Sistema nga Gi-optimize sa Híbrido nga Hangin-Solar Power: Komprehensibong Solusyon sa Disenyo para sa mga Aplikasyon nga Wala sa Grid

1. Introduksyon ug Background​

​1.1 mga Hamubo sa Single-Source Power Generation Systems​

Ang tradisyonal nga standalone photovoltaic (PV) o wind power generation systems adunay natural nga mga kahamubo. Ang PV power generation naaapektuhan sa diurnal cycles ug kondisyon sa panahon, samtang ang wind power generation gidepende sa unstable nga wind resources, resultando sa significant nga pagbag-o sa power output. Aron masigurado ang continuous nga power supply, kinahanglan og large-capacity battery banks para sa energy storage ug balance. Apan, ang mga baterya nga nagdula-dula sa frequent charge-discharge cycles mao ang prone sa pagpadayon sa state of undercharge sukad sa dili maayo nga operating conditions, resultando sa practical service life nga dili mobaya sa theoretical value. Mas critical pa, ang taas nga cost sa baterya mao ang makapadako sa total lifecycle cost aron maputli o mobaya pa sa cost sa PV modules o wind turbines mismo. Kini nga rason, ang pagpadayon sa battery life ug pagbawas sa system costs naging ang core challenges sa pag-optimize sa standalone power systems.

​1.2 Significant Advantages sa Hybrid Wind-Solar Power Generation​

Ang hybrid wind-solar power generation technology mahimong makaovercome sa intermittency sa single energy sources pinaagi sa organic combination sa PV ug wind power, duha ka renewable energy sources. Ang wind ug solar energy adunay natural nga complementarity sa oras (day/night, seasons): strong nga sunlight sa daytime kasinatian sa potentially stronger winds sa gabii; maayo nga solar irradiation sa summer kasinatian sa abundant nga wind resources sa winter. Kini nga complementarity makapahimo og:

• Significant extension sa effective charging time sa batteries, pagbawas sa oras nga sila naglakip sa undercharged state, resultando sa substantial prolongation sa battery service life.
• Pagbawas sa required battery capacity. Tungod kay ang probability nga ang parehas nga wind ug solar wala sa una sama sama gamay ra, ang system mahimong magpower sa load direkta, paghatag og oportunidad sa paggamit og smaller capacity battery bank.
• Domestic ug international studies confirm nga ang hybrid wind-solar systems superior sa single-source power generation systems sa power supply reliability ug lifecycle cost-effectiveness.

​1.3 Mga Kahamubo sa Existing Design Methods ug ang Proposed Solution​

Ang kasamtangan nga system design adunay mga hamubo. Ang professional simulation software gikan sa abroad expensive, ug ang ilang core models confidential, hinumdumi sa widespread adoption. Samtang ang majority sa simplified design methods insufficient—either too much dependent sa meteorological averages ignoring details, o linear simplified models leading to limited accuracy ug poor applicability.

Kini nga solusyon naglakip sa proposal sa set sa accurate ug practical computer-aided design methodologies aron masolve ang uban pang issues.

​II. System Composition ug Core Technical Models​

​2.1 System Architecture​

Ang hybrid wind-solar power generation system nga gidesign niining solusyon usa ka completely standalone off-grid system, walay backup power sources sama sa diesel generators. Ang core components include:

• ​Power Generation Unit:​​ Wind turbine generators, PV array.
• ​Energy Storage ug Management Unit:​​ Battery bank, charge controller (para sa management sa charging ug discharging).
• ​Protection ug Conversion Unit:​​ Diversion load (prevents battery overcharge, protects inverter), inverter (converts DC to AC aron mapasabot sa most load requirements).
• ​Power Consumption Unit:​​ Load.

​2.2 Accurate Power Generation Calculation Models​

Aron makapahimong sa optimized design, natukma kami sa accurate hourly power generation calculation models.

• ​PV Array Model:​​
1. ​Solar Radiation Transposition:​​ Utilizes an advanced anisotropic sky diffuse model aron 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, ug ground-reflected radiation.
2. ​Module Characteristic Simulation:​​ Employs a precise physical model aron characterize the nonlinear output characteristics of PV modules, fully accounting for the effects of irradiance ug ambient temperature on module output voltage ug current, ensuring the accuracy of power generation calculations.
• ​Wind Turbine Model:​​
1. ​Wind Speed Correction:​​ 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. ​Power Curve Fitting:​​ Uses a segmented function (different binomial equations for different wind speed intervals) aron achieve high-precision fitting of the turbine's actual power output curve, enabling accurate hourly energy calculation based on wind speed data.

​2.3 Battery Dynamic Characteristic Model​

Ang battery ang core energy storage component, adunay dynamically changing states. Ang model primarily focuses on:

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

​III. System Optimization ug Sizing Methodology​

​3.1 Power Supply Reliability Indicators​

Ang 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 ug Battery Configuration for a Fixed Wind Turbine Capacity​
• ​Core Task:​​ Under the condition that the wind turbine model ug quantity are fixed, find the combination of PV module ug battery capacities that meets the predetermined reliability indicator (LPSP) ug results in the lowest total equipment cost.
• ​Implementation Method:​​ Through simulation calculations, plot the "balance curve" representing all PV ug 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, ug obtain a series of optimal configurations ug their corresponding costs for different wind turbine capacities.
• ​Final Decision:​​ Compare the total costs of all candidate solutions ug select the wind-PV-battery combination with the globally lowest cost as the final optimized system configuration.

​3.3 System Performance Simulation ug Output​

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