International Journal of Industrial Electronics, Control and Optimization
Volume:4 Issue: 4, Autumn 2021

This study introduces a single-ended method to detect the protection zone and distinguish faults occurring in the back of the relay in the transmission lines and then provides an algorithm to classify different types of faults, including a lightning strike on phases and shield wire. Accordingly, using the Wavelet Transform (WT), the first class of Traveling Wave (TW) current is separated at the beginning of all bus-connected lines. The faulty line and the protection zone are selected based on the relations governing the radiation and reflection. Then, given the features and relations extracted from these waves, the faults caused by lightning strikes on the transmission line and conventional faults are classified, with considering the mutual induction between TWs on the transmission line phases. This action is essential and helpful for transmission line with single phase tripping and auto-reclosing mechanisms. Over 1100 faults with varying conditions and locations are implemented on a 100-km line with a voltage level of 230 kV in the PSCAD software to evaluate and test the proposed method. The results of this heavy simulation confirmed the validity, speed, and accuracy of the proposed method.

In this paper, an adaptive event-triggered consensus problem considering the time delay of the communication network is studied for heterogeneous multi-agent systems. An event-triggered interval is here considered as a specific delay and unified round trip time (RTT) delay. Furthermore, an efficient optimal predictive-based coordination control strategy is introduced for balancing the non-ideal behaviors of communication channels. In order to evaluate the efficiency of the proposed method for controlling network-based multi-agent systems with coupled subsystems, two stages are studied. In the first stage, the very method is implemented on two coupled continuous stirred tank reactors while in the second one, it is used for controlling the voltage and current of a DC microgrid consisting of several distributed generation units. To prevent the unessential utilization of communication resources, the transfer of information will actually occur in this mechanism if a specific event is triggered. The simulation results show the fact that in spite of being non-ideal and time-delayed communication channels, the proposed technique is capable for improving the performance of power grids.

This paper presents microgrid (MG) operation constrained to the reliability, flexibility, and environment indices in the presence of distributed generations (DGs) and energy storage systems (ESSs). The proposed scheme minimizes the total expected operating cost of MGs and DGs. It is also subject to alternating current (AC) power flow equations of MGs, constraints of operation, reliability, and flexibility in MG, and operation model of power sources and storage devices. Stochastic programming is incorporated to model uncertainties of load, energy price, the active power of renewable energy generation, availability of MG equipment, sources, and storage devices. Following on, a hybrid solver formed by combining artificial bee colony (ABC) and sine-cosine algorithm (SCA) is adopted to achieve the optimal solution with approximate conditions of unique ultimate response. Eventually, the suggested scheme is implemented on a 69-bus radial MG, where the numerical results confirm the capability of the scheme in improving the operation, reliability, flexibility, and environment status of the MG.

In this paper, a new method is developed to detect and track the resonance frequency of ultrasonic transducers. In order to have an acceptable performance of transducers, power supplies should be able to detect and track the resonance frequency. Different methods have been used for this purpose. In this research, the voltage of the transducer and the phase difference between the voltage and current are used to find the resonant frequency. The maximum voltage of a transducer is founded in a predefined frequency interval. Afterward, the minimum phase difference between the voltage and current is obtained in a smaller interval around it. The simultaneous use of the voltage and phase shift increases the accuracy and speed of the algorithm. Since the transducer's voltage variations are relatively large near the resonant frequency, it is a versatile parameter compared to the current used in other methods to indicate the resonance frequency. The algorithm is implemented within a microcontroller. An FPGA is used to generate accurate frequency using the Direct Digital Synthesis (DDS) method. The algorithm can detect the resonant frequency under free conditions. Applying force to transducers or emerging the transducer's head to the water changes the resonant frequency. The experimental tests showed that the algorithm could find and track the resonant frequency automatically under loading conditions.

Power systems are categorized as nonlinear dynamical systems, and the importance and complexity associated with their stability have dramatically increased. Accordingly, the behavior of power systems can be characterized by interactions between continuous and discrete-event dynamics. This paper proposes a systematic approach to the design and analysis of a supervisory control scheme for power systems using the hybrid automata (HA) model. The proposed model for optimal controller application is derived, and the power system's overall behavior is modeled using HA to enhance its stability. Hybrid systems' formulation incorporates continuous dynamics as well as discrete switching behavior into a modeling and control framework, thus allowing a complete system description while crystallizing the concepts of safety into system design criteria. This study uses a power system HA model as a discrete event system (DES) plant and controller. In the proposed method, to present the hybrid model, the discrete events used include the presence and absence of disturbances and voltage control elements, fault, sudden load increase, capacitor bank, and under-load tap changer (ULTC) transformer. Voltage stability and control are investigated by the generators’ rotor angle, bus voltage, eigenvalues, and the stability theory of the switched linear systems. Applications in voltage control, stability, and dynamic service restoration are presented on two benchmark power systems with 12 discrete states. The simulation results reveal the effective performance of the proposed supervisory controller model to enhance voltage stability in power systems.

The paper presents reliability-based operation (RBO) of an energy hub consisting of electric vehicles (EVs) and a combined cooling, heating, power (CCHP) system in the electricity, natural gas, and district heating networks. The proposed strategy aims to minimize the total expected operating and reliability costs of the mentioned energy networks as objective functions. Furthermore, the problem is subject to optimal power flow (OPF) equations, reliability constraints, and the hub energy model including constraints of EVs parking lot and CCHP. This strategy has a mixed-integer nonlinear programming (MINLP) model; hence, mixed-integer linear programming (MILP) will be utilized to achieve a unique optimal solution in less computational time for the proposed scheme. Moreover, the scheme includes uncertainties of the load, energy price, the demand of EVs, and equipment availability of the given systems, which are modeled using scenario-based stochastic programming (SBSP). Finally, the approach is implemented on a standard test system in the GAMS software environment. Then, according to the numerical results, it is observed that the mentioned outline can achieve optimal operation conditions and high reliability in energy systems if the EVs and CCHPs are optimally managed in the energy hub form.

In this paper, the effects of magnetization patterns on the performance of Hybrid Electrical Vehicle (HEV) are investigated. HEVs have three magnetic field sources: armature winding, permanent magnets, and field winding. To initiate the investigation, the magnetic field distributions produced by these three sources are obtained. By using the magnetic field distributions, the machine is analyzed under no-load and on-load conditions, and the operational indices, such as self and mutual inductance, cogging-, reluctance- and instantaneous torque, and unbalance magnetic force (UMF) in x- and y direction are calculated. Various magnetization patterns are considered to investigate their influences on the performance of the machine. This step was done with Maxwell software. Furthermore, instantaneous torque and magnitude of UMF are expressed in term of pole arc to pole pitch ratio by using artificial intelligence. The optimal of the pole arc to pole pitch ratio to maximize the average of instantaneous torque and minimize the magnitude of UMF by some multi-objective algorithms is also computed. The modeling and optimization are performed by Matlab Software.

Management and control of charging/discharging of Electric vehicles (EVs) with the aim of profitability for the Distribution System Operator (DSO) and the private sector is one of the challenges in operating Electric vehicles Charging Stations (EVCS). This paper proposes a novel methodology for optimal planning of charging/discharging of the hybrid wind- EVCS which on the one hand, lead to correction of the load curve and on the other hand, improves the grid resilience in extreme weather conditions. In the proposed methodology, since the weather-based outages lead to consumer interruptions, the idea of profit-sharing between DSO and EVCS owners is proposed to incentivize the owner to implement the obtained charging/discharging schedule. To this end, firstly, a Monte-Carlo based stochastic framework for forecasting the probability of weather-based line outages and also modelling uncertainties is devised. Then, a resilience-oriented multi-objective optimization algorithm is presented that, while coordinating the operation of the wind turbine, EV management and Demand Response Programs (DRP), the profits of both EVCS and DSO are maximized during daily operation planning. The resiliency improvement of the proposed method is evaluated by using metrics. The obtained optimal results prove the effectiveness of the proposed method in increasing resiliency and benefits for all players.

This work proposes a new multilevel inverter consisting of basic and submultilevel units. The basic unit is made-up of four isolated dc voltage sources, two bidirectional switches and ten unidirectional switches. To increase the number of the output voltage levels, a cascaded architecture based on series connection of sub-multilevel is proposed. The proposed inverter utilizes two algorithms to determine the values of dc voltage sources. Number of IGBTs, dc voltage sources, gate driver circuits, variety of dc voltage sources and peak standing voltage on the switches are calculated and their optimization to produce maximum number of levels in output voltage is investigated. To examine advantages of the proposed inverter, the topology is compared with other topologies. The results show superiority of proposed topology over most conventional topologies, in number of circuit components. Finally, to confirm the performance of the proposed multilevel inverter, experimental results of a 25-level inverter prototype are provided.

One of the most important classes of fractional calculus is the fractional optimal control problem (FOCP), which arises in engineering. This study presents a direct and efficient numerical method for solving a class of (FOCPs) in which the fractional derivative is in the Caputo sense and the dynamic system includes the fractional- and integer-order derivatives. For this purpose, we use the operational matrix of fractional Riemann-Liouville integration based on the shifted Gegenbauer polynomials. First, the fractional- and integer-order derivatives in the given problem are approximated based on the shifted Gegenbauer polynomials with unknown coefficients. Then by substituting these approximations and the equation derived from the dynamic constraint into the cost functional, an unconstrained optimization problem is obtained. The main advantage of this approach is that it reduces the FOCP given to an unconstrained optimization problem and using the necessary optimality conditions yields a system of algebraic equations which can be easily solved by Newton’s iterative method. In addition, the convergence of the method is proved via several theorems. Finally, some numerical examples are presented to illustrate the validity and applicability of the proposed technique.