Renewable energy has grown in popularity in recent years as a solution to combat the effects of pollution on the environment. The main purpose of this research is to design a microgrid system in Lakshadweep Island to determine the cost and dependability of a solar photovoltaic system that is combined with biomass, wind energy and diesel generator. Two types of hybrid systems like solar/biomass generator/wind turbine and Solar/diesel generator/biomass are investigated to get an optimal solution using HOMER Pro software. The hybrid microgrid system is optimized with low cost of energy (COE) and less environmental pollution. The reliability indice like unmet load is determined for each case to access the performance of the system. The influence of different Weibull shape parameter in solar/biomass generator/wind turbine hybrid system with sensitive variation of solar irradiation and wind speed are discussed. The scheduling of diesel generator in solar/diesel generator/biomass generator with various scenarios are analyzed based on minimum net present cost. The optimization results shows that the solar/diesel generator/biomass hybrid system has low net present cost of 432513 $ and cost of energy of 0.215 $/kWh as compared to solar/biomass/wind turbine for the selected site location. The proposed solar/diesel generator/biomass system produces emission of 7506 kg/yr. The emission produced in Lakshadweep Island using the proposed model is reduced since this Island currently produces electricity mainly with diesel generators. The optimal sizing of various components in microgrid system is performed to get the optimal solution.
Citation: S. Vinoth John Prakash, P.K. Dhal. Cost optimization and optimal sizing of standalone biomass/diesel generator/wind turbine/solar microgrid system[J]. AIMS Energy, 2022, 10(4): 665-694. doi: 10.3934/energy.2022032
Renewable energy has grown in popularity in recent years as a solution to combat the effects of pollution on the environment. The main purpose of this research is to design a microgrid system in Lakshadweep Island to determine the cost and dependability of a solar photovoltaic system that is combined with biomass, wind energy and diesel generator. Two types of hybrid systems like solar/biomass generator/wind turbine and Solar/diesel generator/biomass are investigated to get an optimal solution using HOMER Pro software. The hybrid microgrid system is optimized with low cost of energy (COE) and less environmental pollution. The reliability indice like unmet load is determined for each case to access the performance of the system. The influence of different Weibull shape parameter in solar/biomass generator/wind turbine hybrid system with sensitive variation of solar irradiation and wind speed are discussed. The scheduling of diesel generator in solar/diesel generator/biomass generator with various scenarios are analyzed based on minimum net present cost. The optimization results shows that the solar/diesel generator/biomass hybrid system has low net present cost of 432513 $ and cost of energy of 0.215 $/kWh as compared to solar/biomass/wind turbine for the selected site location. The proposed solar/diesel generator/biomass system produces emission of 7506 kg/yr. The emission produced in Lakshadweep Island using the proposed model is reduced since this Island currently produces electricity mainly with diesel generators. The optimal sizing of various components in microgrid system is performed to get the optimal solution.
[1] | Ai B, Yang B, Shen H, et al. (2003) Computer-aided design of PV/Solar hybrid system. Renewable Energy 28: 1491–1512. https://doi.org/10.1016/S0960-1481(03)00011-9 doi: 10.1016/S0960-1481(03)00011-9 |
[2] | Billinton R, Karki R (2001) Capacity expansion of small isolated power systems using PV and Solar energy. IEEE Trans Power Syst 16: 892–897. https://doi.org/10.1109/59.962442 doi: 10.1109/59.962442 |
[3] | Fujisaki T (2018) Evaluation of Green Paradox: Case study of Japan. Evergreen: Green Asia Educ Cent 5: 26–31. https://doi.org/10.5109/2174855 doi: 10.5109/2174855 |
[4] | Ghahderijani MM, Barakati MS, Tavakoli S (2012) Reliability evaluation of stand-alone hybrid microgrid using Sequential Monte Carlo simulation, Proceedings: IEEE Second Iranian conference on renewable energy and distributed Generation, 33–38. https://doi.org/10.1109/ICREDG.2012.6190464 doi: 10.1109/ICREDG.2012.6190464 |
[5] | Aien M, Biglari A, Rashidinejad M (2013) Probabilistic reliability evaluation of hybrid wind-photovoltaic power systems. Proceedings: International Conference on Electrical Engineering, Mashhad, Iran, 1–6. https://doi.org/10.1109/IranianCEE.2013.6599825 |
[6] | Leite AM, Manso LAF, Mello JCO, et al. (2000) Pseudo-chronological simulation for composite reliability analysis with time varying loads. IEEE Trans Power Syst 15: 73–80. https://doi.org/10.1109/59.852103 doi: 10.1109/59.852103 |
[7] | Karki R, Billinton R (2004) Considering renewable energy in small isolated power system expansion. Proceedings: Canadian Conference on Electrical and Computer Engineering, 367–370. |
[8] | Wangdee W, Billinton R (2005) Reliability-performance-index probability distribution analysis of bulk electricity systems. Canadian J Electr Comput Eng 30: 189–193. https://doi.org/10.1109/CJECE.2005.1541750 doi: 10.1109/CJECE.2005.1541750 |
[9] | All India installed capacity of power stations. (2022) Available from: https://npp.gov.in/publishedReports. |
[10] | Rathore A, Patidar NP (2019) Reliability assessment using probabilistic modelling of pumped storage hydro plant with PV-Solar based standalone microgrid. Electr Power Energy Syst 106: 17–32. https://doi.org/10.1016/j.ijepes.2018.09.030 doi: 10.1016/j.ijepes.2018.09.030 |
[11] | Alktranee M, Bencs P (2021) Simulation study of the photovoltaic panel under different operating conditions. ACTA IMEKO 10: 62–66. http://dx.doi.org/10.21014/acta_imeko.v10i4.1111 doi: 10.21014/acta_imeko.v10i4.1111 |
[12] | Sengthavy P, Doumbia ML, St-Pierre DL (2020) Review on the cost optimization of microgrids via particle swarm optimization. Int J Energy Environ Eng 11: 73–99. https://doi.org/10.1007/s40095-019-00332-1 doi: 10.1007/s40095-019-00332-1 |
[13] | Fathima AH, Palanisamy K (2015) Optimization in microgrids with hybrid energy systems—A review. Renewable Sustainable Energy Rev 45: 431–446, https://doi.org/10.1016/j.rser.2015.01.059 doi: 10.1016/j.rser.2015.01.059 |
[14] | López RD, Bernal JL, Yusta JM, et al. (2011) Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV-wind-diesel systems with batteries storage. Appl Energy 88: 4033–4041. https://doi.org/10.1016/j.apenergy.2011.04.019 doi: 10.1016/j.apenergy.2011.04.019 |
[15] | Shadmand MB, Balog RS (2014) Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid. IEEE Trans Smart Grid 5: 2635–2643. https://doi.org/10.1109/TSG.2014.2315043 doi: 10.1109/TSG.2014.2315043 |
[16] | Zhao B, Zhang X, Chen J, et al. (2013) Operation optimization of standalone microgrids considering lifetime characteristics of battery energy storage system. IEEE Trans Sustainable Energy 4: 934–943. https://doi.org/10.1109/TSTE.2013.2248400 doi: 10.1109/TSTE.2013.2248400 |
[17] | Khan FA, Pal N, Saeed SH (2018) Review of solar photovoltaic and wind hybrid energy systems for sizing strategies optimization techniques and cost analysis methodologies. Renewable Sustainable Energy Rev 92: 937–947. https://doi.org/10.1016/j.rser.2018.04.107 doi: 10.1016/j.rser.2018.04.107 |
[18] | Yang H, Wei Z, Lou C (2009) Optimal design and techno-economic analysis of a hybrid solar-wind power generation system. Appl Energy 86: 163–169. https://doi.org/10.1016/j.apenergy.2008.03.008 doi: 10.1016/j.apenergy.2008.03.008 |
[19] | Vendoti KS, Muralidhar M, Kiranmayi R (2021) Techno-economic analysis of off grid solar/wind/biogas/biomass/fuel cell/battery system for electrification in a cluster of villages by HOMER software. Environ Dev Sustainability 23: 351–372. https://doi.org/10.1007/s10668-019-00583-2 doi: 10.1007/s10668-019-00583-2 |
[20] | Bihari SP, Sadhu PK, Sarita K, et al. (2021) A Comprehensive review of microgrid control mechanism and impact assessment for hybrid renewable energy integration. IEEE Access 9: 88942–88958. https://doi.org/10.1109/ACCESS.2021.3090266 doi: 10.1109/ACCESS.2021.3090266 |
[21] | Bilal BO, Sambou V, Ndiaye PA, et al. (2010) Optimal design of a hybrid solar wind-battery system using the minimization of the annualized cost system and the minimization of the loss of power supply probability (LPSP). Renewable Energy. 35: 2388–2390. https://doi.org/10.1016/j.renene.2010.03.004 doi: 10.1016/j.renene.2010.03.004 |
[22] | Shi Z, Wang R, Zhang T (2015) Multi-objective optimal design of hybrid renewable energy systems using preference-inspired co evolutionary approach. Sol Energy 118: 96–106. https://doi.org/10.1016/j.solener.2015.03.052 doi: 10.1016/j.solener.2015.03.052 |
[23] | Diab AAZ, Sultan HM, Mohamed IS, et al. (2019) Application of different optimization algorithms for optimal sizing of PV/wind/diesel/battery storage stand-alone hybrid microgrid. IEEE Access 7: 119223–119245. https://doi.org/10.1109/ACCESS.2019.2936656 doi: 10.1109/ACCESS.2019.2936656 |
[24] | Bashir M, Sadeh J (2012) Optimal sizing of hybrid wind/photovoltaic/battery considering the uncertainty of wind and photovoltaic power using Monte Carlo. International Conference on Environment and Electrical Engineering, Venice, Italy. https://doi.org/10.1109/EEEIC.2012.6221541 |
[25] | Ma T, Yang H, Lin Lu (2014) Feasibility study of a Stand-Alone Hybrid Solar-Wind-Battery system for a remote island. Appl Energy 121: 149–158. https://doi.org/10.1016/j.apenergy.2014.01.090 doi: 10.1016/j.apenergy.2014.01.090 |
[26] | Adefarati T, Bansal R (2019) Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources. Appl Energy 236: 1089–1114. https://doi.org/10.1016/j.apenergy.2018.12.050 doi: 10.1016/j.apenergy.2018.12.050 |
[27] | Bansal M, Khatod DK, Saini RP (2014) Modeling and optimization of integrated renewable energy system for a rural site. International Conference on Reliability, Optimization and Information Technology—ICROIT, India, 2014. https://doi.org/10.1109/ICROIT.2014.6798289 |
[28] | Gami D, Sioshansi R, Denholm P (2017) Data challenges in estimating the capacity value of solar photovoltaics. IEEE J Photovoltaics 7: 1065–1073. https://doi.org/10.1109/JPHOTOV.2017.2695328 doi: 10.1109/JPHOTOV.2017.2695328 |
[29] | Kamali S, Tyagi VV, Rahim NA, et al. (2013) Emergence of energy storage technologies as the solution for reliable operation of smart power systems: A review. Renewable Sustainable Energy Rev 25: 135–165. https://doi.org/10.1016/j.rser.2013.03.056 doi: 10.1016/j.rser.2013.03.056 |
[30] | Khananm M, Hasan MF, Miyazaki T, et al. (2018) Key factors of solar energy progress in Bangladesh until 2017. Evergreen 5: 77–85. https://doi.org/10.5109/1936220 doi: 10.5109/1936220 |
[31] | Kumar M, Saha BB (2015) Energy security and sustainability in Japan. Evergreen 2: 49–56. https://doi.org/10.5109/1500427 doi: 10.5109/1500427 |
[32] | Gima H, Yoshitake T (2016) Comparative study of energy security in Okinawa Prefecture and the state of Hawaii. Evergreen 3: 36–44. https://doi.org/10.5109/1800870 doi: 10.5109/1800870 |
[33] | Srivastava A, Bajpai RS (2021) Model predictive control of renewable energy sources in DC microgrid for Power flow control. Int J Energy Convers, 9. https://doi.org/10.15866/irecon.v9i4.20152 doi: 10.15866/irecon.v9i4.20152 |
[34] | Suresh V, Muralidhar M, Kiranmayi R (2020) Modelling and optimization of an off-grid hybrid renewable energy system for electrification in a rural areas. Energy Rep 6: 594–604. https://doi.org/10.1016/j.egyr.2020.01.013 doi: 10.1016/j.egyr.2020.01.013 |
[35] | Mariana G, Benevit, Andre G, et al. (2016) Subtle influence of the Weibull Shape Parameter on Homer optimization space of a wind diesel hybrid Gen set for use in southern Brazil. J Power Energy Eng 4: 38–48. http://dx.doi.org/10.4236/jpee.2016.48004 doi: 10.4236/jpee.2016.48004 |
[36] | Nannam HC, Banerjee A (2021) A novel control technique for a single-phase grid-tied inverter to extract peak power from PV-Based home energy systems. AIMS Energy 9: 414–415. https://doi.org/10.3934/energy.2021021 doi: 10.3934/energy.2021021 |
[37] | Gamil M, Lotfy M, Ashraf M, et al. (2021) Optimal sizing of a residential microgrid in Egypt under deterministic and stochastic conditions with PV/WG/Biomass Energy integration. AIMS Energy 9: 483–515. https://doi.org/10.3934/energy.2021024 doi: 10.3934/energy.2021024 |
[38] | Charabi Y, Wahab SA (2020) Wind turbine performance analysis for energy cost minimization. Renewables: Wind, Water Sol, 7. https://doi.org/10.1186/s40807-020-00062-7 doi: 10.1186/s40807-020-00062-7 |
[39] | Alliche M, Rebhi R, Kaid N, et al. (2021) Estimation of the wind energy potential in various North Algerian regions. Energies 14: 7564. https://doi.org/10.3390/en14227564 doi: 10.3390/en14227564 |
[40] | Mohammadi K, Alavi O, Mostafaeipour A, et al. (2016) Assessing different parameters estimation methods of Weibull distribution to compute wind power density. Energy Convers Manage 108: 322–335. https://doi.org/10.1016/j.enconman.2015.11.015 doi: 10.1016/j.enconman.2015.11.015 |
[41] | Celik AN (2003) Energy output estimation for small-scale wind power generators using Weibull-representative wind data. J Wind Eng Indust Aerodynamics 91: 693–707. https://doi.org/10.1016/S0167-6105(02)00471-3 doi: 10.1016/S0167-6105(02)00471-3 |
[42] | Yang D, Jiang C, Cai G, et al. (2020) Interval method based optimal planning of multi-energy microgrid with uncertain renewable generation and demand. Appl Energy 277: 115491. https://doi.org/10.1016/j.apenergy.2020.115491 doi: 10.1016/j.apenergy.2020.115491 |
[43] | Cheng Z, Jia D, Li Z, et al. (2022) Multi-time scale dynamic robust optimal scheduling of CCHP microgrid based on rolling optimization. Int J Electr Power Energy Syst 139: 107957. https://doi.org/10.1016/j.ijepes.2022.107957 doi: 10.1016/j.ijepes.2022.107957 |
[44] | Yang D, Zhang C, Jiang C, et al. (2021) Interval method based optimal scheduling of regional multi-microgrids with uncertainties of renewable energy. IEEE Access 9: 53292–53305. http://10.1109/ACCESS.2021.3070592 doi: 10.1109/ACCESS.2021.3070592 |
[45] | Tang T, Ding H, Nojavan S, et al. (2020). Environmental and economic operation of wind-PV-CCHP-based energy system considering risk analysis via downside risk constraints technique. IEEE Access 8: 124661–124674. https://doi.org/10.1109/ACCESS.2020.3006159 doi: 10.1109/ACCESS.2020.3006159 |
[46] | Zhang H, Yue D, Xie X (2016). Robust optimization for dynamic economic dispatch under wind power uncertainty with different levels of uncertainty budget. IEEE Access 4: 7633–7644. https://doi.org/10.1109/ACCESS.2016.2621338 doi: 10.1109/ACCESS.2016.2621338 |
[47] | Peng C, Xie P, Pan L, et al. (2015) Flexible robust optimization dispatch for hybrid wind/photovoltaic/hydro/thermal power system. IEEE Trans Smart Grid 7: 751–762. https://doi.org/10.1109/TSG.2015.2471102 doi: 10.1109/TSG.2015.2471102 |
[48] | Mohamad F, Teh J, Abunima H (2019) Multi-objective optimization of solar/wind penetration in power generation systems. IEEE Access 7: 169094–169106. https://doi.org/10.1109/ACCESS.2019.2955112 doi: 10.1109/ACCESS.2019.2955112 |
[49] | Farrokhabadi M, Solanki BV, Canizares A, et al. (2017) Energy storage in microgrids: Compensating for generation and demand fluctuations while providing ancillary services. IEEE Power Energy Magazine 15: 81–91. https://doi.org/10.1109/MPE.2017.2708863 doi: 10.1109/MPE.2017.2708863 |
[50] | Nurunnabi M, Roy NK, Hossain E, et al. (2019) Size optimization and sensitivity analysis of hybrid wind/PV micro-grids-a case study for Bangladesh. IEEE Access 7: 150120–150140. https://doi.org/10.1109/ACCESS.2019.2945937 doi: 10.1109/ACCESS.2019.2945937 |