Genelleştirilmiş regresyon modelleri kullanılarak enerji talebi ve tüketimi için bir modelleme yaklaşımı

Enerji yönetimi, mevcut enerji kaynaklarını korumak ve evlerin temel enerji ihtiyaçlarını karşılamak için önemli bir süreçtir. Pek çok çalışma, yük talebini yönetmek ve enerji maliyetlerini en aza indirmek için hanehalkı enerji tüketim modellerini optimize etmeyi amaçlamaktadır. Çatışmalardan etkilenen ülkelerde bu tür optimizasyonlarını benimsenmesi, sınırlı enerji kaynakları nedeniyle daha faydalıdır. Bu çalışma, Suriye'nin kuzeyindeki haneler için en uygun enerji tüketim modelini belirlemektedir. Amaç, enerji fiyatlarını, ortalama aylık hane gelirini, ana elektrik kaynağını, batarya depolama kapasitesini ve alan ısıtma, su ısıtma ve pişirme için kullanılan enerjiyi dikkate alarak en uygun maliyetli enerji kaynaklarını belirlemektir. Yüz otuz altı (136) standartlaştırılmış mesken hane anketi toplandı ve bir test vakası olarak kullanıldı. Verilerin istatistiksel analizi, R-Studio yazılımı kullanılarak yapıldı; Poisson regresyon ve negatif binom regresyon kullanıldı. Bulgular, kullanılan Negatif Binom (NB) modelinin açıklama gücünün yüksek olduğunu ortaya koymuştur. Ayrıca alan ısıtma ve su ısıtma için kullanılan enerji kaynakları da aylık harcamalara doğrudan etki etmektedir. Üretilen model, en uygun maliyetli enerji kaynaklarının alan ısıtma için kömür ve su ısıtma için doğal gaz ve gazyağı olduğunu göstermiştir.

Anahtar Kelimeler:

Enerji Verimliliği, Enerji Yönetimi, Enerjiyi Optimizasyonu, Poisson regresyonu, Negatif binom regresyonu.

MODELLING APPROACH FOR ENERGY DEMAND AND CONSUMPTION USING GENERALIZED LINEAR MODELS

Energy management is an important process for maintaining available energy resources and meeting basic household energy needs. Many studies seek to optimize the household energy consumption patterns to manage the load demand and minimize energy costs. Adopting such optimizations in conflict-affected countries is more beneficial due to limited energy sources. This study identifies the optimal energy consumption model for households in northern Syria. The objective is to identify the most cost-efficient energy sources while considering the prices, average monthly household income, the main source of electricity, battery storage capacity, and energy demands for space heating, water heating and cooking. One hundred and thirty-six (136) standardized surveys of residential households are collected and used as a test case. Statistical analysis of the data was carried out using the R-Studio software, where Poisson regression and negative binomial regression were employed. Findings revealed that the Negative Binomial (NB) model used has high explanatory power. In addition, the energy sources used for space heating and water heating have a direct impact on monthly expenditures. The produced model showed that the most cost-effective energy sources are coal for space heating and natural gas and kerosene for water heating.

Keywords:

Energy Efficient, Energy Management, Optimizing Energy, Poisson Regression, Negative Binomial Regression,

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