Techno-Economic Analysis and Optimization of Renewable Energy Conversion Technologies with Battery and Hydrogen Energy Storage for Patani Island

conditions (Tref= 25°C); Kt(?) is the PV panel temperature coefficient, nd Tamb (K) is the ambient temperature KT= (0.4 ?0.6)% Total numbers of module that make up PV panel can be estimated as Inverter DC Battery O2 H2 H2O Controller Electrical load Wind Turbines Syngass Generator AC Wind AC Solar PV Sun Electrolyzer H2 Tank AC NPV= NPVs x NPVp (2) Where NPVs and NPVp are Number of PV in series and Number of PV in parallel respectively The annual energy output of solar PV panel is determined as (Nyeche&Diemuodeke 2020): EPV= ? PPV(t) 8760 t=1 (3) 2.1.2 Wind Power The amount of air entering and exiting a turbine is unchanged due to the mass conservation of the air stream. Wind energy is converted into mechanical power through an energy converter, wind turbine. Then, the mechanical power is converted into electrical power through a generator. It is vital to know the mean wind velocity, from meteorological, its distribution and wind power distribution for the location under study. The maximum power output Pwinof the turbine is given by Pwin= 8?vA 27 (4) Where A is the affected area of the disc, v is the wind velocity and ? is the air density. The rated power of the wind turbine is obtained from Pwin= 8?vCwp 27 (5) Where Cwp is the power coefficient provided by a manufacture. Furthermore, the output power of the wind turbine varies with the hub height H, the wind velocity is calculated. v= vref( H Href)? (6) Where vref is the reference velocity measured at the reference hub height Href is the reference hub height and ? is the power law exponent. It ranges from 0.10 to 0.25. A power law exponent value of 0.15 is used in the present work. 2.1.3 Biomass Energy potential The yearly biomass energy obtainable from agricultural and forestry leftovers Ukoba et al. (2024) ETh= ?Fj n i xLHV: j= (crop, forest) (7) where ETh is the theoretical energy potential, LHV is the low heating value or mean energy content (Ec) [KJ/kg] and Fj is the residue potential or obtainable residue [ktonnes] Fcrop= ?P n i xRPR (8) Where P is crop production [ktonnes], and RPR is the mean residue-to-product ratio The mass forest product volume (m3) is expressed as above for the forest residue. mF= ?x V (9) where mF is the mass of the forest product, ? is the density of the forest product, and V is the volume of the forest product. The forest residue can be obtained Ff= mF x RPR (10) where Ff is the forest residue and RPR is the residue-to-product ratio, which can be assumed to be 0.72 (Ukoba et al., 2023b). Consequently, an availability factor (AF) is deemed to represent the quantity of residue that may be used for energy production annually. The AF range is 01–1 and varies according on location and crop residue, as shown by Ukoba et al. (2023b) and Souza et al. (2021). The technological potential has been calculated. Et = ?ETh n i xAF= (crop, forest) (11) Where Et is the technical potential and AF is an availability factor that ranges from 0 to 1. Availability factors (AF) of 0.4, 0.5–0.75, and 0.8 were postulated for rice residue, wood residue, and oil-palm residues, respectively (Ukoba et al., 2023b). According to Souza et al. (2021) and Portugal-Pereira et al. (2015), a factor of 0.30 was applied to the other crops, since all agro-crops exhibit a comparable availability factor (AF) range, as reported by Ukoba et al. (2023b) and Deng et al. (2015). Furthermore, all forest residues in Nigeria were allocated an AF of 0.6, consistent with Ukoba et al. (2023b). 2.1.4 Battery Energy Storage system In Renewable energy systems, the incorporation of batteries increases system reliability (Evgueniy. 2024). The batteries serve as an energy storage medium, store surplus renewable energy, and supply energy during capacity shortages. Then energy stored in the battery bank at a specified time can be expressed according to Vendotiet al. (2020), EBatt(t) = EBatt(t?1) + EEE(t) × ?CC × ?CHG (12) where, EEE(t) is the extra energy available from all the systems, ?CCas the charging controller efficiency, and ?CHG as the battery charging efficiency The quantity/state of charging the battery are expressed by the given SOCmin? SOC (t) ?SOCmax (13) Where, SOCmin is the value of the minimum SOC; and SOCmaxis the maximum value of SOC, which is assumed to be1. The minimum value of SOC is obtained using the following SOCmin= 1 – DOD, where DOD is the depth of discharge 2.1.5 Hydrogen Energy Storage system Electrolyser/Hydrogen Tank: Electrolyser works under the process of electrolysis; current flows from one electrode to another electrode within water and thus decomposes into hydrogen and oxygen. In most of the surveys, output of the electrolyzer is exactly coupled with the hydrogen storage tank (Vendotiet al., 2020): The power transferred from electrolyser to hydrogen storage tank has been estimated by Pelec?tank = Pelec?tank × ?elec (14) where, ?elecis the electrolyser efficiency. The output energy stored by hydrogen tank is expressed by EH2,tank (t) = EH2,tank (t ?1) + [Pelec,tank (t) ?(Ptank?Bg(t)/?storage) × ?t] (15) where, Ptank?Bg is the output power of a Biomass generator, ? is the efficiency of hydrogen storage, as approximately 95% for all operating conditions (Vendoti et al., 2020). The mass of hydrogen storage is calculated using Mtank (t) = Etank (t)/HHVH2 (16) where, HHVH2 is hydrogen storage higher-heating value considered as 38.9 kWh/kg (Vendotiet al., 2020). Hydrogen storage tank contains several limits of lower and upper portions. When it exceeds the rated capacity, the total mass of the hydrogen tank is not attainable due to some problems, such as a reduction of hydrogen pressure. The limits of the lower and upper portions of the hydrogen storage tank are expressed by Etank?min ?Etank (t) ?Etank?max (17) Etank (t= 0) ?Etank (8760) (18) Inverter power The inverter converts the DC power from renewable energy source and battery storage to AC power to meet the load demand The input power flowing to the inverter is given by (Jahangir, 2023) Pinv(t) = PML(t) ?inv (19) Where Pinv Inverter input power, PML(t) is the peak power demand by the load at time t, and, ?inv is the inverter efficiency Controller Power The rated current of voltage controller, IVR (A), is determined using IVR= NPVp× ISC× SF (20) where ISC (A) is short circuit current of PV modules; SF (-) is safety factor. 2.2 Energy demand assessment The chosen site for the planned system is Patani Island in Delta State, Nigeria. An hourly energy demand analysis of a specific facility is essential for calculating the ideal size of a hybrid system, Malik et al., (2022). The average hourly electric load specification of an appliance per household in a day,Ekj(Wh/household/day) is known using Diemuodeke et al., (2017) Ekj= ? Pij k NH i NH ; j= 1, 2,3,4, ... , 24 (21) Ej= ?Ekj; j= 1, 2, ... , 24 A k (22) where A is the entire number of appliances. The average daily energy requirement, EDER (Wh/household/day) is given as Diemuodeke et al., (2017) EDER= ? Ej 24 j=1 (23) Equations 21 – 23 are applicable to other groups’ i.e. primary health centres and public schools and Product waste management site. The sample community has average daily energy demand of 121MWh/day (43623 MWh/year) 2.3 Optimisation model The optimisation of hybrid PV-WT-BM with BT and HD system is modelled by minimising the difference between energy generated and energy demanded to accurately size the hybrid plant configuration (Nyeche & Diemuodeke 2020) (Emad et al. 2021) (Malik et al. 2022). Energy generated by the RE system is gives as: REE= PVE+ WTE+ BME (26) wherePVE (kWh) is the energy generated from PV module, WTE (kWh) is the energy generated from wind turbine andBME (kWh) is the energy generated from Biomass system Excess energy generated by the RE system is given as: Eexcess= Max[(REE?ED), 0] ifREE> ED (27) whereED (kWh) is energy demanded (load facility) and is given as ED= REE± BT&HDE (28) whereBT&HDE (kWh) is energy release or stored in BT&HD If ED> REE ED= REE+ BT&HDE