This research article presents a technoeconomic analysis of an RET-based model for powering a hilly remote area telecom tower in Chamba district of Himachal Pradesh, India. Using the HOMER software tool with various evolutionary algorithms, the study found that the most feasible configuration was 30 kW of SP panels, 10 kW of DG units, 20 batteries, and 10 units of converter with a minimum energy cost value of 0.256 $/kWh. The energy cost values from various evolutionary techniques such as HHO, WOA, PSO, and GA were also observed to be competitive. After policy intervention and government subsidies, the cost of energy reduced to 0.167 $/kWh, which is significantly less compared to the diesel-powered system. Furthermore, sensitivity analysis was carried out for changes in solar radiations, ambient temperature, and diesel fuel prices to determine the best optimal configuration for the study.
AbdulwahidUManwellJFMcGowanJG (2007) Development of a dynamic control communication system for hybrid power systems. IET Renewable Power Generation1(1): 70–80.
2.
AdefaratiTBansalRC (2016) Integration of renewable distributed generators into the distribution system: A review. IET Renewable Power Generation10(7): 873–884.
3.
AdefaratiTBansalRC (2019) Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources. Applied Energy236: 1089–1114.
4.
AlaboolHMAlarabiatDAbualigahL, et al. (2021) Harris hawks optimization: A comprehensive review of recent variants and applications. Neural Computing and Applications33: 8939–8980.
5.
AmmariCBelatracheDTouhamiB, et al. (2022) Sizing, optimization, control and energy management of hybrid renewable energy system—A review. Energy and Built Environment3(4): 399–411.
6.
AnandPRizwanMBathSK (2019) Sizing of renewable energy based hybrid system for rural electrification using grey wolf optimisation approach. IET Energy Systems Integration1(3): 158–172.
7.
BevraniHGhoshALedwichG (2010) Renewable energy sources and frequency regulation: Survey and new perspectives. IET Renewable Power Generation4(5): 438–457.
8.
del ValleYVenayagamoorthyGKMohagheghiS, et al. (2008) Particle swarm optimization: Basic concepts, variants and applications in power systems. IEEE Transactions on Evolutionary Computation12(2): 171–195.
9.
EsminAAACoelhoRAMatwinS (2015) A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. Artificial Intelligence Review44(1): 23–45.
10.
EsminAAALambert-TorresGZambroni de SouzaAC (2005) A hybrid particle swarm optimization applied to loss power minimization. IEEE Transactions on Power Systems20(2): 859–866.
11.
GadAG (2022) Particle swarm optimization algorithm and its applications: A systematic review. Archives of Computational Methods in Engineering29: 2531–2561.
12.
HeidariAAMirjaliliSFarisH, et al. (2019) Harris hawks optimization: Algorithm and applications. Future Generation Computer Systems97: 849–872.
Intelligent Energy (2012) The True Cost of Providing Energy to Telecom Towers in India. Intelligent Energy Limited.
15.
KrishnaR (2012) Green Energy Technology (GET) for Telecom Applications. TEC New Delhi: DoT, Govt. of India.
16.
KumarASinghARDengY, et al. (2019b) Integrated assessment of a sustainable microgrid for a remote village in hilly region. Energy Conversion and Management180: 442–472.
17.
KumarSKaurT (2020) Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights. Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy234(6): 862–873.
18.
KumarSKaurTAroraMK, et al. (2019a) Resource estimation and sizing optimization of PV/micro hydro-based hybrid energy system in rural area of Western Himalayan Himachal Pradesh in India. Energy Sources Part A Recovery Utilization and Environmental Effects41(22): 2795–2807.
19.
KumarSKumarVKatalN, et al. (2021) Multiarea economic dispatch using evolutionary algorithms. Mathematical Problems in Engineering2021(3577087): 1–14. 2021.
20.
KumarVSharmaVAryaY, et al. (2022b) Stochastic wind energy integrated multi source power system control via a novel model predictive controller based on Harris Hawks optimization. Energy Sources Part A Recovery Utilization and Environmental Effects44(4): 10694–10719.
21.
KumarVSharmaVNareshR (2022a) Optimal voltage and frequency control in solar integrated power network. Distributed Generation & Alternative Energy Journal37(3): 703–724.
22.
KumarVSharmaVNareshR (2023) Leader Harris Hawks algorithm based optimal controller for automatic generation control in PV-hydro-wind integrated power network. Electric Power Systems Research214: 108924.
23.
KumarSSharmaSSoodYR, et al. (2022) A review on different parametric aspects and sizing methodologies of hybrid renewable energy system. Journal of The Institution of Engineers (India) Series B103: 1345–1354.
24.
Kumar LalDBhusan DashBAkellaAK (2011) Optimization of PV/wind/micro-hydro/diesel hybrid power system in HOMER for the study area. International Journal on Electrical Engineering and Informatics3: 307–325.
25.
LiangXXuSLiuY, et al. (2022) A modified whale optimization algorithm and its application in seismic inversion problem. Mobile Information Systems. Epub ahead of print 24 January 2022. DOI: 10.1155/2022/9159130.
26.
MirjaliliSLewisA (2016) The whale optimization algorithm. Advances in Engineering Software95: 51–67.
27.
NikmehrNNajafi-RavadaneghS (2015) Optimal operation of distributed generations in micro-grids under uncertainties in load and renewable power generation using heuristic algorithm. IET Renewable Power Generation9(8): 982–990.
28.
NingGYCaoDQ (2021) Improved whale optimization algorithm for solving constrained optimization problems. Discrete Dynamics in Nature and Society. Epub ahead of print 9 February 2021. DOI: 10.1155/2021/8832251.
29.
OnarOCShiraziOHAKhalighA (2010) Grid interaction operation of a telecommunications power system with a novel topology for multiple-input buck-boost converter. IEEE Transactions on Power Delivery25: 2633–2645.
30.
RajannaSSainiRP (2016) Development of optimal integrated renewable energy model with battery storage for a remote Indian area. Energy111: 803–817.
31.
RanaNLatiffMSAAbdulhamidSM, et al. (2020) Whale optimization algorithm: A systematic review of contemporary applications, modifications and developments. Neural Computing and Applications32: 16245–16277.
32.
SadeghiDAmiriNMarzbandM, et al. (2022) Optimal sizing of hybrid renewable energy systems by considering power sharing and electric vehicles. International Journal of Energy Research46(6): 8288–8312.
33.
SharmaSSoodYR (2021) Optimal planning and sensitivity analysis of green microgrid using various types of storage systems. Wind Engineering45(4): 939–952.
34.
SharmaSSoodYR (2022a) Microgrids: A review of status, technologies, software tools, and issues in Indian power market. IETE Technical Review39(2): 411–432.
35.
SharmaSSoodYR (2022b) Optimal planning of green microgrid with minimisation of environmental emissions. International Journal of Ambient Energy43(1): 7531–7540.
36.
SharmaSSoodYRMaheshwariA, et al. (2022b) Modeling and analysis of autonomous hybrid green microgrid system for the electrification of rural area. In: KumarSGuptaNKumarS, et al. (eds) Renewable Energy Systems. New York: Wiley.
37.
SharmaSSoodYRSharmaNK, et al. (2022a) Modeling and sensitivity analysis of grid-connected hybrid green microgrid system. Ain Shams Engineering Journal13(4): 101679.
38.
SinghRBansalRC (2018) Review of HRESs based on storage options, system architecture and optimisation criteria and methodologies. IET Renewable Power Generation12(7): 747–760.
39.
SinghRBansalRC (2019) Optimization of an autonomous hybrid renewable energy system using reformed electric system cascade analysis. IEEE Transactions on Industrial Informatics15: 399–409.
TangSTanLLiuT (2021) Modeling and performance analysis of energy harvesting wireless communication systems with reliable energy backup. International Journal of Communication Systems34: e4698.
42.
TripathyBKReddy MaddikuntaPKPhamQV, et al. (2022) Harris Hawk optimization: A survey on variants and applications. Computational Intelligence and Neuroscience. Epub ahead of print 27 June 2022. DOI: 10.1155/2022/2218594.
43.
UpadhyaySSharmaMP (2016) Selection of a suitable energy management strategy for a hybrid energy system in a remote rural area of India. Energy94: 352–366.
44.
Ur RehmanZFatimaMKhanA, et al. (2019) Energy optimization in a smart community grid system using genetic algorithm. International Journal of Communication Systems e4265.
