., TsengC.S. and LinY.H., Power management and control of an electric vehicle with auxiliary fuel cell and wind energies, In 2013 IEEE International Conference of IEEE Region 10 (TENCON 2013) (2013), pp. 1–4. IEEE.
13.
ZahbouneH., ZouggarS., KrajacicG., VarbanovP.S., ElhafyaniM. and ZianiE., Optimal hybrid renewable energy design in autonomous system using Modified Electric System Cascade Analysis and Homer software, Energy Conversion and Management126 (2016), 909–922.
14.
Al-SharafiA., SahinA.Z., AyarT. and YilbasB.S., Techno-economic analysis and optimization of solar and wind energy systems for power generation and hydrogen production in Saudi Arabia, Renewable and Sustainable Energy Reviews69 (2017), 33–49.
15.
TheoW.L., LimJ.S., HoW.S., HashimH. and LeeC.T., Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods, Renewable and Sustainable Energy Reviews67 (2017), 531–573.
16.
AmeliK., AlfiA. and AghaebrahimiM., A fuzzy discrete harmony search algorithm applied to annual cost reduction in radial distribution systems, Engineering Optimization48(9) (2016), 1529–1549.
17.
SichilaluS.M. and XiaX., Optimal energy control of grid tied PV–diesel–battery hybrid system powering heat pump water heater, Solar Energy115 (2015), 243–254.
18.
BelmiliH., HaddadiM., BachaS., AlmiM.F. and BendibB., Sizing stand-alone photovoltaic–wind hybrid system: Techno-economic analysis and optimization, Renewable and Sustainable Energy Reviews30 (2014), 821–832.
19.
ZhaiQ., CaoH., ZhaoX. and YuanC., Assessing application potential of clean energy supply for house gas emission mitigation: A case study on General Motors global manufacturing, Journal of cleaner production75 (2014), 11–19green.
20.
BaghdadiF., MohammediK., DiafS. and BeharO., Feasibility study and energy conversion analysis of stand-alone hybrid renewable energy system, Energy Conversion and Management105 (2015), 471–479.
21.
HuY. and WangZ.L., Recent progress in piezoelectric nanogenerators as a sustainable power source in self-powered systems and active sensors, Nano Energy14 (2015), 3–14.
22.
WuJ., AlbertL.P., LopesA.P., Restrepo-CoupeN., HayekM., WiedemannK.T. and TavaresJ.V., Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests, Science351(6276) (2016), 972–976.
23.
MousaviY. and AlfiA., Fractional calculus-based firefly algorithm applied to parameter estimation of chaotic systems, Chaos, Solitons & Fractals114 (2018), 202–215.
24.
ShahriE.S.A., AlfiA. and MachadoJ.T., Fractional fixed-structure H∞ controller design using augmented lagrangian particle swarm optimization with fractional order velocity, Applied Soft Computing77 (2019), 688–695.
25.
MirjaliliS. and LewisA., The whale optimization algorithm, Advances in Engineering Software95 (2016), 51–67.
26.
AljarahI., FarisH. and MirjaliliS., Optimizing connection weights in neural networks using the whale optimization algorithm, Soft Computing22(1) (2018), 1–15.
27.
ben oualid MedaniK., SayahS. and BekrarA., Whale optimization algorithm based optimal reactive power dispatch: A case study of the Algerian power system, Electric Power Systems Research163 (2018), 696–705.
28.
ReddyP.D.P., ReddyV.V. and ManoharT.G., Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems, Renewables: Wind, Water, and Solar4(1) (2017), 3.
29.
LingY., ZhouY. and LuoQ., Lévy flight trajectory-based whale optimization algorithm for global optimization, IEEE Access5(99) (2017), 6168–6186.
30.
KavehA. and GhazaanM.I., Enhanced whale optimization algorithm for sizing optimization of skeletal structures, Mechanics Based Design of Structures and Machines45(3) (2017), 345–362.
31.
HuH., BaiY. and XuT., A whale optimization algorithm with inertia weight, WSEAS Trans Comput15 (2016), 319–326.
32.
DuP., WangJ., YangW. and NiuT., Multi-step ahead forecasting in electrical power system using a hybrid forecasting system, Renewable Energy122 (2018), 533–550.
33.
BhesdadiyaR., JangirP., JangirN., TrivediI.N. and LadumorD., Training multi-layer perceptron in neural network using whale optimization algorithm, Indian J Sci Technol9(19) (2016), 28–36.
34.
PrasadD., MukherjeeA., ShankarG. and MukherjeeV., Application of chaotic whale optimisation algorithm for transient stability constrained optimal power flow, IET Science, Measurement & Technology11(8) (2017), 1002–1013.
35.
BahramaraS., MoghaddamM.P. and HaghifamM.R., Optimal planning of hybrid renewable energy systems using HOMER: A review, Renewable and Sustainable Energy Reviews62 (2016), 609–620.
36.
SinhaS. and ChandelS.S., Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems, Renewable and Sustainable Energy Reviews50 (2015), 755–769.
37.
KalinciY., HepbasliA. and DincerI., Techno-economic analysis of a stand-alone hybrid renewable energy system with hydrogen production and storage options, International Journal of Hydrogen Energy40(24) (2015), 7652–7664.
38.
EltamalyA.M., MohamedM.A. and AlolahA.I., A novel smart grid theory for optimal sizing of hybrid renewable energy systems, Solar Energy124 (2016), 26–38.
39.
MalekiA., KhajehM.G. and AmeriM., Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty, International Journal of Electrical Power & Energy Systems83 (2016), 514–524.
40.
RahmanM.M., KhanM.M.U.H., UllahM.A., ZhangX. and KumarA., A hybrid renewable energy system for a North American off-grid community, Energy97 (2016), 151–160.
41.
ZhouB., LiW., ChanK.W., CaoY., KuangY., LiuX. and WangX., Smart home energy management systems: Concept, configurations, and scheduling strategies, Renewable and Sustainable Energy Reviews61 (2016), 30–40.
42.
PanI. and DasS., Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO, ISA Transactions62 (2016), 19–29.
43.
TsuanyoD., AzoumahY., AusselD. and NeveuP., Modeling and optimization of batteryless hybrid PV (photovoltaic)/Diesel systems for off-grid applications, Energy86 (2015), 152–163.
44.
EltamalyA.M., AddoweeshK.E., BawahU. and MohamedM.A., New software for hybrid renewable energy assessment for ten locations in Saudi Arabia, Journal of Renewable and Sustainable Energy5(3) (2013), 033126.
45.
AtiaR. and YamadaN., Sizing and analysis of renewable energy and battery systems in residential microgrids, IEEE Transactions on Smart Grid7(3) (2016), 1204–1213.
46.
TummuruN.R., MishraM.K. and SrinivasS., Dynamic energy management of renewable grid integrated hybrid energy storage system, IEEE Transactions on Industrial Electronics62(12) (2015), 7728–7737.
47.
ZhouK., FuC. and YangS., Big data driven smart energy management: From big data to big insights, Renewable and Sustainable Energy Reviews56 (2016), 215–225.
MohamedM.A., EltamalyA.M. and AlolahA.I., Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems, Renewable and Sustainable Energy Reviews77 (2017), 515–524.
50.
KumarA., SahB., SinghA.R., DengY., HeX., KumarP. and BansalR.C., A review of multi criteria decision making (MCDM) towards sustainable renewable energy development, Renewable and Sustainable Energy Reviews69 (2017), 596–609.
51.
MohamedM.A., EltamalyA.M. and AlolahA.I., Sizing and techno-economic analysis of stand-alone hybrid photovoltaic/wind/diesel/battery power generation systems, Journal of Renewable and Sustainable Energy7(6) (2015), 063128.
52.
MohamedM.A., EltamalyA.M. and AlolahA.I., PSO-based smart grid application for sizing and optimization of hybrid renewable energy systems, PloS one11(8) (2016), e0159702.
