Forecasting the Electricity Demand with Increasing Population by Using System Dynamic Approach - A Case Study of Karnal City (India)

Meenakshi¹, Mothi Kumar K E^2, and Nisha Kumari¹

¹Center of Excellence for Energy and Environmental Studies (CEEES), Deenbandhu Chhotu Ram University of Science and Technology (DCRUST), Sonipat, 131 039

²Haryana Space Applications Centre (HARSAC), Citizen Resources Information Department (CRID) Haryana, CCS HAU Campus, Hisar, 125004

Cite this paper:
Meenakshi, Mothi Kumar K E and Nisha Kumari. Forecasting the Electricity Demand with Increasing Population by Using System Dynamic Approach - A Case Study of Karnal City (India). Applied Ecology and Environmental Sciences. 2021; 9(7):707-714. doi: 10.12691/aees-9-7-10

Abstract

Electricity has become an important source of energy in human society. The enormous use of electricity necessitates a mechanism to predict future demand. Modelling and simulation of electricity markets have increasingly involved the use of a System Dynamics (SD) approach. The basis for population growth and policy option scenario is the variation in birth, death and migration rates. Accordingly, the resulting dynamic hypothesis and the stock-flow structures are represented and simulated using software such as Stella. The present study has been undertaken to assess the future electricity demand and the population dynamics in Karnal city (Haryana), India, covering an area of 90.4 km² with a population of 0.28 million. The System Dynamic Approach (Stella version 9.1) was successfully used to predict the future energy demands versus population growth dynamics in five modified scenarios (MS-I, MS-II, MS-III, MS-IV and MS-V) apart from the baseline scenario. The MS – IV was found to be the best scenario, as this scenario projects the stabilized population in the Karnal city, giving an edge over the other four modified scenarios policies. In this case, the population would rise to 0.46 million (2041) from 0.28 million (2011), while the energy demand will rise to 559 Gwh (2041) from 346 Gwh showing an increase of 213 Gwh (38%) over 30 years. The MS – I was found to be very critical, as the maximum energy demand was found to be very high (668 Gwh) with a total raise of 322 Gwh (48%).

Keywords:
population growth electricity demand system dynamic approach stock-flow modelling

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