The influence of meteorological parameters under tropical condition on electricity demand characteristic: Indonesia case study

Abstract

As meteorological conditions can be unique in different countries and may have influence on electricity demand, providing demand model to analyze characteristic of demand is useful as obtained information can be used to manage related power systems better. This paper proposes regression based demand model to identify typical characteristic of demand in Indonesia more detail. Three different demand areas (Racing Area, Poltek-Area, and Paropo Area) in Makassar, Indonesia including their total demand (Total-Area) are analyzed by creating demand model. The demands are correlated with meteorological parameters (temperature functions, relative humidity, and wind speed) and holidays. Individual characteristics are firstly observed to obtain main drivers and their typical effect on each demand area. Furthermore, general characteristics are analyzed to find common characteristic of demand such as what variables influence electricity demand generally. Several options for model are calculated and assessed by statistical tests to get best model. Results indicate more information concerning characteristic of demands can be revealed by models which are well validated. Each demand area has individual characteristic as demand drivers and their effect are relatively different between areas. Other results concerning general characteristic confirm temperature functions, relative humidiy, and holidays are important driver for demand. The variables are quite good to explain electricity demand generally as adjusted coefficient of determination of model (R 2 , ) is 76.42%.An electric power system is expected can effectively service load demand in all time during its operation. To achieve such expected condition, knowledge about characteristics of connected demand in the system is an important thing, as it can be used by power utilities to manage their power systems better. By performing electricity demand analysis particularly characteristic analysis, typical information such as key drivers for demand and how far their effect under a certain condition are possibly known. One of the method that can be used for the task above is regression approach. However, providing a good demand model as analysis tool is not an easy task as load 978·1·4799-6432-1114/$31.00 mOl41EEE 383

Pemodelan Regresi untuk Investigasi Penggerak Konsumsi Listrik Rumah Tangga di Kota Makassar

“…Reduksi konsumsi ini dapat maksimal salah satunya jika ditunjang dengan pengetahuan terkait penggerak konsumsi listrik sebagai dasar dalam melakukan berbagai aksi penghematan bagi pelanggan terhubung. Untuk itu, studi penggerak beban listrik penting dilakukan untuk konsumsi yang berkelanjutan, dan telah menjadi salah satu topik yang mendapat banyak perhatian peneliti dari berbagai negara [3]- [9].…”

Wavelet Analysis of Daily Energy Demand and Weather Variables

“…Indeed, several works have already shown the correlation between the electricity demand and weather variables [1][2][3][4][5]. Valor et al ( ) attributed the seasonal variation of electricity demand to weather variables and the increasing trend to socioeconomic factors [1].…”

“…Ali et al ( ), in their study entitled the relationship between extreme temperature and electricity demand in Pakistan, showed that the electricity demand is more for the summer season, and this demand will be higher (6785.6 GWh) in July 2020 due to rise in air temperature [4]. Akil et al ( ) showed a correlation between the electricity demand and weather variables in Indonesia [5]. Due to the fact that the weather variables may differ from one location to another, it is worth investigating the impacts of these variables on the electricity demand in a specific climate zone.…”

Meteorological Parameters and Daytime Maximum Electricity Demand in Makassar, Indonesia

“…As an extended version of [6], this present study has focus to investigate demand characteristics mainly during maximum demand period for Indonesia context. Meteorological parameters and holidays are considered to explain pattern of demand in the observed period.…”