A Recent Development In The Electricity Transmission And Distribution Grids
Electricity is a backbone of our existence in today’s world. It’s quite hard to imagine a world without electricity in the modern times. We are dependent on it for a major part of our day to day activities. However, electricity does not exist in the natural form and also cannot be stored in usefully large quantities. It has to be harnessed from renewable or non-renewable resources and must be generated continuously to meet the demand from consumers. The electricity that is generated from its various sources are delivered to end users/consumers through the Transmission and Distribution (T&D) lines. Transmission lines comprises of wires/cables that are hung on tall metal towers and carry electricity over long distances at high voltages. The electricity generated at power plants moves through this complex system, often referred to as the ‘grid’, which has powerlines, transformers and electricity substations that ultimately connect electricity producers with the consumers.
High voltage electricity is used in long distance electricity transmission as that state is more efficient and less expensive compared to transmission at low voltage state. However, electricity at lower voltage is required at homes and businesses, who form the end users, as that state is safer for consumption. Transformers at various stages in the grid and those in substations perform the job of increasing (stepping up) or reducing (stepping down) electricity voltages to adjust to the different stages of the movement of electricity from the source of power plants through long-distance transmission lines and lower voltage distribution lines that carry electricity to homes and businesses.
A recent development in the transmission and distribution grids is the smart grid. A smart grid enhances the traditional transmission and distribution system through usage of digital technology and advanced instrumentation that enables utilities and customers to receive up to date information from the grid and also enables communication with the grid. The grid is termed smarter as it makes the electrical T&D system more reliable and also efficient in reducing transmission losses and enables the utilities to detect and fix problems quickly. The smart grid also enables end users to intelligently manage usage of electricity, especially during times of high demands or when system reliability requires lower energy demand.
Advances in power electronics technology has improved the performance and output waveforms of PWM (Pulse-Width Modulation) voltage source inverters and have made them the popular choice for many general purpose variable speed induction motor drives in energy saving applications. Switching frequencies of 10 to 20 kHz with 0.1µs rise times are common with the current Insulated Gate Bipolar Transistor (IGBT) technology. In many industrial applications the PWM inverter and the motor must be at separate locations, thus requiring long motor leads or long cables. [image: ]While the high switching speeds and zero switching loss schemes drastically improve the performance of the PWM inverters, the high rate of voltage rise (dv/dt) of 0 to 600V in less than 0.1 µs has adverse effects on the motor insulation and bearings and deteriorates the waveform quality in applications where long cables are employed.
It has been found that the pulses will travel at approximately half the speed of light (150-200m/µs) and if the pulses take longer than half the rise time to travel from the inverter to the motor, then a full reflection will occur at the motor and the pulse amplitude will approximately double. The voltage reflection due to fast switching transients can be reduced by increasing the rise time and fall time of inverter output voltage pulses. The high dv/dt of inverter output pulses with steep rise time through long cables results in voltage doubling at motor terminal due to voltage reflection phenomena.
The overvoltage appearing across the motor terminal stresses the motor insulation and finally leads to motor insulation failure. The voltage reflection is dependent on factors like rise time of inverter output pulses, the length of the cable used for interconnecting inverter and motor and surge impedance of motor and cable. If the propagation time is more than half of rise time, then voltage reflection at motor terminal occurs with peak voltage of twice the amplitude of input voltage.
The passive dv/dt filter consisting of inductor, capacitor and resistor will increase the rise time and reduce the dv/dt gradient of inverter output voltage pulse. But usage of such passive resistors leads to large power loss which is a major drawback. The required voltage rise time to avoid voltage reflection depends on the length of the cable. If the propagation time is more than half of rise time, the motor terminal voltage will shoot up to double the amplitude of input voltage. The amplitude of reflected voltage wave depends on voltage reflection co-efficient of motor and is given by equation below:ℾm = Zm-Zc/Zm+Zcwhere Zm is motor characteristic impedance and Zc is cable characteristic impedance. The peak motor terminal voltage(Vm) is given by the below equation :Vm=Vsrc(1+ ℾm)where Vsrcrepresents voltage at source The reflection co-efficient varies with the size of the motor and its value reduces as the size of motor increases. The literature reports that the reflection co-efficient value ranges between 0.65 to 0.95.To reduce the losses in induction motor, fast switching devices are used in the inverter, but this in turn may cause overvoltage to appear at the motor terminals. The shorter rise time or steep slope of the voltage would cause the motor insulation to break down.
Many researchers have worked on the topic of overvoltage in transmission lines. Some research work focus on the overvoltage in power lines and others on overvoltage on motor connected via long leads on inverter fed systems. The researchers have identified the factors causing overvoltage. Artificial Neural networks (ANN) based solutions are proposed by few researchers to predict overvoltage on power lines.
Support Vector Machines (SVM) based classification of supply voltage to induction motor was also explored by researchers in the past.
D. Thukaram et al. presents an ANN based approach to predict the peak overvoltage by switching transients during line energization. Levenberg–Marquardt method is used to train the multilayer perceptron. The insulation level of the Extra High Voltage system (EHV) ac system is determined by the switching overvoltage. Electro Magnetic Transients Program (EMTP) tool is used for computation of switching and temporary overvoltage. The aspects considered to influence the transient overvoltage are line length, switching angle, source strength and receiving end reactor.
The proposed tool would be helpful to the operator to predict the overvoltage. During the line energization, travelling wave will start to travel along the line towards the receiving end and double there at the open end with overvoltage near to 2 p.u. A 400kV EHV network is considered for the explanation of the proposed methodology. Motivation for controlled switching of transmission line is to minimize the switching overvoltage during energization. Increase in length, increases the charging current and creates overvoltage at the receiving end bus. Two schemes are adopted to estimate overvoltage in the proposed methodology. In the first scheme, receiving end reactor has fixed value. The parameters that influence peak voltage in this scheme are switching angle, source strength and transmission line length.[image: ]In the second scheme, receiving end reactor is switchable and has various values. The parameters that influence peak voltage in this scheme are receiving end reactor value, switching angle, source strength and transmission line length. An MLP with one hidden layer and 10 hidden units is used in the proposed methodology for both schemes. Supervised learning of ANN is adopted for the proposed methodology, for which input is given to EMTP to get the peak values of transientovervoltage and the same data were used to train the ANN. Error and percentage error are calculated as: Error =|ANN- EMTP|/ EMTP percentage error (%) = error * 100Seyed Abbas Taher et al. uses ANN for nonlinear input-output mapping, to predict temporary overvoltage due to transmission line energization.
Multi-Layer Perceptron(MLP) is trained using Levenberg–Marquardt second order method for obtaining small mean square error(MSE).Switching overvoltage is of primary importance in insulation co-ordination for extra high voltage (EHV) lines. Power system blockset(PSB) of MATLAB/Simulink tool is used for computation of overvoltage in the proposed approach. The sample system considered for explanation of the proposed methodology is a 400 kV EHV network. This methodology considers the following parameters of the network to predict the transient overvoltage.
- Equivalent source voltage
- Equivalent resistance
- Equivalent inductance
- Equivalent capacitance
- Closing time of the circuit breaker poles
- Line length
- Line capacitance
- Shunt reactor capacity.
Magnitude and duration of the overvoltage does not depend directly on any single isolated parameter and variation of one parameter can alter the influence of another parameter. This forbids the derivation of simple formulae applicable to all cases. So, in proposed methodology an ANN is used to predict the magnitude and duration of the peak overvoltage during line energization. A feed forward MLP with 2 hidden layers and 10 hidden units is used in the proposed methodology. Single and 3 phase transmission line energization are analyzed in this work. Percentage errors is calculated as: Error = ANN -PSB/PSB *100A.
V. Jouanne and et al. examines the effect of long motor leads on high frequency PWM fed AC motor drives. It is observed that, though high switching speed improve the performance of the PWM inverters, it has adverse effect on motor insulation. Also, long cable length causes overvoltage at the motor terminal which further stress the motor insulation. Cable transmission theory and cable capacitance analysis are presented and voltage reflection is investigated. The paper also illustrates the effect of inverter pulse output rise time and cable length on the magnitude voltage on the motor terminals.
A. Acharya B and et al. designed an output dv/dt filter for motor drives. Paper proposes new procedure for designing LC clamp filter. PWM inverters output voltage has high dv/dt, which causes doubling of peak voltage at the motor terminal connected using long leads. By using the proposed filter, the voltage doubling effect can be reduced at the motor terminal. Mitigation techniques at the motor end are usage of insulated bearing and electrostatic shield between stator and rotor, increasing the insulation grade and also termination to match the impedance of motor and cable. At the inverter end mitigation techniques are usage of filter, reduction of common mode voltage and resonant switching inverter. The proposed filter, apart from addressing both common mode and differential mode components, the resonant frequency is selected so that the induction motor at high frequency behaves as inductive load and hence gives the higher order filter LCL effect. Effectiveness of the verified using Pspice simulation. The proposed filter is compact and can be placed in inverter package easily.
Vitor F. Couto and et al. proposes an alternate way for modeling transmission line by analyzing the three phase conductors separately. Usually, power transmission lines are modeled as a single quadrupole circuit, with parameters arranged with the same shape of the Greek letter, Pi. 230 kV/197 km transmission line is taken for showing the significance of the proposed method. Simulated results show the occurrence of overvoltage along the line, although voltage has acceptable values at its both ends. Need for new procedures for insulation co-ordination of power transmission lines is highlighted by the researchers.
