Sistema ɗin Tsohon Karamin Hawa da Karamin Rana na Gaba: Wani Bayanin Inganci na Kirkiro wanda Yake Daidai Don Iyakokin Mai Tsarki

1. Magana da Hanyar

1.1 Dangantaka na Tattalin Kashi da Turanci

Tattalin kashi da turanci na PV ko tattalin kashi da hawa na musamman suna da dangantaka. Tattalin kashi da PV yana jin dadin da ya shafi gurbin ranar da kuma harsuna, wanda tattalin kashi da hawa ke amfani da kayan hawa mai yawa, wanda ke samu karfin da ya shafi da aiki. Don haka don in ba da aiki mai tsawo, an bukata sabon bayanai masu kyau don inganta da zama. Amma, batari da take yi aiki da dace-dace suna da kyau a matsayin cikakken lokaci kan a harkokin da suka da damu, wanda ke biya da lokacin da suke da damu cikin ayyukan da suka da damu, wanda ke biya da lokacin da suke da damu cikin ayyukan da suka da damu. Mafi girma, abin da suka da damu wa batari yana iya haɗa da kafin ko kuma ƙarin da PV modules ko tattalin hawa. Saboda haka, inganta tsawon batari da kuma ƙasashe mafi girma ga system yana zama muhimmiyar dangantaka.

1.2 Muhimmin Faide na Tattalin Kashi da PV da Hawa

Tattalin kashi da PV da hawa ta fiye da dangantaka na tattalin kashi mai tsawo ta hanyar tsakiyar PV da hawa, bili biyu na tattalin kashi mai tsawo. PV da hawa suna da mu'amala mai tsawo a lokacin (rana/biyar, harmattan) - rana na nisa na hawa na maye, hawa na biyar na maye; PV na nisa na hawa na maye, hawa na biyar na maye. Wannan mu'amala ta fiye da:

• Mukena tsawon lokacin da batari ke gano da damu, kuma ci nasara da batari a lokacin da suke da damu, wanda ke ƙara tsawon batari.
• Dakile da adadin batari. Saboda ƙasar da PV da hawa ba suka da damu daga baya, system yana iya ba damu a lokacin da suke da damu, wanda ke ƙara da batari mai tsawo.
• Karatu da takaitaccen labaran da suka tabbatar da cewa tattalin kashi da PV da hawa suna da muhimmiyar faide a hukumomin tsawon damu da kuma ƙasashe mafi girma.

1.3 Dangantaka na Tsohon Hanyoyi da Kayan Amsa

Aiki na tsohon hanyoyi yana da dangantaka. Software na tsohon hanyoyi daga tare da masu aiki suna da damu, kuma aikinsu suna da damu, wanda ke ƙara da aikinsu. Amma, yawan hanyoyi masu aiki suna da damu - domin suke amfani da tsohon hanyoyi mai yawa, ko kuma suke amfani da hanyoyi mai yawa, wanda ke ƙara da aikinsu.

Amsar da na iya bayarwa shine hanyoyi mai yawa da kuma aikinsu.

II. Tsohon System da Modelloin Masu Aiki

2.1 Tsohon System

Tattalin kashi da PV da hawa da na iya bayarwa shine tattalin kashi mai tsawo, ba da tattalin kashi mai tsawo. Tsohon komponenti sun hada da:

• Tattalin Kashi: Tattalin hawa, PV array.
• Ingantaccen Damu da Ingantaccen Aiki: Batari, charge controller (don inganta da damu da kuma aiki).
• Tsaro da Zama: Diversion load (don tsaro batari, don tsaro inverter), inverter (don zama DC zuwa AC).
• Tattalin Damu: Load.

2.2 Modelloin Mai Yawa na Tattalin Kashi

Don in ba da aiki mai tsawo, an samun modelloin mai yawa na tattalin kashi.

• Modelloin PV Array:
1. Transposition na Harsuna: An amfani da modelloin mai yawa na harsuna don transposition horizontal PV data zuwa harsuna na PV modules, kuma amfani da direct beam radiation, sky diffuse radiation, da ground-reflected radiation.
2. Simulation na Characteristic na Module: An amfani da modelloin mai yawa na physics don characterize nonlinear output characteristics na PV modules, kuma amfani da harsuna da temperature na environment.
• Modelloin Tattalin Hawa:
1. Correction na Harsuna: An amfani da exponential law don correction reference height wind speed zuwa actual hub height wind speed.
2. Fitting na Power Curve: An amfani da segmented function (different binomial equations for different wind speed intervals) don high-precision fitting na power curve na turbine, kuma amfani da wind speed data.

2.3 Modelloin Dynamic na Batari

Batari ita ce tsohon ingantaccen damu, da states mai yawa. Modelloin sun hada da:

• Calculation na State of Charge (SOC): An amfani da relationship na tattalin kashi da damu don calculate remaining capacity, kuma amfani da self-discharge rate, charging efficiency, da inverter efficiency.
• Management na Charge-Discharge: An define reasonable SOC operating range, kuma an amfani da modelloin na float charge voltage don determine charging conditions.

III. Hanyoyi da Kayan Aikin System

3.1 Indicators na Tsawon Damu

Hanyoyi na tsohon system yana da muhimmiyar indicators:

• Loss of Power Supply Probability (LPSP): Ratio na system outage time zuwa total evaluation time, wanda ke ƙara tsawon damu.
• Loss of Load Probability (LLP): Ratio na load power demand not met by the system zuwa total demand. Wannan shine muhimmiyar indicator.

3.2 Step-by-Step Optimization Design Process

Amsar da na iya bayarwa shine hanyoyi mai yawa, don in ba da aiki mai tsawo.

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.