Journal of Operation and Automation in Power Engineering
Volume:7 Issue: 1, Winter-Spring 2019

The single-phase transformerless grid-connected photovoltaic (PV) systems, mainly the low-power single-phase systems, require high efficiency, small size, lightweight, and low-cost grid-connected inverters. However, problems such as leakage current, the DC current injection and safety issues are incorporated with transformerless grid-connected PV inverters. Besides, the new standards such as Low-Voltage Ride-Through (LVRT) capability and staying connected to the grid during the fault occurrence should be considered for the next generation of transformerless PV inverters. In this paper, a study is going underway on the LVRT capability and the Common-Mode Voltage (CMV) in a number of most common transformerless grid-connected PV inverters. In fact, by a comprehensive study on all possible switching combinations and the current paths during the freewheeling period of the selected inverters, the proposed control strategy for performance improvement of the PV inverters under the normal and the LVRT conditions is presented. As a matter of fact, a reconfigurable PWM method is proposed, which makes it possible to switch between two PWM methods and hence provide improved performance of the inverters in the LVRT condition. Finally, the results of simulations in the normal and the LVRT operations to verify the theoretical concepts are indicated.

Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, in this study a two-stage stochastic mixed-integer non-linear programing is used to model the optimal design problem of hybrid system for ships. The uncertainty of the hourly global solar irradiation and its effect on the output power of the PV system is taken into account. The probability density function of the global solar radiation follows a normal distribution. The Monte Carlo sampling approach is used to generate the scenarios with a specified probability and a proper scenario reduction method is used to decrease the computational burden of problem. Three cases are studied and the results are presented and compared.

Many different methods have been presented to solve unit commitment (UC) problem in literature with different advantages and disadvantages. The need for multiple runs, huge computational burden and time, and poor convergence are some of the disadvantages, where are especially considerable in large scale systems. In this paper, a new analytical and non-iterative method is presented to solve UC problem. In the proposed method, improved pre-prepared power demand (IPPD) table is used to solve UC problem, and then analytical “λ-logic” algorithm is used to solve economic dispatch (ED) sub-problem. The analytical and non-iterative nature of the mentioned methods results in simplification of the UC problem solution. Obtaining minimum cost in very small time with only one run is the major advantage of the proposed method. The proposed method has been tested on 10 unit and 40-100 unit systems with consideration of different constraints, such as: power generation limit of units, reserve constraints, minimum up and down times of generating units. Comparing the simulation results of the proposed method with other methods in literature shows that in large scale systems, the proposed method achieves minimum operational cost within minimum computational time.

Nowadays, water and electricity are closely interdependent essential sources in human life that affect socio-economic growth and prosperity. In other words, electricity is a fundamental source to supply a seawater desalination process, while fresh water is used for cooling this power plant. Therefore, mutual vulnerability of water treatment and power generation systems is growing because of increased potable water and electricity demands especially during extremely-hot summer days. Hence, this paper presents a novel framework for optimal short-term scheduling of water-power nexus aiming to minimize total seawater desalination and electricity procurement cost while satisfying all operational constraints of conventional thermal power plants, co-producers and desalination units. Moreover, advanced adiabatic compressed air energy storage (CAES) with no need to fossil fuels can participate in energy procurement process by optimal charging during off-peak periods and discharging at peak load hours. A mixed integer non-linear programming (MINLP) problem is solved under general algebraic mathematical modeling system to minimize total water treatment cost of water only units and co-producers, total fuel cost of thermal power plants and co-generators. Ramp up and down rates, water and power generation capacities and balance criteria have been considered as optimization constraints. It is found that without co-optimization of desalination and power production plants, load-generation mismatch occurs in both water and energy networks. By incorporating CAES in water-power grids, total fuel cost of thermal units and co-producers reduce from $1222.3 and $24933.2 to $1174.8 and $24636.8, respectively. In other words, application of CAES results in $343.9 cost saving in benchmark water-power hybrid grid.

The existence of unreliable renewable energy resources would be required to use energy resources and storage units simultaneously, particularly in applications such as electrical vehicles and stand-alone energy supplying systems. The objective of this paper is to introduce a new topology of multi input converter in hybrid power supply system of photovoltaic, fuel cell and battery for medium power applications. In this converter, the current ripple is eliminated, due to the presence of the coupled inductor. On the other hand, the probability to achieve a high voltage efficiency, to develop a high voltage DC link, will be achieved by using two transformers, which their terminals are in series. Since a combination of the magnetizing and the leakage inductors of these two transformers are used, there will be a zero voltage switching for switches, and also a soft switching for the output diodes, because of the presence of the leakage inductor in the secondary side of transformers. Steady state model and control system is discussed for the proposed converter. A 200 watt experimental prototype has been made in laboratory to evaluate the proposed converter.

In this paper, a comprehensive parametric analysis for an axial-flux permanent magnet synchronous generator (AFPMSG), designed to operate in a small-scale wind-power applications, is presented, and the condition for maximum efficiency, minimum weight and minimum cost is deduced. Then a Computer-Aided Design (CAD) procedure based on the results of parametric study is proposed. Matching between the generator side and turbine characteristics as well as the mechanical constraints is taken into account in design algorithm. A 2.5 kW AFPMSG with two parallel connected stators and surface mounted permanent magnets on its rotor disk is designed using the developed program, and then three dimensional finite-element analyses are carried out to validate the design procedure.

This paper proposes a new adaptive controller for the robust control of a grid-connected multi-DG microgrid (MG) with the main aim of output active power and reactive power regulation as well as busbar voltage regulation of DGs. In addition, this paper proposes a simple systematic method for the dynamic analysis including the shunt and series faults that are assumed to occur in the MG. The presented approach is based on the application of the slowly time-variant or quasi-steady-state sequence networks of the MG. At each time step, the connections among the MG and DGs are shown by injecting positive and negative current sources obtained by controlling the DGs upon the sliding mode control in the normal and abnormal operating conditions of the MG. Performance of the proposed adaptive sliding mode controller (ASMC) is compared to that of a proportional-integral (PI)-based power controller and SMC current controller. The validation and effectiveness of the presented method are supported by simulation results in MATLAB-Simulink.

Brushless DC (BLDC) motors are used in a wide range of applications due to their high efficiency and high power density. In this paper, sensorless four-switch direct power control (DPC) method with the sector to sector commutations ripple minimization for BLDC motor control is proposed. The main features of the proposed DPC method are: (1) fast dynamic response (2) easy implementation (3) use of power feedback for motor control that is much easy to implement (4) eliminating the torque dips during sector-to sector commutations. For controlling the motor speed, a position sensorless method is used enhancing drive reliability. For reference speed tracking, a PI control is also designed and tuned based on imperialist competition algorithm (ICA) that reduces reference tracking error. The feasibility of the proposed control method is developed and analyzed by MATLAB/SIMULINK®. Simulation results prove high performance exhibited by the proposed DPC strategy.

In this paper, a new high efficiency, high step-up, non-isolated, interleaved DC-DC converter for renewable energy applications is presented. In the suggested topology, two modified step-up KY converters are interleaved to obtain a high conversion ratio without the use of coupled inductors. In comparison with the conventional interleaved DC-DC converters such as boost, buck-boost, SEPIC, ZETA and CUK, the presented converter has higher voltage gain that is obtained with a suitable duty cycle. Despite the high voltage gain of the proposed converter, the voltage stress of the power switches and diodes is low. Therefore, switches with low conduction losses can be applied to improve the converter efficiency. Moreover, due to utilization of interleaving techniques, the input current ripple is low which makes the suggested converter a good candidate for renewable energy applications such as PV power system. Operation principle and steady-state analysis of the proposed converter in continuous conduction mode (CCM) and discontinuous conduction mode (DCM) are discussed in detail. Also, theoretical efficiency of the proposed converter is calculated. Finally, in order to evaluate the proposed converter operation by a renewable energy source such as a PV, the simulation results are presented. Moreover, a 220W prototype of the presented DC-DC converter is designed and implemented in the laboratory to verify its performance.

This paper develops an adaptive control method for controlling frequency and voltage of an islanded mini/micro grid (M/µG) using reinforcement learning method. Reinforcement learning (RL) is one of the branches of the machine learning, which is the main solution method of Markov decision process (MDPs). Among the several solution methods of RL, the Q-learning method is used for solving RL in this paper because it is a model-free strategy and has a simple structure. The proposed control mechanism is consisting of two main parts. The first part is a classical PID controller which is fixed tuned using Salp swarm algorithm (SSA). The second part is a Q-learning based control strategy which is consistent and updates it's characteristics according to the changes in the system continuously. Eventually, the dynamic performance of the proposed control method is evaluated in a real M/µG compared to fuzzy PID and classical PID controllers. The considered M/µG is a part of Denmark distribution system which is consist of three combined heat and power (CHP) and three WTGs. Simulation results indicate that the proposed control strategy has an excellent dynamic response compared to both intelligent and traditional controllers for damping the voltage and frequency oscillations.

In this paper, the operation of a future distribution network is discussed under the assumption of a multi-carrier microgrid (MCMG) concept. The new model considers a modern energy management technique in electricity and natural gas networks based on a novel demand side management (DSM) which the energy tariff for responsive loads are correlated to the energy input of the network and changes instantly. The economic operation of MCMG is formulated as an optimization problem. In conventional studies, energy consumption is optimized from the perspective of each infrastructure user without considering the interactions. Here, the interaction of energy system infrastructures is considered in the presence of energy storage systems (ESSs), small-scale energy resources (SSERs) and responsive loads. Simulations are performed using MCMG which consists of micro combined heat and power (CHP), photovoltaic (PV) arrays, energy storage systems (ESSs), and electrical and heat loads in grid-connected mode. Results show that the simultaneous operation of various energy carriers leads to a better MCMG performance. Moreover, it has been indicated that energy sales by multi sources to main grids can undoubtedly reduce the total operation cost of future networks.

One of the most efficient lighting technology is based on light-emitting diodes (LEDs). Common LED drivers with AC-input (50-60Hz) usually require a bulk electrolytic capacitor to decrease low-frequency ripple in the output. However, the critical element that limits the lifespan of the LED driver is the electrolytic capacitor. An isolated off-line LED driver is proposed in this paper, in which the required output capacitance is reduced so that the electrolytic capacitor can be omitted from the driver structure. The driver’s configuration and controlling method provide a high input power factor. Just a single switch and therefore a single controlling IC have been used in the proposed structure. The input power factor correction is implemented utilizing a boost-based method, and a novel structure is introduced for dc/dc conversion section. Power factor correction and dc/dc conversion are performed employing a simplistic and single controlling system. The output current feeding the LEDs is a high frequency pulsating current. Calculations, simulations and experimental waveforms of a laboratory prototype are presented to confirm the validity of the proposed driver.