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

The intermittent nature of renewable sources, such as solar and wind, leads to the need for a hybrid renewable energy system (HRES) that can provide uninterrupted and reliable energy to a remote and off-grid location with the use of a biogas generator and battery. In the present study, conventional PV panels have been integrated with phase change material (PCM) for power enhancement. In addition, various configurations (i. PV-Wind-Battery system, ii. PV-PCM-Wind-Battery, iii. PV-Wind-Biogas-Battery and iv. PV-PCM-Wind-Biogas-Battery) have been compared for the hot and humid climatic location of Chennai, India. Optimization has been carried out to minimize the cost of energy and the net present cost has also been computed. It has been found that the integration of PCM with the PV-Wind-Biogas-Battery-based off-grid system results in savings of USD 0.22 million in terms of net present cost and reduces the cost of energy from USD 0.099/kWh to USD 0.094/kWh. Similarly, for another off-grid HRES configuration of PV-Wind-Battery, the integration of PCM results in savings of USD 0.17 million, and reduces the cost of energy from USD 0.12/kWh to USD 0.105/kWh.


Introduction
The availability of energy plays a very important role in the economic growth and sustainable development of a society and nation. Around 10% of the world's population (789 million people), especially in remote areas, live without electricity [1]. Some of the reasons behind this include the high financial cost of the extension of a grid network to such areas, low population density, and several other cultural and social aspects. Most of the people in these regions depend on fossil fuel and locally available traditional fuels, such as wood and animal waste, to meet their energy demand, due to its easy availability. However, there are several problems associated with using fossil fuel, such as high variability in the prices, environmental degradation, and health issues. One of the solutions to overcome the drawbacks of fossil fuel and provide clean and easy electricity in these regions is using available renewable energy sources in that region [2]. This also results in economic development, an improved ecological balance and human development [3]. However, the intermittent and unpredicted power output of renewable sources results in a nonviable power supply and creates the need for a methodology for obtaining reliable energy and winter peak load demands of 6.33% and 11.5%, respectively. Kumar et al. [17] carried out a techno-economic and environmental study of a residential community in South India, considering the SDG7 goals by integrating different system configurations of a photovoltaic/wind turbine/diesel generator/battery energy storage system (PV/WT/DG/BESS). The results show that a hybrid renewable energy system with PV + DG + BESS is the most cost-effective configuration for the location of the study. Li et al. [18] carried out a technoeconomic feasibility study of a hybrid renewable system used to meet the load demand of a house in Urumqi, China, using different configurations of energy source. The result shows that the total net present cost (NPC) of the system can be reduced by 9% and 11% compared with a PV/battery and wind/battery power system if a hybrid system is used employing PV/wind/battery. The sensitivity study performed by the authors also shows that the total PV module generation of a hybrid system combined with a tracking system is greater than that of a system with an optimized PV module tilt angle.
Wu et al. [19] carried out the multi-objective optimization of an HRES integrating biomass CHP, PV and a heat storage system, considering economic and environmental emissions. The result shows that the optimized system with percentage contributions from CHP, PV and grid of 51.22%, 1.54% and 47.24%, respectively, can facilitate a tradeoff between economic factors and emissions. Suleman et al. [20] developed an HRES employing solar and geothermal energy for multigeneration applications. The result shows that by combing these two energy sources, the overall energy and exergy efficiency of the system can reach 54.7% and 76.4%, respectively. Chang et al. [21] studied a biohydrogen-based renewable system (BHIRES), which integrates the hydrogen generation of biomass fermentation, renewable energy power generation, and electrolysis, for hydrogen production and its further storage, and uses fuel cells for heat and power generation. The analysis showed that the BHIRES is cost-effective as compared to wind/PV/hydrogen, and reduces the cost of energy of the system by 9.6% from USD 1.005 kWh to USD 0.908 kWh. The result also shows that the BHIRES system reduces the final cost of the system by 11.6% as compared to a wind/PV/hydrogen system. The experiment conducted by Karthick et al. [22] on an integrated PV-PCM system at Kovilpatti, Tamil Nadu, India, using glauber salt (Na 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.
From the literature review, it can be observed that several researchers have optimized a hybrid renewable energy system using different technologies and methodologies. However, no work has been found in the literature where a phase change material has been integrated with a PV and hybrid renewable energy system. Phase change materials have the ability to cool down the PV [25] and store huge amount of energy in a latent form, consequently increasing the PV electrical efficiency [26]. The present study investigates how the integration of a phase change material with a PV panel will affect the optimization of the HRES, which thus has the potential to reduce the cost of energy. The mathematical modeling and optimization of the system have been carried out.

Description of the Proposed System
In order to analyze the effects of different components, such as the PV, wind turbine, PCM, biogas and battery, on the overall performance and cost of the hybrid renewable energy system, four different configurations have been considered, as follows: (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.
The PV panel, wind turbine and battery bank are connected to the DC bus, whereas the biogas generator and electric load are connected to the AC bus. To maintain the flow of energy between the components of the HRES, a converter is used, which converts an alternating current (AC) to a direct current (DC), or vice versa. The control panel is the heart of the whole system, and it controls the flow of energy between the components. Figure 1 shows the schematic representation of the proposed HRES.

Wind Energy System
A wind turbine is a device that converts the kinetic energy of wind into electrical energy. The power output of the wind turbine depends upon various factors, such as the turbine's size, the wind speed and the height of the rotor, and is given by Equation (1) [27] where a and b are given by a = , P R is the rated power of the turbine (W), V ci is the cut-in wind speed, V r is the rated wind speed and V co is the cut-out wind speed measured in ms −1 . The output power of the wind turbine at different heights can be calculated by assessing wind speed at the reference height. Equation (2) is used to calculate wind speed at different heights where V h and V re f are wind speed (ms −1 ) at height H (m) and at reference height H re f (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.

PV System
The PV module is a device that converts solar irradiation into electrical energy. The power output of a solar PV system depends upon several factors, such as the solar irradiance on the PV (G I ), the area of a panel (A), the number of panels (N), the operating temperature of the cell (T c ), the efficiency at STC (η 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]. Table 2 illustrates the specifications of the PV panel used for the present study. Figure 3 shows solar radiation at the IIT Madras, Chennai for the complete year.

Phase Change Material
Phase change materials can store/release huge amounts of heat during phase transition. This property of the PCM makes it suitable for various heating and cooling applications, and also suitable for integration with renewable resources for efficient system operation. Compared to a sensible heat storage system, the PCM-based latent heat storage system has a much higher ability to store or release thermal energy [30,31], which can be seen in the temperature vs. energy profile of the phase change material ( Figure 4). The energy Profile of sensible material with respect to temperature is OAB whereas energy profile of phase change material with respect to temperature is OACD as shown in Figure 4.

PV-PCM System
A PV-PCM is an integrated system in which a phase change material is attached at the back of the PV panel, as shown in Figure 5. The phase change material absorbs the heat of the PV module and thereby regulates the operating temperature of the PV [32]. The lower operating temperature of the solar cells increases the electrical efficiency [33,34] and prevents the degradation of the panel, which improves the overall effective life of the panel. It has been reported that PCM integration can improve the electrical efficiency of the system significantly for hot climates as compared to cold climates [35]. Experiments conducted by Japs et al. [36] at the University of Paderborn show that a PV-PCM-integrated system can generate 3.05% more electricity compared to a conventional panel. The heat storage capacity of the PCM depends upon the melting temperature of the PCM and its latent heat capacity. Calcium chloride hexahydrate with a melting point of around 30 • C and a latent heat capacity of 191 kJ/kg is used as the PCM, and its thermophysical properties are listed in Table 3. The mathematical model presented in the previous work [35] has been used to evaluate the performance of the PV-PCM system.

Biogas Generator
A biogas generator is a device that uses biogas as fuel and converts it into electrical energy. Biogas is a mixture of gases produced by the decomposition of organic waste in an anaerobic environment. The power output from the biogas generator is given by Equation (4) [28].
The specifications of the generator are presented in the Table 4 [37]. Table 4. Specifications of generator [36].

Battery Bank Energy Storage System
The charging of the battery takes place when the power generated by the PV and wind turbine is more than the demand. When the power produced by the PV and wind is less than the demand, the battery bank acts as a secondary power source. The battery bank's capacity is selected based on the power required for a day, the battery efficiency, and the energy demand. The characterization of the battery's charge status and discharge status is determined by the state of charge (SOC). The SOC is defined as the ratio of current capacity to the nominal capacity of the battery. The battery is fully charged when the SOC is 1 and battery is empty when the SOC is 0. The instantaneous SOC of a battery can be calculated by Equation (5) [38].
where SOC(t) is the state of charge of the battery at time t, σ is the battery self-discharge rate, I bat is the battery current at time t (A), η bat is the battery charge efficiency and C bat is the capacity of the battery.
The instantaneous battery current can be calculated by Equation (6).
where P 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].
where E 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.

Converter System
In the present system, the wind turbine, PV/PCM panel and battery bank are connected to the DC bus, whereas biogas generator and the electric load are connected to the AC bus. Therefore, a converter is required to convert AC to DC, or vice versa, as per the requirement to maintain the flow of power between the HRES components. The converter consists of a rectifier and inverter assembly. The power output of the converter is given by the Equations (8) and (9): where P 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.

Load Profile
For the present study, a hostel in IIT Madras, Chennai, India is assessed for its electric load. The electric load profile is the main influencing factor in the design and optimization of integrated hybrid energy systems. So, it is very important to know how load varies during weekdays and weekends in order for the hybrid system to achieve the maximum utilization of resources and minimum system costs. The electric loads considered for the present study are computers, fans, lights, electronic devices and machinery. The electric load profiles of the Hostel during weekdays and during weekends are shown in Figure 6a and Figure 6b respectively.

Constraints
The optimization of the hybrid integrated system has been achieved considering different constraints, which are discussed as follows.

Lower and Upper Limit of Energy Source
In present study, the sizes of the PV-PCM, wind turbine, biogas generator and battery bank were varied to find the optimum levels to meet the electricity demand of the hostel at IIT Madras. The lower and upper limits of the PV-PCM, wind turbine, biogas generator and battery bank are given by the following Equation (10): (10) where N 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.

Battery Bank Operational Constraint
For the long life and effective functioning of the battery bank, it is important that the charging and discharging of the battery is within safe operational limits. The battery bank should not be overcharged or discharged below a limit. The operational constraints levied on the battery bank for effective and safe working are given by Equation (11): where E Battmin and E Battmax are, respectively, the maximum and minimum allowed energy values of the battery bank.

Wind Turbine Operational Constraints
The wind turbine power output depends on the wind speed. Only after the cut-in (threshold) wind speed is power generation possible from the wind turbine. Additionally, for safe operation, there is a cut-off wind speed after which the turbine is not operated. The operational wind speed constraint imposed on the wind turbine for effective power generation is given by Equation (12):

Power Reliability Constraints
The integrated hybrid renewable energy sources must always be able to meet the load demand with zero percentage shortage. The loss of power supply probability (LPSP) is the power exerted by the HRES to meet load demand. The LPSP is given by Equation (13) [39], Loss of power supply (LPS) at any time "t" can be calculated by Equation (14) [40]

Control Strategy and Operation
The operation of the hybrid renewable energy system is a priority-based interaction between different energy sources. The control algorithm mediates between electric load and the power output of the different energy sources. The control strategy operates with the following objectives: (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.
The dispatch strategy of the HRES based on the priority of operation is described in Table 5. Involves running cost and regular maintenance cost due to prime mover emission

Net Present Cost
The net present cost (NPC) is the total present cost of the system (expense minus revenue) incurred over the lifetime of the project. NPC includes capital cost, operation and maintenance cost (O&M), replacement cost, fuel cost and salvage cost. NPC is calculated using Equation (15) [41] NPC = C ann CRF i, R proj (15) where C ann is the annualized cost and CRF is the capital recovery cost.

Cost of Energy
The cost of energy (COE) is the average net present cost of the generated electric energy. COE is calculated as the ratio of annualized cost (C 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), where C ann is the annualized cost and E ser is the useful energy generated by the integrated system.

Capital Recovery Factor
The capital recovery factor (CRF) signifies the return on invested capital over an investment's life span. It is the ratio of a constant annuity to the present value of receiving that annuity over the lifetime of a project. The CRF is calculated by Equation (17), where i is interest rate (%) and an is annuity. The economic data and operation life of different components of the HRES are listed in Table 6.

Results and Discussion
In the present study, four configurations ((i) PV-Wind-Battery system, (ii) PV-PCM-Wind-Battery, (iii) PV-Wind-Biogas-Battery and (iv) PV-PCM-Wind-Biogas-Battery) have been compared. Optimization has been carried out to minimize the cost of energy and the net present cost has also been computed. It has been found that the optimum configuration of a PV-Wind-Battery system is the one with an 819 kW PV, a 321 kW wind turbine, 3957 Ah battery storage and a 316 kW converter. After PCM integration, the optimum configuration is the one with a 781 kW PV-PCM, a 278 kW wind turbine, 3980 Ah battery storage and a 391 kW converter. Similarly, the optimum configuration for the PV-Wind-Biogas-Battery includes a 265 kW PV, a 228 kW wind turbine, a 420 kW biogas generator, 657 Ah battery storage and a 184 kW converter. After PCM integration, the optimum configuration is the one with a 224 kW PV-PCM, a 206 kW wind turbine, a 420 kW biogas generator, 633 Ah battery storage and a 170 kW converter. The energy production and economic analysis are presented in the following subsections.

Energy Analysis
The monthly energy contributions of various energy sources for different configurations of the HRES are presented in Figures 7-10. It can be observed from Figures 7 and 8 (comparison between Conf-1 and Conf-2) that due to the integration of a PCM with the PV panel, the percentage contribution of the photovoltaics increased significantly. The total energy contribution of the photovoltaic increased from 1,217,961 kWh/year to 1,380,474, even when there was a reduction in the installed PV from 819 kW to 781 kW. The penetration factor of PV also increased from 132% to 150%. Similarly, it can be observed from Figures 9 and 10 (comparison between Conf-3 and Conf-4) that due to the integration of PCM with the PV panel, the percentage contribution of the photovoltaics increased significantly. The total energy contribution of the photovoltaic increased from 340,835 kWh/year to 394,079 kWh/year, even when there was a decrease in the installed PV from 265 kW to 224 kW. The penetration factor of PV also increased from 37.1% to 42.8%. A breakdown of the energy analysis of all the configurations of the hybrid renewable energy system is presented in Table 7.

Economic Analysis
The optimization of all the configurations of the HRES was carried out on the basis of the net present cost of the system, which includes the capital cost, operation and maintenance cost, fuel cost, and replacement cost minus the salvage cost of all components over the time period of 25 years. A breakdown of the net present cost of all the configurations of the hybrid renewable energy system is presented in Table 8. The NPCs of Conf-1, Conf-2, Conf-3 and Conf-4 are USD 2.50 million, USD 2.32 million, USD 1.65 million and USD 1.43 million, respectively. It can be observed that due to the efficiency enhancement of the PV panel using a phase change material, there was a reduction in the principal, operation and maintenance costs of the PV panel, thereby resulting in cost savings of USD 0.17 million between Conf-1 and Conf-2 and USD 0.22 between Conf-3 and Conf-4. The cost of energy (CoE) of the HRES is also reduced due to the integration of PCM with the PV panel. The CoE values of Conf-1, Conf-2, Conf-3 and Conf-4 are USD 0.12/kWh, USD 0.105/kWh, USD 0.099/kWh and USD 0.094/kWh, respectively.

Sensitive Analysis
A sensitive analysis of the hybrid renewable energy system has been carried out for configuration 4 to understand how variations in the costs of different components affect the net present cost and the overall cost of energy.

Variation in PV-PCM Panel Cost
The NPC and CoE of the hybrid system have been evaluated via variations in the PV-PCM's cost, equating to a factor of 0.8 to 1.3 of its principal cost. The variations in the NPC and CoE with changes in PV-PCM cost are shown in Figure 11. It can be observed that with changes in the cost of the PV-PCM panel, there are variations in the NPC and CoE of the system. With a 20% decrease in the cost of the PV-PCM system, the NPC and CoE of the overall system will reduce to USD 1.41 million and USD 0.093/kWh, respectively. Similarly, with a 20% increase in PV-PCM cost, the NPC and CoE of the HRES increase to USD 1.46 and USD 0.095/kWh, respectively.

Variation in Wind Turbine Cost
The NPC and CoE of the hybrid system have been evaluated via the variations in the wind turbine cost, which equate to a factor of 0.8 to 1.3 of its principal cost. The variations in the NPC and CoE with changes in wind turbine cost are shown in Figure 12. It can be observed that with a change in the cost of the wind turbine, there are variations in the NPC and CoE of the system. With a 20% decrease in the cost of the wind turbine, the NPC and CoE of the overall system will reduce to USD 1.39 million and USD 0.092/kWh, respectively. Similarly, with a 20% increase in the wind turbine cost, the NPC and CoE of the HRES increase to USD 1.46 and USD 0.096/kWh, respectively.

Variation in Biogas Generator Cost
The NPC and CoE of the hybrid system have been evaluated via the variations in the cost of the biogas generator, which equate to a factor of 0.8 to 1.3 of its principal cost. The variations in the NPC and CoE with changes in the cost of the biogas generator are shown in Figure 13. It can be observed that with changes in the cost of the biogas generator, there are significant variations in the NPC and CoE of the system. With a 20% decrease in the cost of the biogas generator, the NPC and CoE of the overall system will reduce to USD 1.37 million and USD 0.088/kWh, respectively. Similarly, with a 20% increase in the biogas generator cost, the NPC and CoE of the HRES increase to USD 1.48 and USD 0.0975/kWh, respectively.

Variation in Battery Cost
The NPC and CoE of the hybrid system have been evaluated via the variations in the battery cost, which equate to a factor of 0.8 to 1.3 of its principal cost. The variations in the NPC and CoE with changes in the battery cost are shown in Figure 14. It can be observed that with a change in the battery cost, there are variations in the NPC and CoE of the system. With a 20% decrease in the battery cost, the NPC and CoE of the overall system will reduce to USD 1.41 million and USD 0.090/kWh, respectively. Similarly, with a 20% increase in the battery cost, the NPC and CoE of the HRES increase to USD 1.45 million and USD 0.096/kWh, respectively.

Conclusions
A hybrid energy system usually consists of two or more renewable energy sources used together to provide increased system efficiency. For uninterruptible and viable power supply, various cost effective energy sources, such as solar, wind, hydro, and biogas, can be integrated together to meet the electric load demand in a reliable manner. There are various advantages to a hybrid renewable energy system (HRES): (i) better utilization of renewable energy, (ii) better load matching, (iii) better controllability, and (iv) lower operational and maintenance cost.
In the present study, the performance of a hybrid renewable energy system consisting of PV, PCM, a biogas generator, wind and battery has been investigated. It can be observed that due to the ability of the PCM to absorb the heat from the photovoltaic panel, the performance of the PV panel increases, which results in a reduction in the net present cost and the cost of energy of the overall system. For the PV-Wind-Biogas generator-Batterybased off-grid system, the integration of a phase change material with a PV panel results in a saving of USD 0.22 million in terms of net present cost, and reduces the cost of the energy of the system from USD 0.099/kWh to USD 0.094/kWh. Similarly, for another off-grid HRES configuration of PV-Wind-Battery, the integration of a phase change material with the photovoltaic panels results in a saving of USD 0.17 million, and also reduces the cost of energy of the system from USD 0.12/kWh to USD 0.105/kWh.
The present work can be expanded by integrating the PV-PCM with other renewable energy systems for different geographical locations. The PCM-based energy system can also be integrated with a cogeneration energy system for enhanced system efficiency and a lower cost of energy.