GRD Journals- Global Research and Development Journal for Engineering | Volume 4 | Issue 4 | March 2019 ISSN: 2455-5703
Fuzzy Logic Based Electricity Theft Identification in Distribution Systems S. Palaniyappan Assistant Professor Department of Electrical and Electronics Engineering SRM TRP Engineering College, Tiruchirappalli – 621105 India
Abstract Electricity consumer dishonesty is a major problem faced by all power utilities. Finding proficient measurements for detecting duplicitous electricity consumption has been a dynamic research area in recent years. This paper deals with Neuro-Fuzzy logic based electrical power theft detection, the quantity of theft power, finding the exact location of theft zone and controlling of theft in the location. The implementation of this proposal in a most efficient manner is to develop a Neuro-Fuzzy algorithm based electricity theft monitoring system which comprises PIC microcontroller and interfacing circuits on the entire location and which is installed at Electricity Board. It is well planned at the verdict out of theft information exhibited by the PC. This technique is proved in this paper as a simple way to detect electrical power theft without any human interface. Keywords- Power Theft Detection, Non-Technical Losses (NTL) and Neuro-Fuzzy Logic Technique Etc
I. INTRODUCTION The power stealing is a foremost problem in recent days which causes lot of loss to Electricity boards. It is highly preclude, and at the same time it directly affects the economy of a nation. As per survey every year Rs.12,50,000 crores power theft losses arise by utility companies and households across the world. In our country Rs. 2,25,000 crores losses will occurs over the power theft happening every year. Power theft losses consists of two categories such as Technical losses and Non-technical losses. The whole technical losses are caused by power dissipation in the transmission lines, transformers, power system components and also computed with the information about total load and the total energy billed [1]. The factor of power theft in the NTL varies from state to state, and within a state itself, it shows variation from region to region. Non-technical losses cannot be exactly calculated, but can be estimated from the difference between the total energy supplied to the customers and the total energy billed. In many developing countries, the data regarding NTL is very difficult to analyze theft in terms of actions that cause these losses [2]. The existing system is not able to identify the exact location of tapping in the electricity. Wireless data transmission and receiving technique is used to provide an additional facility of wireless meter reading with the same technique and same cost [3]. This will protect the distribution network from power theft is done by tapping and meter tampering. In [4], GSM based electricity theft identification consists of microcontroller, energy meter and ZIGBEE unit is used to monitoring theft and also send a messageto the authorised agency which looks after the electricity consumed. The main problem associated with the rural areas which is really difficult to install the wired system to convey the information. In [5] [6], these paper deals with automatic meter reading and theft control system in energy meter. This model reduces the manual manipulation work and theft control. The proposed paper is used to identify the exact location of the theft, amount of power theft and corresponding penalty charges are calculated by using Neuro-Fuzzy Technique implemented through the PIC Microcontroller. This technique provides the theft information and reduce the penalty amount to the government and also improve the generated power is utilized in a most efficient manner.
II. PROPOSED APPROACH The Aggregate Technical & Commercial (AT&C) loss of Indian utilities ranges from 12 to 70%. The generation and transmission sectors of the Indian power sector are almost in parity with other utilities across the world. [16] In the distribution sector, irrigation pump sets and single point unmetered connections are major sources of energy losses. Since energy loss and theft cannot be measured but only estimated, practically no one in the industry is able to say how much electricity is used by these two sectors with reasonable accuracy. The absence of metering system and faulty meters give ample opportunity for utilities to fabricate on transmission and distribution (T&D) losses. The proposed stealing block diagram consists of PC unit, PIC 16F877A microcontroller, LCD display, Neuro-Fuzzy logic algorithm, Loads (Light and Fan) and MAX232 connector. The fuzzy logic algorithm contains the number of units programmed and identify the theft from load side and report to the EB office through display units. The PIC microcontroller is used to transfer the data (include power with respect to time) to the Electricity board from each home. The block diagram of Neuro-Fuzzy Technique based power theft detection in particular area as shown in fig. 1.
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