javad nikoukar

This paper delves into the meticulous optimization of distributed energy resources and their storage within a conventional microgrid framework. The optimization endeavor leverages an array of cutting-edge technologies including photovoltaic, wind, fuel cells, micro-turbines, and batteries, with the dual objectives of curtailing operational expenses and fortifying system reliability. To attain these objectives, the article employs a refined algorithm derived from the Grey Wolf Optimization technique. Furthermore, simulations are executed under two distinct scenarios. In the first scenario, the presumption is that all distributed energy resources within the microgrid are exploitable, whereas in the second scenario, spatial constraints necessitate the exclusion of photovoltaic and wind turbine resources. Simulation outcomes evince that post-implementation of energy management via metaheuristic algorithms, there is a discernible reduction in the operational costs of the microgrid alongside an enhancement in system reliability. Additionally, the elimination of photovoltaic and wind resources results in escalated costs and grid blackout within the microgrid. In summary, the simulation findings affirm the superior efficacy of the proposed modified Grey Wolf algorithm in addressing energy management quandaries in comparison to the Particle Swarm Optimization algorithm.

This paper introduces and discusses a new control strategy for nonholonomic wheeled mobile robots (WMR). Robot models include kinematic and dynamic equations of motion. A barrier function adaptive terminal sliding mode control is used to control the movement of the robot. It considers sliding mode control (SMC) to deal with the dynamic model uncertainties of the chaos system, and uses a combination of SMC with an adaptive control approach to solve the upper boundaries problem of unknown model uncertainties and their estimation. Chattering is completely eliminated without over estimating the control gains by adopting an adaptive continuous barrier function in the dynamic switching function. Using the Lyapunov's stability theory, it was shown that the proposed scheme can guarantee the convergence of system states to the vicinity of the sliding surface in finite time. Additionally, the adoption of a sliding surface with a nonlinear and integral switching function resulted in removing the reaching phase of the sliding surface and yielding a controller that is robust to uncertainties from the start. The effectiveness of the proposed control method was assessed using three scenarios implemented to a Liu's uncertain chaotic system in MATLAB/Simulink environment. The obtained results confirmed the ability of the proposed approach to achieve continuous and smooth control rules for such chaotic systems. Among the main attributes of the proposed control method are its ability to completely eliminate chattering and yield a robust performance against model uncertainties and unknown external disturbances.

Dynamic production power planning to meet hourly load demand is one of the important issues in production management and operation of power systems. In this article, the problem of optimal load dispatch considering transmission network losses, considerations and practical limitations of thermal power plants such as increasing and decreasing ramp rates, prohibited production areas, steam valve effect with the combination of renewable resources including wind farms and solar units has been raised. Renewable energy sources have reduced environmental pollution due to the non-use of fossil fuels, but these sources have uncertainty and random nature in production. On the other hand, wind and solar sources are considered to be part of fast start-up sources and thermal sources are considered to be part of slow start-up thermal sources. Considering the mentioned cases together complicates the problem of optimal load distribution, in this article, a new method based on the sine-cosine algorithm is used to determine the contribution of different production sources in the load supply. To solve this problem, which has non-convex cost functions, a new method based on the sine-cosine algorithm has been used. In order to evaluation the effectiveness of the proposed method, simulation results and numerical studies on a sample system including 6 thermal units, 5 wind units and 13 solar units have been implemented and compared with other metaheuristic algorithms. The results of numerical studies show the superiority of the proposed method over other methods while having the appropriate speed and accuracy.

In traditional generation systems, about 25% of energy is wasted, and the presence of distributed energy resources (DER) such as photovoltaic, wind turbines, fuel cell, and the combined heat and power can reduce fuel consumption, pollution, and transmission losses. In this paper, a complete energy management framework in a microgrid is proposed by considering the constraints using Improved Shuffled Frog Leaping Algorithm, in which the exact share of energy production for different units is determined. The proposed scheme is used to select the best arrangement of DERs in the microgrid, the output of which is to determine the number and optimal location of DERs in several bus-bars. Then, the independent system operator determines the quantity of energy exchange and consumption by considering load distribution constraints. Boilers and CHPs have also been used to maintain the balance between the production of thermal power by energy sources and thermal demands. In addition, the Demand Response Program has been used with the aim of smoothing the load curve and of reducing the operating costs. Finally, the proposed method has been implemented and simulated using MATLAB software on a two standards 69-and- 118-bus IEEE system. The comparison of the results with other algorithms showed the accuracy and superiority of the proposed method from the point of view of reducing operating costs.

In addition to the many advantages of Distributed Generation (DG) for the distribution networks, they change the direction and increase the level of fault current. These changes may cause the loss of protection coordination of reclosers and fuses in distribution networks. Usually, the operation time of reclosers is determined by two main settings, TDS and IP, but two other parameters (A and B), which are defined by the standards of traditional reclosers, are also influential on the operation time of reclosers. These two parameters can be modified in digital reclosers. In this article, these two characteristics are optimized with TDS and IP to restore protection coordination. For this purpose, first, the location and the size of the DGs are specified, after that to alleviate the effects of the DGs, the location and the impedance of FCLs are optimized by a multi-objective optimization function to reduce the loss, improve voltage profile, and reduce the effects of changes in the feeders’ fault current while DGs are connected to the distribution network. Then, to restore the protection coordination, and to reduce the operating time of the protection equipment, fuse, and recloser, the parameters A, B, TDS, and IP are optimized using a multi-function optimization. To validate the proposed approach, the IEEE 33-bus network in the presence of synchronous DGs and resistive SFCL has been simulated in DIgSILENT software.

In this paper, we investigate a hybrid controller for wheeled mobile robots in the presence of external disturbances and parametric uncertainty. Robot models include kinematic and dynamic equations of motion. In this paper, in order to reach the final position, the wheeled moving robot must be controlled in such a way that it can follow a reference path. Many studies often use a motion control strategy for the wheeled mobile robot. In this study, the proposed control strategy has two stages including cinematic control and dynamic control. In this regard, first after introducing the kinematic model of the robot, we design a predictive controller for this part and prove it. Then, based on the nonlinear dynamic dynamics of the robot, an adaptive sliding mode dynamic controller is introduced to estimate the disturbances online, automatically adjust the gain of the control and eliminate the umbrella phenomenon completely. Then, the proposed design is analyzed and proved using Lyapanov's theory of stability. According to the proposed adaptive control law, optimal convergence and tracking performance of all signals are guaranteed and tracking errors can converge arbitrarily in finite time to the source. Simulation results have been performed to show the effectiveness of the proposed design using Matlab software.

Transmission lines and transformers are the most important equipment of a power network, the outage of which can lead to cascading failure. This paper tries to identify those lines or transformers that cannot be prevented from being overloaded by operations such as load shedding or production decrease through considering a model of cascade outage simulation. Also, one of the risk assessment methods, called Failure Modes and Effects Analysis (FMEA) method, is used to identify the critical network lines and transformers known as initial events of cascading failures. This method through the evaluation of three criteria ofseverity, occurrence, and detection assesses and categorizes the risk priority number (RPN) of the combination of possible N-K (1). The proposed method was implemented in the IEEE 39-bus test system, and its results showed its accuracy compared to the other methods.

Cascading failures are one of the most destructive states in the power systems, which may initially start with a small error and then spread with a chain effect like a domino, leading to large-scale blackouts. Therefore, it is necessary to prevent cascading failures, because our daily lives depend heavily on a stable and reliable power supply network. So far different methods have been proposed to identify the initial events of cascade failures, including fault-prone lines and transformers, with the aim of taking remedial action scheme to reduce the adverse effects of cascade failure. In this paper, several well-known methods with the potential to detect initial events that lead to catastrophic cascading failures are first implemented of the IEEE 39-bus test system and the Competencies and shortcomings of methods are compared. In the following, a new method is presented with appropriate speed and accuracy compared to other methods. The enumeration method based on William Fine risk assessment technique is used to validate the results of different methods. The enumeration method is a difficult and time-consuming method. Therefore, in order to reduce the dimensions of the mentioned method in order to validate the methods more appropriately and faster, the William Fine risk assessment technique is used. This technique identifies and ranks the potential and effective initial events in creating the chain of cascading failures in the power system by calculating the risk assessment score of combinations of possible N-K(1<K≤3) contingencies.

In this paper, reference path tracking based on terminal slip mode control for a wheeled mobile robot is presented and the proposed method is practically simulated on a mobile robot. The wheeled actuator is a nonlinear system with two inputs for controlling and three state variables and a nonlinear constraint. To control this system in this paper, first by converting the equations of the non-holonomic system into a chain form, the equations of a wheeled mobile robot are extracted for generalized chain equations. Then the limited time terminal sliding model control method is presented to control the reference path tracking of this system. It could be run using a graphical simulation environment in MATLAB software. The proposed method for the wheeled mobile robot used in the laboratory is simulated. The simulation results in the graphical environment show the efficiency of the proposed method in comparison with the classical sliding mode control method. Finally, the practical results of the controller simulation to follow the reference path provided on the mobile robot are shown. The results of the practical simulation show well the proper performance of the proposed method.

In this paper, the protection coordination for Digital dual-setting directional overcurrent relays (DS-DOCR) in the presence of renewable energy sources and energy storage system in the conditions of maximum and minimum fault current in the distribution network is investigated. The proposed scheme minimizes the total operating time of the relays to achieve fast protection coordination in DS-DOCR relays. In addition, to increase the flexibility in the DS-DOCR settings, the permitted range for all relay parameters such as A, B, pickup current (IP), and time dial setting (TDS) is explained in both forward and backward directions. In the proposed scheme, the operating results of DS-DOCR relays on the IEEE 9-bus distribution network in the presence of maximum penetration of photovoltaic sources (PV), wind and energy storage systems (ESSs), in maximum and minimum fault current conditions are investigated. Simulation of the study method is done in DIgSILENT Power Factory software. The numerical results indicate that the proposed solution algorithm has ideally provided the optimal values ​​of the DS-DOCR relays setting parameters, and is capable of achieving reliable and fast protection coordination.

Recently, Combined Heat and Power (CHP) systems have been utilized increasingly in power systems. With the addition penetration of CHP-based co-generation of electricity and heat, the determination of economic dispatch of power and heat becomes a more complex and challenging issue. The optimal operation of CHP-based systems is inherently a nonlinear and non-convex optimization problem with a lot of local optimal solutions. In this paper, the Improved Shuffled Frog Leaping Algorithm (ISFLA) is used for solution of the problem. ISFLA is an improved version of shuffled frog leaping algorithm in which new solutions are produced in respect to global best solution. The ISFLA is well able to attain the optimal solutions even in the case of non-convex optimization problems. To evaluate the efficiency of the proposed method, it has been implemented on the standard test system. The obtained results have been compared with other heuristic methods. The numerical results show that the ISFLA is faster and more precise than other methods.

This paper presents the system stability-constrianted optimal protection coordination (SSCOPC) as stochastic problem in the microgrid with grid-connected and islanded operation modes, including renewable energy sources (RESs) and energy storage systems (ESSs). To regulate optimally the dual setting overcurrent relays (DSORs) and to selectin the reactance size of fault current limiter (FCL), the system minimizes the total relays operation time in the primary and backup protection modes. Also, it is subject to the limits of the coordination time interval (CTI), DSORs setting parameters, FCL size, and microgrid stability in the fault condition. Generally, the microgrid includes RESs and ESSs; thus, the proposed SSCOPC needs a daily operation of microgrid as stochastic model to calculate network variables before fault occurrence. Hence, s this situation minimizes the microgrid operation cost and load shedding cost of islanded microgid which are subjected to optimal power flow equations in the presence of RESs and ESSswhile considering the uncertainty of the load and its generation. Therefore, by applying the proposed problem on the 9 and 32 bus microgrid, solving the problem by the Crow Search Algorithm (CSA), and selecting optimal size of RESs and ESSs, based on operation and protection coordination indices, the proposed SSCOPC can obtain a fast protection solution that considers system stability in faulty conditions.

Due to the progress of renewable energy technologies and the intention of energy policymakers to use these clean and cheap resources, many studies have focused on ways to take advantage of these energies. Limitations, such as low capacity, output power uncertainty, and sustainability problems, make the use of distributed energy resources costly and difficult. Among distributed generation resources, renewable energy resources such as wind energy and solar energy are more environmentally friendly and are used more than other technologies. Despite the many advantages of these resources, their output power depends on such factors as wind speed and solar intensity, which cannot be accurately predicted. For this reason, the infiltration[MSH1]  of high levels of these resources into power systems increases system uncertainty and can reduce reliability while system reliability is very important for power system designers and operators, as well as energy consumers. To solve these problems, a new concept, named virtual power plant, is proposed. A virtual power plant is a collection of distributed energy resources that come together to participate in the market. Virtual power plants can efficiently coordinate, aggregate, and manage different distributed energy resources such as distributed generation, energy storage systems, and controllable loads. These plants are flexible agents for a range of distributed energy sources that can be used in wholesale markets to provide services to system operators. The energy management system is the heart of a virtual power plant that coordinates the flow of power from generators, controllable loads, and energy storage devices. This paper proposes a full model for optimal planning of a virtual power plant if uncertainties of distributed generation sources such as wind and solar energy, as well as electrical vehicles, are considered. To prevent the negative effects of the presence of electric vehicles on electricity networks, especially in virtual power plants, it is necessary to charge these vehicles in a controlled manner and with careful planning. In addition, the demand response whose modeling is based on price-based demand response for non-users and encouragement-based for electric vehicles is optimized on two scenarios, and a 32-bus network is studied. The main goal of the research is to maximize the profit of the virtual power plant for the simultaneous use of load response and electric vehicles with the capability of connecting to the grid.

Due to the ever-growing load, especially peak load, the increase in the capacity of plants is inevitable for the response to this growth. Peak load causes increases in customer costs and vast investments in generating and transmission parts. Therefore, restructuring in the electrical industry, competition in the electrical market and Demand Response Programs (DRPs) are of special importance in power systems. In DRPs, customers in certain periods, such as peak or times when the price is high, decrease self-consumption. It means profit for costumers and prevention of expensive production in peak time for a genera-tion source. Moreover, to decrease the operation cost of network and ever-growing technology significantly, the power sys-tems operators have employed new sources of energy production as well as thermal units, and it has led to the emergence of Electric Vehicles (EVs) technology as a new source of energy production. This paper studies the simultaneous presence of DRPs and EVs to minimize the total operation cost of a network from one hand and from the other to improve the level of system reserve in Unit Commitment (UC) problem with considering the security constraint. Here, the proposed framework is structured as a Mixed Integer Programming (MIP) and solved using CPLEX solver.

Reactive power as a utility of ancillary service in restructured environment is supplied by Independent System Operator (ISO). Due to the particular importance of optimal pricing strategy in the power market, the study aims to investigate this problem more closely. To this end, first the problems of restructuring, reactive power generation and its associated costs thereof were reviewed and different types of transmission rights identified. Next, an algorithm was proposed as the selected method for reactive power pricing in terms of Fina g simultaneous Opportunity Cost (OC) at power plants. The pricing method was based on the respective marginal costs as ncial Transmission Rights (FTR) of transmission lines in the presence of the hybrid market model (spot and bilateral) usin well as the optimal power flow and implemented the succession planning method via MATLAB for IEEE 57-buses test system. Comparison of the results obtained from the proposed method (where in capacitors and Static VAR Compensator (SVC) were considered as reactive power generation sources) with those of the current pricing method used in the Iran power grid showed increased earnings due to reactive power investment.