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A prepaid meter monitoring system with SMS alert is designed simulated and constructed using microcontroller to achieve a unique transmission of SMS messages to designated mobile phone numbers. The work is a response to the need to checkmate commercial energy losses in utility electrical distribution system. The system utilizes a normally open micro-switch incorporated into the monitoring system to detect when the prepaid meter cover is opened. The system triggers a series of actions which eventually lead to the sending of an SMS alert message to the GSM mobile phones at the commercial unit of the utility Electricity Distribution Company which contains the meter number and address where the tamper/theft originates. The system also triggers an alarm system to alert the individual within the vicinity that an intruder has tampered with the meter in order to commit fraud/energy theft. The system utilizes the existing GSM networks and protocols through the modem interface. When the messages are sent to the designated mobile phones the messages are also retained at the memory card interfaced to the modem which can be retrieved when the need arises. This work discusses in detail the steps taken in the process of realizing the set goals including the design, simulation, implementation testing and results. The construction was implemented with reliable and readily available components in the market. The results showed that the power of the system is 6 watts. The alternating current input voltage is 220V (AC) at 50/60 Hz. The output current of voltage regulator is 500 mA. The system was validated using bar chart for comparison of its functionality with the existing ones in terms of transmission of SMS messages, recording and tracking of information in real-time and the operation was very excellent which is a remarkable improvement over the existing prepaid meter monitoring system.
Title page i
Table of contents vi
List of table x
List of figures xi
Symbols and abbreviations xiii
1.1 Background of the Study 1
1.2 Electricity Theft Mechanisms 4
1.3 Causes of Electricity Theft
1.4 Existing Ways of Tackling Electricity Theft 7
1.5 Electricity Theft Identification In Distribution System 9
1.6 Aims and Objectives 15
1.7 Justification of the Study 15
1.8 Scope of the Study 15
1.9 Limitations of the Study 16
2.1 Related Works On Power Theft Identification 17
3.1 Simulation 23
3.2 Construction 25
3.3 The Design Circuits 25
3.4 Power Supply Unit 26
3.5 Battery Charging Unit 33
3.6. The Normally Open Micro-Switch 36
3.6.1 Detection System 36
3.7 Transistor Driver 39
3.8 Transfer Function of the Output Filter 42
3.9 Microcontroller 43
3.9.1 Pin Description of the AT89C52 Microcontroller 45
3.9.2 The Ports Description of AT89C52 46
3.9.3 Instruction Set of the AT89C52 Microcontroller 48
3.9.4 Software Algorithm 49
3.9.5 Serial Communication in Microcontroller 49
3.10 The Wireless Communication System 50
3.10.1 Short Message Service (SMS) Principle 51
3.10.2 The Working Principles of SMS 52
3.10.5 SMS Network Cellular Components 55
3.10.6 SMS Subscriber Services 57
3.11 GSM Modem Type 57
3.11.1 Communication with GSM Modem 57
3.11.2 GSM USB Cable 58
SYSTEM OPERATION, TESTING AND RESULTS
4.1 System Circuit Diagram 60
4.2 The Functions of the Components in the System Circuit
4.3 Results and Discussions 66
4.4 The simulation Tests carried out 67
4..4.1 No Theft Condition 67
4.4.2 Theft Condition 77
4.4.3 The Transistor Switching Time under Theft and on no Theft Conditions 89
4.4.4 The Transfer Function Magnitude and Phase Plot 91
4.5 Hardware Implementation 94
4.6 Completed Packaging of the Prepaid Meter Monitoring System 95
4.7 GSM Mobile Phone at Customer Unit of Utility Electricity Distribution Center 96
4.8 Validation the Results 97
Summary, Conclusion and Recommendation
5.1 Summary 102
5.2 Conclusion 103
5.3 Recommendation 104
Table 3.1: Table showing the Instruction set of the AT89C52 Microcontroller 48
Table 4.1: Inputs and Outputs of Operational Amplifier when the Output is Low on no Theft Condition 71
Table 4.2: The Output Voltage and Current of Voltage Regulator on no Theft condition 73
Table 4.3: The output voltage against input voltage on no theft condition 75
Table 4.4: Buzzer Voltage against Frequency 79
Table 4.5 Inputs and Outputs of Operational Amplifier at when the Output is High under Theft Condition 81
Table 4.6: Output current under Theft Condition 83
Table 4.7: The Output Voltage of the Prepaid Meter against Input Voltage of Utility Supply under Theft Conditions 85
Table 4.8: Input Voltage Variation against Frequency 87
Table 4.9: The Transistor ON and OFF Switching WaveForm Table 89
Table 4.10: The Transfer Function Magnitude against Frequency 91
Table 4.11: The Transfer Function Phase Angle against Frequency 92
Table 4.12: The Reviewed System Efficiency 99
Table 4.13: Specification table of Power, Voltage, Current and Frequency Utilized 101
Figure 3.1: The system block Diagram 26
Figure 3.2: Block diagram of the power supply unit 27
Figure 3.3: The bridge rectifier 28
Figure 3.4: The AC input voltage, the DC output voltage and the
filtered DC output waveforms of the power supply 29
Figure 3.5: Circuit Diagram of the power supply unit 32
Figure 3.6: Battery charging circuit diagram 35
Figure 3.7: The Circuit Diagram of the Detection system 38
Figure 3.8: Circuit diagram for the transistor driver 40
Figure 3.9: AT89C52 Microcontroller pin configuration 44
Figure 3.10 SMS Cellular Network 56
Figure 4.1: Circuit Diagram 61
Figure 4.2: The simulation result when there was no theft 69
Figure 4.3: The simulation result when there was theft 72
Figure 4.4: Plot of Buzzer Voltage against Frequency 74
Figure 4.5: Plot of the output voltage against input voltage on no theft conditions 76
Figure 4.6: The simulation result when there was theft 78
Figure 4.7: Plot of Buzzer Voltage against Frequency under theft condition 80
Figure 4.8: Ouput voltage against inverting and non-inverting inputs at high output voltage level under theft condition 82
Figure 4.9: Plot of the output current under theft condition 84
Figure 4.10: Plot of the output voltage against input voltage under theft conditions 86
Figure 4.11: Plot of the Output Voltage against frequency under theft condition 88
Figure 4.12: The waveform of the switching transistor OFF or ON mode under theft or no theft condition 90
Figure 4.13: Transfer function magnitude plot against frequency 92
Figure 4.14: Transfer function phase angle plot against frequency 93
Figure 4.15: Photo of the components soldered on the vero board. 94
Figure 4.16: The photo showing the complete packaging of the prepaid meter theft monitoring system 95
Figure 4.17: SMS alert reading received with mobile phone at consumer unit at Utility Electricity Distribution Company 96
Figure 4.18: The validation of the work using bar chart representation of various Author’s reviewed 100
AC Alternating current
IC Integrated circuit
DC Direct current
SMS: Short Message Service
GSM: Global System for Mobile
SVM: Support Vector Machine
FIS: Fuzzy Interference System
AMI: Association Montessori International
PLC: Power Line Carrier
CPS: Cellular Phone System
NTL: Non Technical Loss
LHD: Left Hand Drive
LDR: Light Dependent Resistor
IDE: Integrated Development Environment
PROM: Programmable Read-only Memory
ANSI COMA: American National Standards Institute /Code Division Multiple Access
MSC: Mobile Switch Center
PSTN: Public Service Telephone Network
HLR: Home Location Register
VLR: Visitor Location Register
SMSC: Short Message Service Center
TCP/IP: Transmission Control Protocol/Internet Protocol
GMSC: Gateway Mobile Switching Center
EDC: Electrical Distribution Company
LED: Light Emitting Diode
BJT: Bipolar Junction Transistor
TTL: Transistor Transistor Logic
ROM: Read Only Memory
RAM: Random Access Memory
EA: External Access
VCC: Voltage at Common Collector
PSEN: Program Store Enable
ALE: Address Latch Enable
RxD: Reflex Datafile
TxD Transmit Data
RD: Recurring Deposit
USB: Universal Serial Bus
CMGF: Command Message Format
Ctrl+z Control z
LM: Length Measurements
Bps: Bit Per Second
SCON: Serial Control
SBUF Register: Serial Data Buffer
1.1 Background of the Study
(Sule, 2010), described Power System as a network that provides regions, Industries and homes with electrical energy. He also stated that electricity generation, transmission and distribution are three stages of delivering electricity to consumers. This power system is known as the grid and can be broadly divided into the generators that supply the power, the transmission system that carries the power from the generating centers to the load centers and the distribution system that feeds the power to nearby homes and industries. The distribution system is a part of power systems which is dedicated to delivering electrical energy to the end user. The planning and the design of electrical supply system are everyday task for engineers in the electric utilities companies. The goal of power distribution planning is to satisfy the growing and changing load demand within operational constraints and with minimal costs Sharma, et al., (2008). It is necessary for Power Distribution Company to update their customer’s information that corresponds to their electrical attributes. The database contains useful information that shows linkages with the distribution transformers, feeder and substation. It is also important to design a system that monitor the accuracy of consumption at the customer end. The design of smart system improves system reliability, hence encourages investments to the industry.
Electrical distribution improvement has many approaches ranging from feeder optimization, phase balancing and costing model for distribution planning. All these are ideas and efforts by many scholars in the field of electronics to improve distribution. In Nigeria, the power distribution has constituted seventy percent of electrical utility problem Titus, et al., (2013). Due to inadequacies in planning and use of wrong solution for an identified problem, it is obvious to note that the major problem of electricity utility comes from distribution of bulk power that have been transmitted over a long distance and the reason for this is that distribution demands are not known and well managed. Against the back drop that consumers of electricity are not identified based on their location, it is impossible to estimate the accurate demand of electricity for customers in such area. Another major problem is identified as commercial losses that reduces revenue, hence discourages investment into the system, Damian et al., (2015). The use of estimated load has also reduced the system reliability. This is a problem that cannot be solved overnight. However, with the right approach, solution is certain. The SMS (short message service) alert can provide the solution in the management of utility by way of detecting commercial loss which is a function of electrical theft.
(Kaira, 2014) proposed two methods in conjunction with the existing methods; the two methods are:
Identified Differential scheme is achieved by attachment of sensors to heavy appliance such as fridges air conditioner and other heavy equipment, other loads were attached to one sensor. In the case where the total energy measured from individual sensor is sum and is not equal to that of the meter, theft is detected, otherwise no theft.
In integrated scheme of sort X-bee is embedded into the meter that communicates with the module present at sensing the total power given out of it. In the case of electrical theft, consumer homes were individually switched off remotely to detect consumer involved in the theft.
The limitation of the two methods proposed by Kalra (2014) is that privacy of the consumer is abused by installation of multiple sensors in the differential scheme. The method is costly to manage because at every intervals of time check is carried out to detect theft. The right of the customer to access energy is infringed, in the integrated scheme consumers that are not involved in electricity theft are cut off from supply for a period of time to detect the premises where the theft occur, this is also infringing on right of some customers who are not involve in the unwholesome behaviour.
Non-Technical Loss (NTL) occurs as a result of electricity theft (Dey, et al., 2010). He further highlighted types of electrical theft as: Fraudulent activities of customer, Stealing electricity, Irregular bill payment and unpaid bill. Meter tampering is classified into analogue and digital. Dey, et al., (2010) described Analogue tampering as Shortage of phase current coil which caused the current to pass through the shorter path which results to meter’s unable to detect current passing through it. Current flow reversal by swapping of load and supply terminal, hence meter would be unable to detect quantity of electricity through it. Neutral disconnection hence meter unable to detect energy through it because of no potential difference.
Magnet is used to slow down rotation of the disc in analogue meter, hence reduction in sensitivity of the meter to record energy value. Tampering in digital motor is noticed when neutral is removed. Installation of’ current transformers at both phase and neutral line to measure currents and teed hack to micro controller to determine difference in current is proposed Dey, et al., (2010).
In analogue meters, painting of rotating disc divided into four equal proportions in black and white, with LHD and LDR attached to the disc and powered is proposed. Rotation of the disc indicates no theft as the voltage to the micro controller varies otherwise theft is detected Dey, et al; (2010).
1.2 Electricity Theft Mechanisms
Electricity thefts may occur in different forms. From available literature and practical daily reports in Nigeria, Sayema, et al; (2014), the common ways include bypassing (illegal tapping of electricity from the feeder), meter tampering (by grounding the neutral wire as it does not measure readings) and physical methods to evade payment of bills. The basic method of stealing electricity is a direct wire-connection to a main power route passing a shop or a house so that electricity can flow to the consumer without crossing the electric meter installed by a government agency which is responsible for providing electrical services to customer. There are different types of theft done all over the world. Huge amount of power theft are done by tapping from line or bypassing the meter.
According to a study, 80% of the total theft detected all over the world is from residential buildings and 20% from commercial and industrial premises, Suriyamongkol, (2014).
1.3 Causes of Electricity Theft
All energy distribution companies operate with some accepted degree of losses. This is no different from the scenario in Nigeria. The losses incurred are subdivided into two namely: Technical losses and Non- technical losses.
Some localized catalyzing factors influencing electricity theft in Nigeria include lack of accountability in electricity market system, political protection of employees involved in corruption, influential customers who do not pay their bills, absence of effective laws to abate electricity related crimes and inadequate and ineffective enforcement of existing weak laws and generally negative attitude of electricity customers. Electricity pilferage has its root in corruption and bad governance. Customers attitude contribute a great deal to revenue losses. These attitudes range from their ill-conceived feelings that electricity should be a welfare commodity and therefore legitimate to steal from the state, to the generalization that the state is not incurring losses. They do not have the fore-knowledge that the money realized from the payment of bills are re-instated into the power sector for its improvement and development.
1.4 Existing Ways of Tackling Electricity Theft
The first step in electricity theft reduction is to become knowledgeable about the theft problem. Unless the nature and extent of power theft are known in great details, any attempts to deal effectively with the problem are prone to fragmented and limited action that has little over-all success, Smith, (2004). Corruption is one of the difficult problem areas for electricity organizations because power theft occurs with the connivance of employees of the power sector. Employees should hence, be paid adequately so that the issue of bribe collection will not be their last resort. Power companies are combating theft through the use of smart meters and sophisticated software that continuously records consumption and send the data back to them. One advantage of using the smart meter is that it eliminates contact between the consumers and the power provider’s employees thus preventing the issue of bribery, Depury, et al., (2010).
The already existing methods which may be utilized in tackling electricity theft in some countries where practiced include proper enforcement of electricity regulatory laws, periodic and impromptu checks of consumer homes, electronic tampering detection meter and use of prepaid meter. The limitations of using the smart meters are that, consumers feel it discloses privacy of their homes which are not ethically true and that it interferes with radio frequency and create problems in radio transmission profile, Wang, et al., (2013). Periodic checks are not 100% efficient due to its laborious and sluggish nature. Adopting this kind of method in electricity theft reduction will delay accurate and effective reading of the meters in remote areas that are non-accessible. Moreover, as result of the ever-increasing rate of corruption (such as greed and bribes) in the Nigeria, the proper enforcement of laws would take a drastically longer time than stipulated. In the past, committees that were set- up see it as an avenue to amass wealth rather than strictly punish defaulters, thus all these reasons have hindered the growth of our power sector.
1.5 Electricity Theft Identification in Distribution System
Electricity theft takes place in various forms and works with the help and support of different parties which include the utility staff and political leaders based on enacted laws and consumers. The major challenges of utility company are that the money invested into production of electricity for distribution is not recovered as a result of electrical theft.Kalaivani, (2014). As a result, the masses have to pay extra fees in terms of tariff toutility company to compensate for these losses, (Kalaivani, 2014).
According to Kalaivani (2014), electricity consumers steal energy in the following way: Unhooking technology, One fire one ground technology, Reverse the in and the out, Cross meter to connect wire, Exchange fire with zero. (Kalaivani, 2014) proposed a method to monitor electricity theft based on information from a distribution transformer and various output of meter readings from the various consumer’s premises. In their method, the energy giving out from a transformer is measured while various reading in the consumer’s premises is summed up with a comparator. The outputs of the reading from different consumer’s premises are feed into a differentiator with output from the transformer. This various outputs are subtracted; a difference indicates that there is power theft. The limitation of this is that, they only measure power theft at the transformer, and cannot point precisely the consumer premises that these theft occurred, an intelligent system is required to solve the problem.
(Sagar et al., 2013) used the method of installing communication meter at both customer’s premises and the electric pole connecting the customer’s premises. The two meter sent out information of consumption, which is compared to check the difference. The difference in the two measurements indicates power theft. The disadvantage of method is that, the proposed method is post-paid metering which does not support fast revenue collection. In addition, the method involves data collection and analysis, hence involves more cost of managing electricity.
According to Syed, et al., (2012), they proposed that the power distribution and theft control by identifying patterns of distribution demand, consumption, loses and supply power to areas in need of power at a particular time based on the available database of consumer demand, consumption and losses. In view of Syed et al., (2012) they identified four kinds of power theft thus: Kunda, Meter reversing, Hinder hard dealing and Power mafia.
In kunda method of power theft, the utility poles are very close enough to building that wire can be easily suspended on them in the form of hook, while in meter reversing electrical technician can carry out this kind of theft with the consumer and reversing the electrical meter to give lower reading. Under hand dealing is a method of power theft where the utility staffs connects consumer’s to power line illegally because they have been paid some stipend. Power mafias are groups of highly organized power thefts, they controls some areas and detects what happens in those areas Syed, et al., (2012).
Power theft can be combated by mapping area of power demand, load shading technique will be used use to cut off area that are prone to power theft and increase power supply to area less prone to theft Syed et al.,(2012). One major disadvantage of this technique is that it does not provide solution to power theft at each individual premises rather it only provide a mapping of the area to show distribution planning.
Toward power to all: A case study of misuse of power in Lucknow India, misuse of power was studied by Triparthi, (2011). It was observed that consumers do not turn OFF their lights during the day time because there is no special billing plan. The billing plans are the same for all time of the day. They proposed that electricity billing plan should not be the same for all time of the day so that consumers will be forced to turn off their light during periods that light are not necessary, Triparthi, (2011).
According to Mohammed, (2012), GSM base based smart meter distribution system identifies common methods used by consumers for electrical theft. The methods are as follows:
Installing of GSM smart miners al both consumer’s premises and transformer supplying to the consumer linked to database installation at central station was proposed by Mohammed, (2012). The energy consumption at every premises connected to the transformer are sent to the data base and summed up. The total consumption of the houses is compared with transformers load at interval, in case of difference, electrical theft has occurred in a particular interval and vicinity. Accordingly the three phases and neutral current were also compared. Limitation of this method is that they considered energy theft in a particular area and riot in particular premises, using information from various consumer premises and the transformer, hence needed to be improve upon.
Electricity losses occur as a result of electrical theft due to meter tampering, meter malfunctioning, illegal connections and billing irregularities, Thong, et al., (2010). Support Vector Machine (SVM) and fuzzy Interference System (FlS) are proposed for detection of nontechnical loses. Meter event log by Remote Meter Reading arid Installation inspection were used for loss detection. Limitation of this method is that theft is not detected instantly and data analysis takes a long time before theft can be detected. Another limitation is that too much data is involved and this may bring confusion hence wrong detection.
According to Kalra, (2014), the following ways are used by consumer to steal electricity. Direct hooking from line, this constitutes 80 percent of the total power theft. It was farther stated that consumers tap directly from the point ahead of the energy meter. Other methods include input, and output terminals that have been shorted by while in order to disallow energy meter to registered consumption.
(Kalra, 2014), also noted that injection of foreign material causes the meter to misbehave against the utility company’s condition and operate to advantage of the customer involve in the theft .It was added that hole drilled in electromechanical meter obstructs free movement of the rotating disc by insertion of foreign material inside the meter. According to Kalra (2014) the following methods were in use and could not totally eliminate theft detection.
Vector base data classification method which involves data acquisition, processing, feature extraction, classification training and parameter optimization, classification, data post processing, and suspected customer list generation. In his idea, a data set of customer consumption pattern is developed on historical data and applied on Support Vector Machine (SVM). SVM are trained to present all possible form of data. Specification base intrusion detection technique, in this technique, use of monitoring state to improve the detection rate over a wireless sense network, mutual inspection and AMI.
Game theory base detection investigate incentive problem of electricity distribution where customer energy usage is imperfectly observable by the distributor. The researcher also noted that as a result of privacy protection of each customer and this makes it difficult for distributors to observe correctly the precise quantity of energy used.
Current electrical distribution system in Nigeria requires intensive approach in order to deliver quality energy to the customer. Energy losses are the major factors hindering the delivering of electrical energy. The losses are categorized as technical and commercial losses. High technical distribution losses in the system are primarily due to inadequate investments over the years for system improvement works, which has elements like transformers and conductors, and lack of adequate reactive power support, Thakur, (2004). The commercial losses are mainly due to metering efficiency, power theft, pilferages under billing and sharp practices of distribution staffs.
With the advancement of technology particularly in the field of computer as well as microcontrollers, all the activities in our day to day living have become a part of information and we find computers and microcontrollers at each and every application.
Nowadays, the energy consumption and energy distribution have become a big subject for discussion because of huge energy theft. Theft in this case refers to a deliberate attempt to steal considerable amount of energy by ensuring no/low energy recording in the measuring device. Hence, there is the need to think in this line and a solution has to be proffered. Thus this project work is taken up to serve the purpose of energy monitoring so that energy theft can easily be detected and huge penalties can be imposed on these thieves. By detecting energy theft cases, people or electricity consumers will become aware and energy theft can be prevented or seriously reduced to the improvement of the nation’s economy.
This project is categorized into two sections namely:
1.6 Aim and Objectives
The aim is to develop a system used to monitor and detect incidences of power theft in the form of connecting load directly to the power line, bypassing the energy meter, paying less than what is consumed and by changing connection of the lines.
The specific objectives are as follows:
1.7 Justification for the Study
Due to the prevalence of meter tampering and energy theft cases, the need to reason in this line and come up with solutions arose. Presently, in the country, there are no measures in place to curtail this problem. Hence the microcontroller based power theft identifier was invented. This system, once implemented will drastically reduce if not totally eliminate the problem of energy theft in the country.
1.8 Scope of the Study
The project is limited to two representations: models of electrical energy meters utilizing a normally open micro-switch as a detecting device placed inside the meters and using GSM modem to establish a link between the consumer residence and the Electricity power monitoring station and the AT89C52 microcontroller as the control device. The basic instruction set used by the AT89C52 microcontroller which enables it to perform its basic function is achieved by writing a working program using Assembly language, and this enables the microcontroller to provide a vital link with other components of the project to be able to control their activities within the system.
1.9 Limitations of the Study
The research is limited to erratic power supply prevalent in the country. As the system requires electricity to function, the absence of power supply will hinder its operation.
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