GESS-based technical loss estimation for sustainable power networks - Masdzarif, Nur Diana Izzani; Anwar Ibrahim, Khairul; Kim Gan, Chin; Hown Tee, Wei (Indonesian Journal of Electrical Engineering and Computer Science, 2025)
In the pursuit of global environmental sustainability, minimizing technical losses (TL) in power distribution networks has become a key priority for utility providers. Despite numerous advancements, precise loss estimation remains a challenge due to dynamic network conditions, complex configurations, and varying parameters such as load patterns and system topology. This issue is critical, as reducing TL not only enhances distribution efficiency but also contributes to lowering greenhouse gas (GHG) emissions. This study aims to develop and demonstrate a robust method for estimating TL aligned with the global environmental sensing and sustainability (GESS) principles. The proposed approach integrates an advanced loss estimation sequence comprising peak power loss (PPL), load loss factor, and an energy flow model. It is applied to real case studies, enabling assessment of both feeder and transformer losses. Results highlight the impact of key parameters including transformer capacity factor, cable length, load factor (LF), and loss factor on overall losses. Furthermore, the method facilitates quantification of environmental and economic impacts, revealing that both carbon footprint and cost rates are highly sensitive to total energy losses. This work underscores the significance of accurate TL estimation in promoting environmentally and economically sustainable power distribution systems.