Considering DG in Expansion Planning of Subtransmission System

Deregulation has been obtained new options in the design and planning of the power system. One of these options is the integration of Distributed Generation (DG) into the power system. In this paper, the presence of distributed generation is regarded as another alternative for supplying the load of subtransmission system. The effects of DG on expansion planning of subtransmission system have been modeled as an  optimization problem where the Genetic Algorithm (GA) and Linear Programming (LP) are employed to solve it. The proposed approach is applied to a realistic subtransmission system and the results are evaluated

FACTS Devices Allocation Using a Novel Dedicated Improved PSO for Optimal Operation of Power System

Flexible AC Transmission Systems (FACTS) controllers with its ability to directly control the power flow can offer great opportunities in modern power system, allowing better and safer operation of transmission network. In this paper, in order to find type, size and location of FACTS devices in a power system a Dedicated Improved Particle Swarm Optimization (DIPSO) algorithm is developed for decreasing the overall costs of power generation and maximizing of profit. Thyristor-Controlled Series Capacitor (TCSC) and Static VAr compensator (SVC) are two types of FACTS devices that are considered to be installed in power network. The purpose of this study is reducing the power generation costs and the costs of FACTS devices with considering different load levels. The main bases of this paper are using of Optimal Power Flow (OPF) and DIPSO algorithm to techno-economical analysis of the system for finding optimal operation. The Net Present Value (NPV) method is used to economic analysis of the system and power losses and maximum possibility load demand are considered for technical analysis. The proposed method is implemented on IEEE 57-bus test system and the achieved results are compared with genetic algorithm and particle swarm optimization methods to illustrate its effectiveness

Optimal Operation Management of Grid-connected Microgrid Using Multi-Objective Group Search Optimization Algorithm

Utilizing distributed generations (DGs) near load points has introduced the concept of microgrid. However, stochastic nature of wind and solar power generation as well as electricity load makes it necessary to utilize an energy management system (EMS) to manage hourly power of microgrid and optimally supply the demand. As a result, this paper utilizes demand response program (DRP) and battery to tackle this difficulty. To do so, an incentive-based DRP has been utilized and the effects of applying DRP on microgrid EMS problem have been studied. The objective functions of microgrid EMS problem include the total cost and emission. These metrics are combined in a multi-objective formulation and solved by the proposed multi-objective group search optimization (MOGSO) algorithm. After obtaining Pareto fronts, the best compromise solution is determined by using fuzzy decision making (FDM) technique. Studies have been employed on a test microgrid composed of a wind turbine, photovoltaic, fuel cell, micro turbine and battery while it is connected to the upper-grid. Simulation results approve the efficiency of the proposed method in hourly operation management of microgrid components

Mini/Micro-Grid Adaptive Voltage and Frequency Stability Enhancement Using Q-learning Mechanism

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

Hierarchy Style Application in Line Extension with Responsive Loads Evaluating the Dynamic Nature of Solar Units

This paper presents a model for line extension scheduled to participate in responsive loads in the power system aiming the improvement of techno-economical parameters. The model is studied with the presence of photovoltaic generators that produce variable power depending on the geographical condition. The investment cost of the transmission expansion plan, demand response operation cost, generation costs and the sum of the voltage deviations are the four indices that the optimization problem is designed based on these four criteria. Objective functions are dynamic variables that change daily due to variation in generation and load. A multi-objective optimization method based on the analytic hierarchy technique is employed to solve the problem. The Pareto-optimal set is extracted with gravitational search style and the best solution is fund by AHT manner. Studies are carried out on the modified 30-bus and 24-bus IEEE test system to confirm the capability of the presented model. Two frameworks are defined to compare the suggested manner. A different amount of PV penetration is discussed in several scenarios. Also, load uncertainty is formulated and involved based on probability distribution function

A Robust Discrete FuzzyP+FuzzyI+FuzzyD Load Frequency Controller for Multi-Source Power System in Restructuring Environment

In this paper a fuzzy logic (FL) based load frequency controller (LFC) called discrete FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) is proposed to ensure the stability of a multi-source power system in restructured environment. The whale optimization algorithm (WOA) is used for optimum designing the proposed control strategy to reduce fuzzy system effort and achieve the best performance of LFC task. Further, to improve the system performance, an interline power flow controller (IPFC) and superconducting magnetic energy system (SMES) is included in the system. Governor dead band, generation rate constraint, and time delay are considered as important physical constraints to get an accurate understanding of LFC task. The performance of the optimized FP+FI+FD controller is evaluated on a two area six-unit hydro-thermal power system under different operating conditions which take place in a deregulated power market and varying system parameters in comparison with the classical fuzzy PID controller. Simulation results shows that WOA based tuned FP+FI+FD based LFC controller are relatively robust and achieve good performance for a wide change in system parameters considering system physical constraints

Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response

The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based on the intelligent algorithm is proposed to optimal operate the demand side management in the presence of DG units and demand response. Firstly, the best location and capacity of different technologies of DG are selected by optimizing the technical index including the active and reactive loss and the voltage profile. Secondly, the daily performance of multi-DG and grid is optimized with and without considering the demand response. The economic and environmental indices are optimized in this step. In both steps, the non-dominated sorting firefly algorithm is utilized to multi-objective optimize the objective functions and then the fuzzy decision-making method is used to select the best result from the Pareto optimal solutions. Finally, the proposed method is implemented on the IEEE 33-bus distribution system and actual 101-bus distribution systems in Khoy-Iran. The obtained numerical results indicate the impact of the proposed method on improving the technical, economic and environmental indices of the distribution system

An Interleaved Configuration of Modified KY Converter with High Conversion Ratio for Renewable Energy Applications; Design, Analysis and Implementation

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

Design of output feedback UPFC controller for damping electromechanical oscillations using

a b s t r a c t In this paper, a novel method for the design of output feedback controller for unified power flow controller (UPFC) is developed. The selection of the output feedback gains for the UPFC controllers is converted to an optimization problem with the time domain-based objective function which is solved by a particle swarm optimization technique (PSO) that has a strong ability to find the most optimistic results. Only local and available state variables are adopted as the input signals of each controller for the decentralized design. Thus, structure of the designed UPFC controller is simple and easy to implement. To ensure the robustness of the proposed stabilizers, the design process takes into account a wide range of operating conditions and system configurations. The effectiveness of the proposed controller for damping low frequency oscillations is tested and demonstrated through nonlinear time-domain simulation and some performance indices studies. The results analysis reveals that the designed PSO-based output feedback UPFC damping controller has an excellent capability in damping power system low frequency oscillations and enhance greatly the dynamic stability of the power systems. Moreover, the system performance analysis under different operating conditions show that the d E based controller is superior to both the m B based controller and conventional power system stablizer

Multi-Stage Fuzzy Load Frequency Control Based on Multi-objective Harmony Search Algorithm in Deregulated Environment

A new Multi-Stage Fuzzy (MSF) controller based on Multi-objective Harmony Search Algorithm (MOHSA) is proposed in this paper to solve the Load Frequency Control (LFC) problem of power systems in deregulated environment. LFC problem are caused by load perturbations, which continuously disturb the normal operation of power system. The objectives of LFC are to mini small size the transient deviations in these variables (area frequency and tie-line power interchange) and to ensure their steady state errors to be zero. In the proposed controller, the signal is tuned online using the knowledge base and fuzzy inference. Also, to reduce the design effort and optimize the fuzzy control system, membership functions are designed automatically by the proposed MOHSA method. Obtained results from the proposed controller are compared with the results of several other LFC controllers. These comparisons demonstrate the superiority and robustness of the proposed strategy