Minimizing non-technical losses with point-to-point measurement of voltage drop between “SMART” meters

Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

“…Reactive management presents a challenge for network operators and end customers. The former seek to decrease technical losses presented in the wires of the primary and/or secondary circuits and transformers' cores and theirs winding [7,15].Additionally, they intend to eradicate the non-technical losses caused mainly due to illegal connections on the system [6,16]. End customers seek not to be involved in economic penalties due to losses caused by the usage of electric machines at the industrial level, which create inconveniences with the power factor.…”

“…The author of [5] discussed the amount of money invested in these systems and the type of losses presented; besides, they mentioned that 2/3 parts of the investment in power systems is associated with the distribution, for which distribution is known as "invisible giant" of the power system. In terms of power losses, these can be categorized into technical and nontechnical losses [6]. Technical losses occur through the energy dissipation when running power system components such as transmission and distribution lines and primary and secondary conductors; likewise, these are found in transformers' winding and cores [7,8].…”

Computational Intelligent Approaches for Non-Technical Losses Management of Electricity

“…The former corresponds to the percentage of electrical energy transformed into other types of energy during the transmission process. The second group refers to the amount of electrical energy delivered to end-users but is not billed properly and is therefore not economically represented [2,3]. In the NTL group, we find products of errors and breakdowns in measurement equipment, energy not invoiced due to errors in meter reading or billing processes, and finally, those associated with fraudulent behavior of customers, who evade payment corresponding to the consumption of electrical energy [4,5].…”

Using AIS EM Data to Find the Parameters of a Distribu-tion Grid

“…Оперативные данные об указанных параметрах позволят расширить функции существующих АИИС КУЭ в части контроля и диагностики технического состояния и уровня надежности РЭС [13,14]. Кроме того, важным приложением оперативной оценки параметров РЭС является возможность их использования при реализации существующих и разработке новых методов выявления несанкционированных отборов электроэнергии (НОЭ) на контролируемом участке сети [15][16][17][18][19][20][21][22][23][24][25][26][27], а также при идентификации и мониторинге технических и коммерческих потерь электроэнергии в РЭС [15]. Поэтому вопрос оперативной идентификации параметров участков распределительной сети по данным АИИС КУЭ является актуальным и требует своего развития.…”