Systema Optimum Hybrida Ventus-Solaris: Solutio Designi Comprehensiva pro Applicationibus Extra Reticulum

1. Introductio et Background

1.1 Difficultates Systematum Generationis Unicae Fontis Energiarum

Systemata traditionalia generationis photovoltaicae (PV) vel eolicorum generationis energeticae habent inhaerentes defectus. Generatio PV afficitur a cyclo diei et conditionibus meteorologicis, dum generatio eolica pendet ab instabilibus ventis, quae ad magnas fluctuationes productionis energeticae ducunt. Ut continuae supplymentum electricitatis assecurare possimus, necessaria sunt magnae capacitates batariorum pro storage et balance energiarum. Tamen, bateriae sub frequentibus cyclus charge-discharge longo tempore in statu subcharge remanere solent sub duris conditionibus operativis, quod ad vitam practicam multo breviorem quam valor theoreticus reducit. Quod est gravius, alta costus batariorum significat totalem costum lifecycle posse adpropinquare vel etiam superare costum modulorum PV vel turbine eolicarum ipsarum. Itaque, extensio vitae batariorum et reductio costum systematis facta sunt nucleum difficultatum in optimisatione systematum standalone.

1.2 Praestantia Significa Hiberno-Solaris Generationis Energeticae

Technologia hiberno-solaris generationis efficaciter superat intermittenciam unicae fontis per organicam combinationem PV et eolicarum, duarum fontium renovabilium. Ventus et solaris exhibent naturalem complementaritatem in tempore (diurno/nocturno, saeculari): fortis lux solaris diurna saepe concidit cum potentius ventis nocturnis; bonae irradiationes solares aestivales possunt coniungi cum abundantibus ventis hiemalibus. Haec complementaritas permittit:

• Magnam extensionem temporis effective charging batariorum, reductio temporis in statu subcharge, quod substantialem prolongationem vitae servicii batariorum efficit.
• Reductionem capacitarum batariorum requirit. Cum probabilitas utrumque ventus et solaris simul non disponibilis sit parva, systema saepe potest directe load powerare, permitens usum minoris capacitatis batariorum.
• Studia domestica et internationalia confirmant systemata hiberno-solaria superare systemata unicae fontis in fide reliable supply et cost-effectiveness lifecycle.

1.3 Defectus Methodorum Design Existentialium et Propositum Solutionis

Design systematis currentis difficultates facit. Software professional simulationis ab exterioribus carum est, et nuclei modelorum saepe secreti sunt, impedientes adoptionem widespread. Simul, plures methodi design simplificati insufficiunt—aut nimis dependunt a mediis meteorologicis ignorantes details, aut utuntur linearibus modellis simplificatis ad accuratiam limitandam et applicabilitatem pauperem.

Hoc solutionem intendit proponere set accurate et practica computer-aided design methodologies ad resolvendum praedicta problemata.

II. Compositio Systematis et Nuclei Technici Modelorum

2.1 Architectura Systematis

Hiberno-solaris generationis systema in hac solutione designatum est systema totaliter standalone off-grid, sine backup power sources sicut diesel generators. Nuclei componentes includunt:

• Unitas Generationis Energeticae: Turbine generator eolicae, array PV.
• Unitas Storage et Management Energiae: Bateria bank, charge controller (ad management charging et discharging).
• Unitas Protectionis et Conversionis: Diversion load (prevents battery overcharge, protects inverter), inverter (converts DC to AC to meet most load requirements).
• Unitas Consumptionis Energeticae: Load.

2.2 Accuratissimi Modeli Calculationis Generationis Energeticae

Ad design optimizatum, accurate hourly power generation calculation models constitutimus.

• Model PV Array:
1. Transposition Solaris Radiations: Utilizat an advanced anisotropic sky diffuse model to accurately transpose horizontal solar radiation data measured by weather stations to the irradiance incident on the tilted surface of the PV modules, comprehensively considering direct beam radiation, sky diffuse radiation, and ground-reflected radiation.
2. Simulatio Characteristicarum Modulorum: Employs a precise physical model to characterize the nonlinear output characteristics of PV modules, fully accounting for the effects of irradiance and ambient temperature on module output voltage and current, ensuring the accuracy of power generation calculations.
• Model Turbinarum Eolicarum:
1. Correctio Velocitatis Venti: Corrects the reference height wind speed from meteorological data to the actual hub height wind speed based on the exponential law governing wind speed variation with height.
2. Fitting Curvae Potentiae: Uses a segmented function (different binomial equations for different wind speed intervals) to achieve high-precision fitting of the turbine's actual power output curve, enabling accurate hourly energy calculation based on wind speed data.

2.3 Model Dynamic Characteristicarum Batariorum

Bateria est nucleus storage energiae, cum statibus dynamicis mutabilibus. Modelus principaliter considerat:

• Calculatio State of Charge (SOC): Dynamically simulates the battery's charge and discharge processes based on the relationship between power generation and load consumption at each time step, accurately calculating the remaining capacity, while considering practical factors like self-discharge rate, charging efficiency, and inverter efficiency.
• Management Charge-Discharge: To extend battery life, a reasonable SOC operating range is defined (e.g., limiting the maximum depth of discharge to 50%), and a model correlating float charge voltage with SOC and ambient temperature is established to accurately determine charging conditions.

III. Methodologia Optimisationis et Sizing Systematis

3.1 Indicators Fide Reliable Supply

Design prioritizes meeting the user's specified power supply reliability requirements. Key indicators include:

• Loss of Power Supply Probability (LPSP): The ratio of system outage time to the total evaluation time, intuitively reflecting supply continuity.
• Loss of Load Probability (LLP): The ratio of the load power demand not met by the system to the total demand. This is the most critical core indicator for system optimization design.

3.2 Step-by-Step Optimization Design Process

This solution adopts a systematic optimization process, aiming to minimize the initial investment cost of equipment to find the optimal configuration.

1. Step 1: Optimize PV and Battery Configuration for a Fixed Wind Turbine Capacity
• Core Task: Under the condition that the wind turbine model and quantity are fixed, find the combination of PV module and battery capacities that meets the predetermined reliability indicator (LPSP) and results in the lowest total equipment cost.
• Implementation Method: Through simulation calculations, plot the "balance curve" representing all PV and battery configurations that meet the reliability requirement. Then, using the cost tangent method or computer program screening based on equipment unit prices, determine the unique optimal combination with the lowest cost.
2. Step 2: Global Optimization by Varying Wind Turbine Capacity
• Core Task: Change the wind turbine capacity or number, repeat the optimization process of Step 1, and obtain a series of optimal configurations and their corresponding costs for different wind turbine capacities.
• Final Decision: Compare the total costs of all candidate solutions and select the wind-PV-battery combination with the globally lowest cost as the final optimized system configuration.

3.3 Simulation and Output of System Performance

After determining the optimal configuration, the system's annual operation can be simulated hour-by-hour, generating detailed reports including:

• Time Dimension: Hourly battery state of charge, system energy balance.
• Statistical Dimension: Daily/monthly/annual unmet load energy, reliability indicators (LPSP, LLP), wind/solar power generation share, energy surplus and deficit situations, etc.

IV. Conclusion

The optimized design method for hybrid wind-solar power generation systems proposed in this solution, based on comprehensive mathematical models and precise local meteorological data, can uniquely determine the system configuration with the minimum initial equipment investment cost while satisfying specific user electricity demands and power supply reliability requirements. This method effectively addresses the shortcomings of single-source power generation systems, overcomes the limitations of existing design approaches, and provides a powerful tool for the scientific, efficient, and economical design of hybrid wind-solar power generation systems, holding significant value for engineering applications.