# Optimization of a novel Hybrid Wind Bio Battery Solar Photovoltaic System Integrated with Phase Change Material

^{1}

^{2}

^{3}

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## Abstract

**:**

## 1. Introduction

^{3}, with a total net present cost (NPC) of USD 0.813 million. Rezzouk and Mellit [9] carried out the techno-economic feasibility and sensitivity analysis of a PV-Diesel-Battery-operated HRES, with the penetration of PV varying from 0% to 100%. From the results, it can be observed that system stability and optimum performance can be achieved with 25% PV penetration. A sensitivity analysis showed that global radiation has a significant effect on the NPC and CoE of the system. Rahman et al. [10] showed that biogas and solar systems can be integrated to develop a hybrid energy system that can meet both electrical load and thermal (cooking) demands, and can efficiently replace conventional facilities. The results also show that monetary savings worth USD 309 to 412 per year can be achieved by using the proposed hybrid renewable energy system. Considering climate diversity and the energy efficiency of buildings, Mokhtara et al. [11] investigated the optimal sizing and mapping of hybrid renewable energy systems for an off-grid building at seven different locations in Algeria. The results show that climate zone and the energy performance of the building have significant effects on the optimal sizing of the HRES. The study makes recommendations related to efficient energy management between energy sources, stored energy and load demand for the optimization of the overall HRES. Baruah et al. [12] carried out techno-economic feasibility analyses of an HRES for the academic township in Sikkim, India, using HOMER. The results show that the optimum system is a PV-Wind-Biogas-Syngas-Hydrokinetic-Battery-based system with an LCOE of USD 0.095/kWh. Al-bonsrulah et al. [13] carried out an analysis of a hybrid system for the Bahr Al-Najaf region. The results show that the energy contributions of fuel cell, wind turbine and PV are 4.38%, 26.3% and 69.3%, respectively. Katsivelakis et al. [14] performed a techno-economic analysis of a hybrid renewable energy system on Donoussa Island, Greece, by varying the contributions (20%, 50% and 100%) of renewable energy resources. The results show that with a 50% renewable energy contribution, a system can be obtained with 0% excess energy, an NPC of EUR 4,031,102.3 and a COE of EUR 0.2401/kWh. Kanase-Patil et al. [15] showed that an HRES with micro hydropower, biomass, biogas, solar energy, wind and energy plantation, with individual contributions of 44.99%, 30.07%, 5.19%, 4.16%, 1.27% and 12.33%, respectively, can provide for the electrical and cooking needs of seven off-grid villages in Uttarakhand, India. The results also showed that the optimal HRES system had 0.95 energy index ratio, at the optimized cost of Rs 19.44 lacs and a COE of Rs 3.36 per unit.

_{2}SO

_{4}.10H

_{2}O) as the PCM, showed that the electrical efficiency of the PV panel was increased by 10% due to a reduction in its operating temperature by 8 °C. Stropnik and Stritih [23] showed that, with PCM, the surface temperature of the PV panel can be lowered by a maximum of 35.6 °C, resulting in 9.2% additional power compared to a conventional PV panel. Khanna et al. [24] analyzed a finned PCM integrated PV panel, showing that the power produced by the PV panel in a warmer climate increases in the range of 10.1% to 12.1%, and in colder climates it increases in the range of 5.4% to 6.7%, as compared to the reference PV panel.

## 2. Description of the Proposed System

- (i)
- Conf-1—PV–Wind–Battery system;
- (ii)
- Conf-2—PV–PCM–Wind–Battery system;
- (iii)
- Conf-3—PV–Wind–Biogas–Battery system;
- (iv)
- Conf-4—PV–PCM–Wind–Biogas–Battery system.

## 3. Description, Mathematical Modeling and Specification of System Components

#### 3.1. Wind Energy System

^{−1}.

^{−1}) at height H (m) and at reference height ${H}_{ref}$ (m), respectively, and α is the power law coefficient. Figure 2 shows the wind speed at the IIT Madras, Chennai, India, for the whole year, and Table 1 shows the specifications.

#### 3.2. PV System

_{I}), the area of a panel (A), the number of panels (N), the operating temperature of the cell (T

_{c}), the efficiency at STC (${\eta}_{o}$) and the degradation factor (d

_{PV}). Maximum energy is obtained from the PV panel when it operates in MPPT mode. The power output of the PV panel is given by Equation (3) [29].

#### 3.3. Phase Change Material

#### 3.4. PV-PCM System

#### 3.5. Biogas Generator

#### 3.6. Battery Bank Energy Storage System

_{bat}is the battery current at time t (A), ƞ

_{bat}is the battery charge efficiency and C

_{bat}is the capacity of the battery.

_{pv/PCM}(t) is the instantaneous power generated by the PV/PCM module, P

_{wind}(t) is the instantaneous power generated by the wind turbine, P

_{load}(t) is the instantaneous power demand and V

_{bat}(t) is the terminal voltage of the battery. The capacity of the battery C

_{bat}is calculated by Equation (7) [39].

_{load}is the total energy demand, AD is the daily autonomy, DOD is the depth of discharge of the battery, η

_{inv}is the inventor efficiency, and η

_{bat}is the battery efficiency.

#### 3.7. Converter System

_{inv,out}is the output power of the inverter, η

_{inv}is the efficiency of the inverter, P

_{DC}is the DC power input, P

_{rec,out}is the output power of the rectifier, η

_{rec}is the efficiency of the rectifier and P

_{AC}is the AC power input.

#### 3.8. Load Profile

#### 3.9. Constraints

#### 3.9.1. Lower and Upper Limit of Energy Source

_{PV-PCM}, N

_{WT}, N

_{Biogen}and N

_{Batt}are the capacities of the PV-PCM panels, the wind turbine and the biogas generator, and the number of batteries, respectively. The capacity values of all the system components are considered as integer values.

#### 3.9.2. Battery Bank Operational Constraint

_{Battmin}≤ E

_{Batt}(t) ≤ E

_{Battmax}

_{Battmin}and E

_{Battmax}are, respectively, the maximum and minimum allowed energy values of the battery bank.

#### 3.9.3. Wind Turbine Operational Constraints

_{Ci}≤ V (t) ≤ V

_{Co}

#### 3.9.4. Power Reliability Constraints

_{Dem}(t) − E

_{WT}(t) − E

_{PV/PCM}(t) − E

_{Biogen}(t) − E

_{Batt}(t)

## 4. System Operation and Optimization

#### 4.1. Control Strategy and Operation

- (i)
- To maximize the utilization of energy from PV and wind energy sources;
- (ii)
- To minimize the storage capacity and operation of the battery bank;
- (iii)
- To minimize the operation of the biogas generator so as to reduce the emissions and the operation and maintenance cost.

#### 4.2. Net Present Cost

#### 4.3. Cost of Energy

_{ann}) to the total energy generated by the integrated system. COE includes capital cost, fuel cost, financing cost, and O&M cost. COE is an important parameter for the optimization of the integrated renewable energy system. COE signifies the revenue per unit of electric unit sold to recover the investment and operation cost of the system. The COE is calculated using Equation (16),

#### 4.4. Capital Recovery Factor

## 5. Results and Discussion

#### 5.1. Energy Analysis

#### 5.2. Economic Analysis

## 6. Sensitive Analysis

#### 6.1. Variation in PV-PCM Panel Cost

#### 6.2. Variation in Wind Turbine Cost

#### 6.3. Variation in Biogas Generator Cost

#### 6.4. Variation in Battery Cost

## 7. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- UN. United nations—sustainable energy for all initiative launched in 2011. Available online: https://www.seforall.org/goal-7-targets/access (accessed on 2 October 2021).
- Al Siyabi, I.; Al Mayasi, A.; Al Shukaili, A.; Khanna, S. Effect of Soiling on Solar Photovoltaic Performance under Desert Climatic Conditions. Energies
**2021**, 14, 659. [Google Scholar] [CrossRef] - Duran, D.C.; Gogan, L.M.; Artene, A.; Duran, V. The Components of Sustainable Development—A Possible Approach. Procedia Econ. Financ.
**2015**, 26, 806–811. [Google Scholar] [CrossRef] [Green Version] - Tito, S.R.; Lie, T.T.; Anderson, T.N. Optimal sizing of a wind-photovoltaic-battery hybrid renewable energy system considering socio-demographic factors. Sol. Energy
**2016**, 136, 525–532. [Google Scholar] [CrossRef] [Green Version] - Jamshidi, S.; Pourhossein, K.; Asadi, M. Size estimation of wind/solar hybrid renewable energy systems without detailed wind and irradiation data: A feasibility study. Energy Convers. Manag.
**2021**, 234, 113905. [Google Scholar] [CrossRef] - Alberizzi, J.C.; Frigola, J.M.; Rossi, M.; Renzi, M. Optimal sizing of a Hybrid Renewable Energy System: Importance of data selection with highly variable renewable energy sources. Energy Convers. Manag.
**2020**, 223, 113303. [Google Scholar] [CrossRef] - Martín-Arroyo, S.; Cebollero, J.A.; García-Gracia, M.; Llamazares, Á. Stand-Alone Hybrid Power Plant Based on SiC Solar PV and Wind Inverters with Smart Spinning Reserve Management. Electronics
**2021**, 10, 796. [Google Scholar] [CrossRef] - Das, M.; Singh, M.A.K.; Biswas, A. Techno-economic optimization of an off-grid hybrid renewable energy system using metaheuristic optimization approaches—Case of a radio transmitter station in India. Energy Convers. Manag.
**2019**, 185, 339–352. [Google Scholar] [CrossRef] - Rezzouk, H.; Mellit, A. Feasibility study and sensitivity analysis of a stand-alone photovoltaic–diesel–battery hybrid energy system in the north of Algeria. Renew. Sustain. Energy Rev.
**2015**, 43, 1134–1150. [Google Scholar] [CrossRef] - Rahman, M.; Hasan, M.M.; Paatero, J.; Lahdelma, R. Hybrid application of biogas and solar resources to fulfill household energy needs: A potentially viable option in rural areas of developing countries. Renew. Energy
**2014**, 68, 35–45. [Google Scholar] [CrossRef] [Green Version] - Mokhtara, C.; Negrou, B.; Settou, N.; Settou, B.; Samy, M.M. Design optimization of off-grid Hybrid Renewable Energy Systems considering the effects of building energy performance and climate change: Case study of Algeria. Energy
**2020**, 219, 119605. [Google Scholar] [CrossRef] - Baruah, A.; Basu, M.; Amuley, D. Modeling of an autonomous hybrid renewable energy system for electrification of a township: A case study for Sikkim, India. Renew. Sustain. Energy Rev.
**2020**, 135, 110158. [Google Scholar] [CrossRef] - Al-Bonsrulah, H.; Alshukri, M.; Mikhaeel, L.; Al-Sawaf, N.; Nesrine, K.; Reddy, M.; Zaghib, K. Design and Simulation Studies of Hybrid Power Systems Based on Photovoltaic, Wind, Electrolyzer, and PEM Fuel Cells. Energies
**2021**, 14, 2643. [Google Scholar] [CrossRef] - Katsivelakis, M.; Bargiotas, D.; Daskalopulu, A.; Panapakidis, I.; Tsoukalas, L. Techno-Economic Analysis of a Stand-Alone Hybrid System: Application in Donoussa Island, Greece. Energies
**2021**, 14, 1868. [Google Scholar] [CrossRef] - Kanase-Patil, A.; Saini, R.; Sharma, M. Integrated renewable energy systems for off grid rural electrification of remote area. Renew. Energy
**2010**, 35, 1342–1349. [Google Scholar] [CrossRef] - Elavarasan, R.M.; Leoponraj, S.; Dheeraj, A.; Irfan, M.; Sundar, G.G.; Mahesh, G. PV-Diesel-Hydrogen fuel cell based grid connected configurations for an institutional building using BWM framework and cost optimization algorithm. Sustain. Energy Technol. Assess.
**2021**, 43, 100934. [Google Scholar] [CrossRef] - Kumar, N.; Chopra, S.; Chand, A.; Elavarasan, R.; Shafiullah, G. Hybrid Renewable Energy Microgrid for a Residential Community: A Techno-Economic and Environmental Perspective in the Context of the SDG7. Sustainability
**2020**, 12, 3944. [Google Scholar] [CrossRef] - Li, C.; Ge, X.; Zheng, Y.; Xu, C.; Ren, Y.; Song, C.; Yang, C. Techno-economic feasibility study of autonomous hybrid wind/PV/battery power system for a household in Urumqi, China. Energy
**2013**, 55, 263–272. [Google Scholar] [CrossRef] - Wu, Q.; Zhou, J.; Liu, S.; Yang, X.; Ren, H. Multi-objective Optimization of Integrated Renewable Energy System Considering Economics and CO
_{2}Emissions. Energy Procedia**2016**, 104, 15–20. [Google Scholar] [CrossRef] - Suleman, F.; Dincer, I.; Agelin-Chaab, M. Development of an integrated renewable energy system for multigeneration. Energy
**2014**, 78, 196–204. [Google Scholar] [CrossRef] - Chang, P.-L.; Hsu, C.-W.; Hsiung, C.-M.; Lin, C.-Y. Constructing an innovative Bio-Hydrogen Integrated Renewable Energy System. Int. J. Hydrogen Energy
**2013**, 38, 15660–15669. [Google Scholar] [CrossRef] - Karthick, A.; Murugavel, K.K.; Ramanan, P. Performance enhancement of a building-integrated photovoltaic module using phase change material. Energy
**2018**, 142, 803–812. [Google Scholar] [CrossRef] - Stropnik, R.; Stritih, U. Increasing the efficiency of PV panel with the use of PCM. Renew. Energy
**2016**, 97, 671–679. [Google Scholar] [CrossRef] - Khanna, S.; Reddy, K.S.; Mallick, T.K. Effect of climate on electrical performance of finned phase change material integrated solar photovoltaic. Sol. Energy
**2018**, 174, 593–605. [Google Scholar] [CrossRef] - Khanna, S.; Newar, S.; Sharma, V.; Reddy, K.; Mallick, T.K. Optimization of fins fitted phase change material equipped solar photovoltaic under various working circumstances. Energy Convers. Manag.
**2019**, 180, 1185–1195. [Google Scholar] [CrossRef] - Khanna, S.; Newar, S.; Sharma, V.; Reddy, K.; Mallick, T.K.; Radulovic, J.; Khusainov, R.; Hutchinson, D.; Becerra, V. Electrical enhancement period of solar photovoltaic using phase change material. J. Clean. Prod.
**2019**, 221, 878–884. [Google Scholar] [CrossRef] [Green Version] - Roque, P.; Chowdhury, S.; Huan, Z. Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study. Energies
**2021**, 14, 4291. [Google Scholar] [CrossRef] - Chauhan, A.; Saini, R. Techno-economic optimization based approach for energy management of a stand-alone integrated renewable energy system for remote areas of India. Energy
**2016**, 94, 138–156. [Google Scholar] [CrossRef] - Klugmann-Radziemska, E.; Wcisło-Kucharek, P. Photovoltaic module temperature stabilization with the use of phase change materials. Sol. Energy
**2017**, 150, 538–545. [Google Scholar] [CrossRef] - Reddy, K.; Mudgal, V.; Mallick, T. Review of latent heat thermal energy storage for improved material stability and effective load management. J. Energy Storage
**2018**, 15, 205–227. [Google Scholar] [CrossRef] - Reddy, K.S.; Mudgal, V.; Mallick, T.K. Thermal Performance Analysis of Multi-Phase Change Material Layer-Integrated Building Roofs for Energy Efficiency in Built-Environment. Energies
**2017**, 10, 1367. [Google Scholar] [CrossRef] [Green Version] - Ahmad, A.; Navarro, H.; Ghosh, S.; Ding, Y.; Roy, J. Evaluation of New PCM/PV Configurations for Electrical Energy Efficiency Improvement through Thermal Management of PV Systems. Energies
**2021**, 14, 4130. [Google Scholar] [CrossRef] - Bandaru, S.; Becerra, V.; Khanna, S.; Radulovic, J.; Hutchinson, D.; Khusainov, R. A Review of Photovoltaic Thermal (PVT) Technology for Residential Applications: Performance Indicators, Progress, and Opportunities. Energies
**2021**, 14, 3853. [Google Scholar] [CrossRef] - Al Siyabi, I.; Khanna, S.; Sundaram, S.; Mallick, T. Experimental and Numerical Thermal Analysis of Multi-Layered Microchannel Heat Sink for Concentrating Photovoltaic Application. Energies
**2019**, 12, 122. [Google Scholar] [CrossRef] [Green Version] - Singh, P.; Khanna, S.; Becerra, V.; Newar, S.; Sharma, V.; Mallick, T.K.; Hutchinson, D.; Radulovic, J.; Khusainov, R. Power improvement of finned solar photovoltaic phase change material system. Energy
**2020**, 193, 116735. [Google Scholar] [CrossRef] - Japs, E.; Sonnenrein, G.; Steube, J.; Vrabec, J.; Kenig, E.; Krauter, S. Technical Investigation of a Photovoltaic Module with Integrated Improved Phase Change Material. In Proceedings of the 28th European photovoltaic solar energy conference and exhibition, Paris, France, 30 September–4 October 2013. [Google Scholar] [CrossRef]
- Specification, Test Generator; Sawafuji Electric Co., Ltd. ELEMAX Generator SH7600EX: Owner’s Manual; 2015; Available online: http://www.elemax.jp/products_ex.html (accessed on 22 March 2021).
- Chiasson, J.; Vairamohan, B. Estimating the State of Charge of a Battery. IEEE Trans. Control Syst. Technol.
**2005**, 13, 465–470. [Google Scholar] [CrossRef] - Singh, A.; Baredar, P.; Gupta, B. Techno-economic feasibility analysis of hydrogen fuel cell and solar photovoltaic hybrid renewable energy system for academic research building. Energy Convers. Manag.
**2017**, 145, 398–414. [Google Scholar] [CrossRef] - Kashefi Kaviani, A.; Riahy, G.H.; Kouhsari, S.M. Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages. Renew Energy
**2009**, 34, 2380–2390. [Google Scholar] [CrossRef] - Lian, J.; Zhang, Y.; Ma, C.; Yang, Y.; Chaima, E. A review on recent sizing methodologies of hybrid renewable energy systems. Energy Convers. Manag.
**2019**, 199, 112027. [Google Scholar] [CrossRef]

**Table 1.**Specifications of the wind turbine [28].

Parameter | Unit | Value |
---|---|---|

Pr | kW | 3 |

Vr | m/s | 12 |

Vci | m/s | 3.1 |

Vco | m/s | 24 |

Rated voltage | V | 240 |

Rotor diameter | m | 4.5 |

Swept area | m^{2} | 15.1 |

Parameter | Unit | Value |
---|---|---|

P_{max} | W | 250 |

V_{oc} | V | 37.9 |

I_{sc} | A | 8.59 |

V_{@Pmax} | V | 30.94 |

I_{@Pmax} | A | 8.08 |

FF | % | 76.11 |

${\eta}_{o}$at STC | % | 15.9 |

Thermophysical Properties | Unit | Specification |
---|---|---|

Melting point | °C | 30 |

Heat of fusion | kJ kg^{−1} | 191 |

Thermal conductivity | W m^{−1}C^{−1} | 1.08 |

Density | kg/l | 1.71 |

Specific heat capacity | kJ kg^{−1} K^{−1} | 1.4 |

Kinematic viscosity | m^{2} s^{−1} | 1.84 × 10^{−3} |

Thermal expansion coefficient | K^{−1} | 5.0 × 10^{−4} |

**Table 4.**Specifications of generator [36].

Parameter | Specification |
---|---|

Model | ELEMAX SH5300EX Generator |

Engine type | 4-stroke, single cylinder, side valve, Spark ignition engine |

Ignition system | Transistorized coil ignition (TCI) |

Rated power | 6.3 kW @ 3600 rpm |

Generator AC output | 5.3 kVA @ 220 V, 60 Hz |

Cooling system | Forced air cooling |

Component | Energy Availability | Constraint | Priority Level | Remarks |
---|---|---|---|---|

PV | Sunny hours | Night time, cloudy sky | 1 | Cheapest source of energy, no prime mover, no emission, less maintenance |

Wind turbine | High wind speed | Low and very high wind speed | 2 | Cheap source of energy, no emission, regular maintenance cost |

Battery bank | When SOC is more than zero | Overcharging and discharging | 3 | Stored renewable energy can be used, no emission |

Biogas generator | Always available | Over winding heating limit | 4 | Involves running cost and regular maintenance cost due to prime mover emission |

Component | Capital Cost (in USD) | O&M Cost (in USD) | Replacement Cost (in USD) | Life |
---|---|---|---|---|

Wind turbine | 934/kW | 50/kW/year | 934/kW | 25 years |

PV Panel | 300/kW | 20/kW/year | 300/kW | 25 years |

PV-PCM Panel | 400/kW | 25/kW/year | 400/kW | 25 years |

Solar inverter and control panel | 180/kW | 8/kW/year | 180/kW | 15 years |

Battery (200 Ah, 12 V) | 150/batt | 5/batt/year | 110/batt | 5 years |

Biogas generator | 400/kW | 0.01/kWh | 300/kW | 20,000 h |

Configuration | Component | Capacity Factor (%) | Penetration Factor (%) | H of Operation/y | Energy Contribution (kWh/y) |
---|---|---|---|---|---|

Conf-1 | Wind turbine | 28.4 | 130 | 7564 | 1,198,517 |

Solar PV | 17 | 132 | 4373 | 1,217,961 | |

Rectifier | 3.02 | - | 2347 | - | |

Inverter | 11.4 | - | 4268 | - | |

Conf-2 | Wind turbine | 28.4 | 113 | 7564 | 1,037,968 |

Solar PV-PCM | 17.3 | 150 | 4373 | 1,380,474 | |

Rectifier | 2.29 | - | 2147 | - | |

Inverter | 10.1 | - | 4687 | - | |

Conf-3 | Wind turbine | 28.4 | 103 | 7564 | 944,626 |

Solar PV | 17.3 | 37.1 | 4373 | 340,835 | |

Biogas gen | 4.71 | - | 1260 | 173,320 | |

Rectifier | 5.39 | - | 2674 | - | |

Inverter | 14.2 | - | 3962 | - | |

Conf-4 | Wind turbine | 28.4 | 92.6 | 7564 | 851,283 |

Solar PV-PCM | 17 | 42.8 | 4373 | 394,079 | |

Biogas gen | 5.44 | - | 1477 | 200,266 | |

Rectifier | 4.36 | - | 2517 | - | |

Inverter | 13.2 | - | 4055 | - |

Component | Principal Cost (in USD) | O&M Cost (in USD) | Replacement Cost (in USD) | Fuel Cost (in USD) | Salvage Cost (in USD) | Total (USD) | |
---|---|---|---|---|---|---|---|

Conf-1 | Wind turbine | 449,400 | 207,487 | 0 | 0 | 0 | 656,887 |

PV | 286,506 | 264,558 | 0 | 0 | 0 | 551,064 | |

Converter and control panel | 56,957 | 32,725 | 24,165 | 0 | 4548 | 109,300 | |

Battery | 592,650 | 255,383 | 383,950 | 0 | 52,057 | 1,179,926 | |

Complete HRES | 1,385,513 | 760,152 | 408,116 | 0 | 56,605 | 2,497,177 | |

Conf-2 | Wind turbine | 389,200 | 179,692 | 0 | 0 | 0 | 568,892 |

PV-PCM | 234,300 | 194,120 | 0 | 0 | 0 | 428,420 | |

Converter and control panel | 70,377 | 40,413 | 29,842 | 0 | 5617 | 135,015 | |

Battery | 597,000 | 257,258 | 386,769 | 0 | 52,440 | 1,188,587 | |

Complete HRES | 1,290,877 | 671,483 | 416,611 | 0 | 58,057 | 2,320,914 | |

Conf-3 | Wind turbine | 319,200 | 147,373 | 0 | 0 | 0 | 466,573 |

PV | 92,700 | 85,599 | 0 | 0 | 0 | 178,299 | |

Converter and control panel | 33,184 | 19,066 | 14,079 | 0 | 2649 | 63,680 | |

Battery | 97,050 | 41,850 | 179,018 | 0 | 4642 | 313,276 | |

Biogas generator | 168,000 | 80,195 | 96,115 | 302,591 | 16,249 | 630,652 | |

Complete HRES | 710,134 | 374,083 | 289,212 | 302,591 | 23,540 | 1,652,480 | |

Conf-4 | Wind turbine | 217,622 | 127,373 | 0 | 0 | 0 | 344,995 |

PV-PCM | 89,600 | 72,617 | 0 | 0 | 0 | 162,217 | |

Converter and control panel | 30,585 | 17,573 | 14,079 | 0 | 2442 | 59,795 | |

Battery | 98,400 | 43,191 | 182,354 | 0 | 4832 | 319,113 | |

Biogas generator | 168,000 | 68,412 | 80,974 | 261,156 | 27,165 | 551,377 | |

Complete HRES | 604,207 | 329,166 | 277,407 | 261,156 | 34,439 | 1,437,497 |

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**MDPI and ACS Style**

Mudgal, V.; Singh, P.; Khanna, S.; Pandey, C.; Becerra, V.; Mallick, T.K.; Reddy, K.S.
Optimization of a novel Hybrid Wind Bio Battery Solar Photovoltaic System Integrated with Phase Change Material. *Energies* **2021**, *14*, 6373.
https://doi.org/10.3390/en14196373

**AMA Style**

Mudgal V, Singh P, Khanna S, Pandey C, Becerra V, Mallick TK, Reddy KS.
Optimization of a novel Hybrid Wind Bio Battery Solar Photovoltaic System Integrated with Phase Change Material. *Energies*. 2021; 14(19):6373.
https://doi.org/10.3390/en14196373

**Chicago/Turabian Style**

Mudgal, Vijay, Preeti Singh, Sourav Khanna, Chandan Pandey, Victor Becerra, Tapas K. Mallick, and K. S. Reddy.
2021. "Optimization of a novel Hybrid Wind Bio Battery Solar Photovoltaic System Integrated with Phase Change Material" *Energies* 14, no. 19: 6373.
https://doi.org/10.3390/en14196373