Standard IEEE-30 Bus Research Articles

Rule-Based Detection of False Data Injections Attacks against Optimal Power Flow in Power Systems.

Cyber-security of modern power systems has captured a significant interest. The vulnerabilities in the cyber infrastructure of the power systems provide an avenue for adversaries to launch cyber attacks. An example of such cyber attacks is False Data Injection Attacks (FDIA). The main contribution of this paper is to analyze the impact of FDIA on the cost of power generation and the physical component of the power systems. Furthermore, We introduce a new FDIA strategy that intends to maximize the cost of power generation. The viability of the attack is shown using simulations on the standard IEEE bus systems using the MATPOWER MATLAB package. We used the genetic algorithm (GA), simulated annealing (SA) algorithm, tabu search (TS), and particle swarm optimization (PSO) to find the suitable attack targets and execute FDIA in the power systems. The proposed FDIA increases the generation cost by up to 15.6%, 45.1%, 60.12%, and 74.02% on the 6-bus, 9-bus, 30-bus, and 118-bus systems, respectively. Finally, a rule-based FDIA detection and prevention mechanism is proposed to mitigate such attacks on power systems.

Power flow control of power systems based on a simple TCSC model

Thyristor-Controlled Series Capacitor (TCSC) is used to control the active power flow in transmission lines in the power system to specific values. This paper proposes a simple modeling of TCSC into Newton-Raphson load flow algorithm in order to reduce the complexity and enhance the reusability of the original load flow code. TCSC is represented by two injected loads at the sending and auxiliary buses. These loads are calculated based on the specified active power while the reactive power is calculated based on the systems. The reactive loads are updated during the iterative process until the convergence is achieved. TCSC parameters are calculated based on the voltages of connected buses and the specified active power. This model solves the problem associated with the selection of proper initial values of the TCSC control parameter. The proposed TCSC model is validated using the standard IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test systems.

Optimal Reconfiguration in Distribution Systems with Distributed Generations Based on Modified Sequential Switch Opening and Exchange

The distribution systems operate radially with meshed topologies thanks to tie-switches and sectionalizing switches consisting of the systems. The power distribution systems are undergoing evolutions strongly toward active distribution systems for reliability and quality of service enhancements through reconfiguration. The distributed generations are also one effective solution for the above objectives. A consumption time is one of the considerable issues that many existing methods have not been achieved for reconfiguration purpose. This paper brings an adaptive solution called modified sequential switch opening and exchange (MSSOE), which is carried out with MATLAB and MATPOWER tool, to overcome these issues. The fundamental loop has been proposed for the MSSOE method to reduce search space in the iteration process. In each step of the searching process, MSSOE observes that if any switches within the same loop of the selected tie-switch are deleted to avoid opening those switches in the next iteration. The process of MSSOE is done when the radial topology is given. The proposed method is tested with the standard IEEE 33-bus, IEEE 69-bus, and IEEE 119-bus distribution systems to observe the effectiveness of the MSSOE algorithm. Comparison to existing algorithms in terms of global solution and computation time conclude that the MSSOE is the best method.

Probability box theory-based uncertain power flow calculation for power system with wind power

Abstract The uncertainty of wind speed may lead to the deviation and change of wind power output, which influences the stability of wind farm. Therefore, in this paper, a probability box (p-box) based uncertain power flow model for wind power is proposed, which initially introduces p-box to power flow calculation. A probabilistic interval power flow model with both probability and interval is established. Firstly, the drift interval of wind speed is obtained and its p-box model is established by analyzing the distribution of wind speed. Secondly, the wind power output p-box is derived from the wind speed p-box based on the relationship between wind power output and wind speed, then the p-box of wind power output is discretized and introduced into the power flow equation to obtain the power flow p-box model. Finally, Newton–Raphson method is used to solve the power flow p-box model. Experiments on data collected from a wind farm (running standard IEEE30-bus test system) in Inner Mongolia demonstrate that our method is more effective and accurate than the traditional Monte Carlo simulation (MCS) and classical interval power flow (IPF) method.

Reactive Power Optimization of Power System Based on Improved Differential Evolution Algorithm

This paper presents a novel differential evolution (DE) algorithm, with its improved version (IDE) for the benchmark functions and the optimal reactive power dispatch (ORPD) problem. Minimization of the total active power loss is usually considered as the objective function of the ORPD problem. The constraints involved are generators, transformers tapings, shunt reactors, and other reactive power sources. The aim of this study is to discover the best vector of control variables to minimize power loss, under the premise of considering the constraints system. In the proposed IDE, a new initialization strategy is developed to construct the initial population for guaranteeing its quality and simultaneously maintaining its diversity. In addition, to enhance the convergence characteristic of the original DE, two kinds of self-adaptive adjustment strategies are employed to update the scaling factor and the crossover factor, respectively, in which the detailed information about the two factors can be exchanged for each generation dynamically. Numerical applications of different cases are carried out on several benchmark functions and two standard IEEE systems, i.e., 14-bus and 30-bus test systems. The results achieved by using the proposed IDE, compared with other optimization algorithms, are discussed and analyzed in detail. The obtained results demonstrated that the proposed IDE can successfully be used to deal with the ORPD problem.

Stochastic Modeling of a DFIG Wind Turbine in Matpower

One of the main trends in the electric power industry is the use of green energy – renewable energy sources (RES), especially wind power generation. The penetration of large wind turbine (WT) power capacity leads to changes in the topology and characteristics of electric power systems (EPS), which can cause an increase the likelihood of emergency processes and a decrease in the steady-state and transient EPS stability. The issue arises in ensuring the EPS stability with RES units, especially in the case of large disturbances. The main way to solve this issue is mathematical modeling. However, almost all the main currently used software programs are based on deterministic methods for calculating EPS processes, which are not able to consider all possible state uncertainties. To reliably determine all possible states of the system in which it can be, it is necessary to determine in a non-deterministic form how the values in the nodes and branches will be distributed. The peculiarity of this paper is associated with the use of a set of approaches to increase the accuracy of the results obtained: the approximation method in combination with two goodness-of-fit criteria for wind; the SIBD method, which generates the required probability density without loss of density values; and the controlled discretization of input variables. This paper assumes the formation of a WT stochastic model to study the impact of RES on stability in a non-deterministic form using the example of IEEE standard bus systems in the Matpower program.

Multi-objective Optimization of Combined Economic Emission Dispatch Problem in Solar PV Energy Using Hybrid Bat-Crow Search Algorithm

The current paper deals with multi-objective fuel cost optimization of a conventional power plant (CPP) and emission minimization in CPPs and Solar PV Power Plants (SPVPPs) using hybrid Bat-Crow search algorithm. To resolve this complicated, non-convex, and excessively nonlinear problem, a variety of meta-heuristic optimization algorithms are developed and effectively employed. To handle the evolutionary multi-objective algorithms’ inadequacies like early convergences, slowly meeting Pareto-optimal front, and narrow trapping, generally applying a combination of different algorithms is unusual. This paper presents the hybrid evolutionary multi-objective optimization process, which is based on combining the Crow search optimization with the Bat algorithm for dealing with the combined economic emission dispatch (CEED) through SPVPP. A hybrid technique combined with the proposed constriction handling method can balance out exploitation and exploration tasks. Different IEEE standard bus systems were tested with the proposed hybrid method using the quadratic cost function and monitoring the transmission losses. The result of proposed algorithm is compared with Bat, PSO and Crow Search Algorithm. The proposed method can be effective with the simulation results.

Adequate Operation of Hybrid AC/MT-HVDC Power Systems Using an Improved Multi- Objective Marine Predators Optimizer

This paper presents an Improved Multi-Objective Marine Predators Optimizer (IMMPO) for optimal operation of hybrid AC and multi-terminal-high voltage direct current (AC/MT-HVDC) power systems. The proposed IMMPO incorporates an external repository to conserve the non-dominated preys. Furthermore, fuzzy decision making is employed to select the best compromise operating point for the hybrid AC/HVDC power systems. In these systems, the active and reactive power controllability of the voltage source converters (VSCs) are activated besides the full control in AC grids via the committed generators, transformer tap settings and VAR compensations. The modelling of the VSC losses is integrated in its quadratic function of the converter current. The optimal operation of AC/MT-HVDC power systems is handled as a multi-objective problem for minimizing the total fuel costs, the environmental emissions of the generation units and the total losses over the AC, HVDC transmission lines and VSCs stations. For solving this problem, several recent optimization algorithms are applied on a modified standard IEEE 30-bus. Also, a real part of the Egyptian West Delta Region Power Network emerged with VSC-HVDC grids is considered as a practical case study. The simulation results demonstrate the effectiveness and preponderance of the proposed algorithm with great stability indices over several competitive algorithms. Nevertheless, the proposed IMMPO is successfully extracting well-diversified Pareto solutions while a compromise operating point is effectively produced to satisfy the operator requirements.

Optimal Placement and Sizing of Capacitors in Radial Distribution Systems: A Two-Stage Method

Optimal allocation of shunt capacitors in the radial distribution networks results in both technical and economic benefits. This paper presents a two-stage method of Loss Sensitivity Factor (LSF) and Cuckoo Search Algorithm (CSA) to find the optimal size and location of shunt capacitors with the objective of minimizing cost due to power loss and reactive power compensation of the distribution networks.
 The first stage utilizes the LSF to predict the potential candidate buses for shunt capacitor placement thereby reducing the search space of the second stage and avoiding unnecessary repetitive load flow while the second stage uses the CSA to find the size and actual placement of the shunt capacitors satisfying the operating constraints.
 The applicability of the proposed two stage method is tested on the standard IEEE 33-bus and Ayepe 34-bus Nigerian radial distribution networks of the Ibadan Electricity Distribution Company. After running the algorithm, the simulation results gave percentage real and reactive power loss reduction of 34.28% and 28.94% as compared to the base case for the IEEE 33-bus system while the percentage real and reactive power loss reduction of 22.89% and 21.40% was recorded for the Ayepe 34-bus system.
 Comparison of the obtained results with other techniques in literatures for the standardized IEEE 33-bus reveals the efficiency of the proposed method as it achieved technical benefits of reduced total power loss, improved voltage profile and bus voltage stability, and the economic benefit of reduced total cost due to electrical power loss and compensation.

A method for power suppliers’ optimal cooperative bidding strategies considering network losses

The bidding strategies of power suppliers to maximize their interests is of great importance. The proposed bi-level optimization model with coalitions of power suppliers takes restraint factors into consideration, such as operating cost reduction, potential cooperation, other competitors’ bidding behavior, and network constraints. The upper model describes the coalition relationship between suppliers, and the lower model represents the independent system operator’s optimization without network loss (WNL) or considering network loss (CNL). Then, a novel algorithm, the evolutionary game theory algorithm (EGA) based on a hybrid particle swarm optimization and improved firefly algorithm (HPSOIFA), is proposed to solve the bi-level optimization model. The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species, with the EGA automatically predicting a plausible adaptation process for the others. Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation. A novel improved firefly algorithm (IFA) is combined with a chaotic sequence theory to escape from the local optimum. In addition, the Shapley value is applied to the profit distribution of power suppliers’ cooperation. The simulation, adopting the standard IEEE-30 bus system, demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem

Enhancing power system loadability and optimal load shedding based on TCSC allocation using improved moth flame optimization algorithm

The power systems become operate closer to loadability limits; hence, the power systems static voltage stability assessment becomes an essential task in planning and operating for electric power systems to prevent voltage instability. In this paper, the improved moth flame optimization (IMFO) technique is applied for optimal location and size of (TCSC) with the aim of reducing load shedding, preventing voltage collapse, and enhancing the power system loadability. IMFO is developed to avoid the stagnating in local optima and improve the convergence characteristics of the conventional moth flame optimization. The loadability of the system is obtained using continuation power flow (CPF). The proposed approach is formulated by merging CPF with IMFO incorporated with TCSC. Multi-objective function is solved for minimization of loadability, load shedding, voltage stability index, and severity index. A contingency analysis is implemented on power system as two scenarios: The first scenario is outage of generator and the second scenario is outage line. Placement of TCSC has been determined by power flow analysis. The developed approach is tested on standard IEEE-30 bus system in normal operation, and contingency cases of generator and bus outage. The IMFO is compared to recent and well-known optimization techniques. The results reveal the efficiency of the proposed algorithm to reduce load shedding, continuous energy service to the customers and prevent occurrence of voltage collapse.

Optimal Placement and Sizing of Shunt Capacitors in Radial Distribution System Using Polar Bear Optimization Algorithm

Reduction in power loss while maintaining the acceptable voltage profile has become a challenge for distribution system operators due to expanded living standards. Properly sized shunt capacitors (SCs) allocated at suitable locations of the distribution system can enhance its performance by tackling the power quality issues and foster multiple technical and economic benefits. Most of the existing research work in this domain is accomplished at fixed loading conditions without incorporating purchasing, installation, operation and degradation costs of the SCs. In this work, an intelligent metaheuristic polar bear optimization algorithm (PBOA) is applied to solve the optimal capacitor placement and sizing problem in the radial distribution system (RDS) at various loading conditions. By formulating multiple objective functions for the annual operating cost (AOC), this work incorporates the cost of real power loss ( $$ P_{\text{loss}} $$ ) and various costs associated with SCs. The proposed technique is tested on various IEEE standard bus systems under different loading conditions. The proposed PBOA reduces AOC and $$ P_{\text{loss}} $$ of RDS while maintaining tolerable voltages at systems’ buses. The reductions of 51%, 35%, 26% and 53% in $$ P_{\text{loss}} $$ are observed for IEEE standard 15-, 33-, 34- and 85-bus systems, respectively, at 100% loading from their uncompensated cases. Similarly, reductions in AOCs for the same systems at 100% loading are 32%, 25%, 16% and 45%, respectively. These results prove superiority of proposed method over recent state-of-the-art algorithmic approaches. The results of this work can be useful for distribution system operators in achieving reliable and efficient operation of the power grid.

Transmission Security Enhancement under (N−1) Contingency Conditions with Optimal Unified Power Flow Controller and Renewable Energy Sources Generation

Transmission system security management under (N−1) line contingency is one of the typical and essential tasks in power system operation and control. This paper examines the impact of the optimal unified power flow controller (OUPFC) and renewable energy sources (RES) on the severity of (n−1) line contingency on transmission system security. To test the performance of OUPFC device under single line contingency conditions, an optimal power flow (OPF) based multi-objective function is formulated using real power loss and line collapse proximity indicator (LCPI). Primarily, the optimal location of the OUPFC is determined using LCPI index and then (n−1) contingency analysis is performed by considering OUPFC device at different RES generation levels. Here, the control variables of OUPFC, tap-changers, VAr injections, output power of conventional energy sources (CES), bus voltages and bus angles are optimized with two different variants of the cuckoo search algorithm (CSA) namely (1) dynamically increasing switching parameter in power of three (CSA1) and (2) exponentially increasing switching parameter (CSA2). The simulation results of various case studies on a standard IEEE-30 bus test system have shown the superiority of CSA2 in solving the multi-objective, non–linear complex optimization problem over CSA1 and time-varying acceleration coefficient-particle swarm optimization (TVAC-PSO). Also, the ability of OUPFC for managing the impact of (n−1) line contingency and variable RES generation is shown in terms of decreased real power loss, improved voltage profile and enhanced security margin.

Optimal PV Size and Location to Reduce Active Power Losses While Achieving Very High Penetration Level With Improvement in Voltage Profile Using Modified Jaya Algorithm

In this article, a new multiobjective algorithm is proposed for determining the optimal sizing and allocation of the photovoltaic (PV) systems in radial distribution systems. A Jaya algorithm is modified to find the optimal PV capacities for limited bus locations at the network. The proposed algorithm showed better performance against known techniques, and the results are presented. Besides, a new distinguished methodology is improved and developed based on the Jaya Algorithm to find the optimum capacity of each PV system that satisfies an improvement of the voltage profile and reduces power losses under high penetration levels. Also, optimum capacities are determined by considering the connection of the PV systems for all buses along with the network. Furthermore, the proposed method is verified on the standard IEEE-33 bus test system with high penetration rates. Simulation and validation are obtained by MATPOWER and OCTAVE software.

Vulnerability Assessment of Power Grids Against Link-Based Attacks

In modern power grids, a local failure or attack can trigger catastrophic cascading failures, which makes it challenging to assess the attack vulnerability of power grids. In this brief, we define the optimal $K$ -link attack problem and study the attack vulnerability of power grids in cascading failures. We propose a link centrality measure based on both topological and electrical properties for power grids. According to this centrality measure, we propose a greedy attack algorithm and an optimal attack algorithm. Simulation results based on standard IEEE bus test data show that the optimal attack is better than the greedy attack and the traditional PSO-based attack in fracturing power grids. Moreover, the greedy attack has an adequate attack efficiency with a smaller computational cost. This brief aids in understanding the vulnerability of power grids and provides clues for securing power grids.

Potential Drop Analysis of a Radial Distribution System with Various Loads

At present the green environment plays a crucial part in fighting against the global warming. The Electric Vehicles which are eco-friendly provides the solution for these environmental issues which promotes low carbon emission. In the present scenario variation of the power flow and voltage profile at specific nodal junctions in a radial distribution system, when Electric Vehicle has been connected as a load is essential This paper shows the potential drop analysis on a distribution system with Electric Vehicle as a load. The results provide the total real power loss, total reactive power loss occurs in the radial test bus system and the voltage magnitude at nodes for an IEEE standard bus system. The Backward/Forward sweep method has been implemented on IEEE test bus radial distribution system. Various types of loads such as residential, commercial, and industrial with Electric Vehicles are considered for testing. The results indicate that a drop in voltage when Electric Vehicles has been integrated into the grid along with other consumers. The programming results has been compared with standard values and found to be satisfactory. Suggestions’ for improving the voltage profile had also included in this paper.

MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING DIFFERENTIAL EVOLUTION

Reactive power optimization is a major concern in the operation and control of power systems. In this paper a new multi-objective differential evolution method is employed to optimize the reactive power dispatch problem. It is the mixed–integer non linear optimization problem with continuous and discrete control variables such as generator terminal voltages, tap position of transformers and reactive power sources. The optimal VAR dispatch problem is developed as a nonlinear constrained multi objective optimization problem where the real power loss and fuel cost are to be minimized at the same time. A conventional weighted sum method is inflicted to provide the decision maker with a example and accomplishable Pareto-optimal set. This method underlines non-dominated solutions and at the same time asserts diversity in the non-dominated solutions. Thus this technique treats the problem as a true multi-objective optimization problem. The performance of the suggested differential evolution approach has been tested on the standard test system IEEE 30-bus.

Optimal Placement of FACTS Devices Based on Whale Optimization Algorithm for Power System Security Enhancement

The present-day power system is vulnerable to instability and security threats due to the continuously changing load pattern. To enhance the security of the power system and to avoid the electrical power system from collapsing, the condition of the system security has to be inspected by security analysis tools and it can be enhanced by the proper integration of FACTS devices into the network. This paper presents a methodology in which the security of the system can be analyzed with the help of an index called Line Overload Severity Index (LOSI). Unified Power Flow Controller (UPFC) is preferred to improve the security of the power system. Owing to the cost involved in placing UPFCs it is obligatory to use minimum number of devices, by optimally placing them in the network. It is obligatory to recognize an ideal location to install UPFC. Considering the Line overload Sensitivity Index, the optimal location identification for UPFC is done. The paper also presents the formulation of a new severity function using transmission line loadings. The severity function combines the objectives of reducing transmission line loadings and improvement of voltage profile during multi line contingencies. In the event of multi-line contingencies, the objective function for reducing the fuel cost and the severity function are analyzed. Optimal power flow method is followed to analyze the security of the electrical power system during contingency situations. This optimal location identification procedure and the OPF are solved using a metaheuristic technique, Whale Optimization Algorithm (WOA). The whole methodology that is proposed is experimented on a standard IEEE-30 bus test system.

Optimal Power Flow in Uncertain Power System

Due to the increasing demand of electricity in ever-growing electricity market, it is necessary to observe the nature of load and map the effects of load uncertainties on the operation of power system. These uncertainties have also led to voltage instability which is sooner or later considered to be a fundamental cause of blackouts. The distributed generation sources can also be regarded as the source of uncertainties at the load ends of power systems. Along with the load uncertainties, wind turbine generation (WTG) and solar plants have also been used as a source of uncertainties in this paper. The load uncertainties have been incorporated in the system by designing a dynamic load flow program. Corresponding to all uncertain inputs critical case has been identified by the singularity property of load flow jacobian. For the optimal load flow a multi-objective optimization problem aiming to constrained objective function to enhance voltage stability, improve stability index value, reduce system losses and increase reactive reserve margins at generator buses has been formulated. Black hole algorithm has been used to achieve the optimal values of control variables and hence optimal load flow. The aforementioned problem has been tested on standard IEEE-14 bus system.

A Cost Effective Solution to Security Constrained Unit Commitment and Dispatch Problem using Hybrid Search Algorithm

The Security constraints unit commitment (SCUC) is a powerful scheduling technique used in power markets for daily planning. SCUC is a framework that combines two common algorithms in the electricity industry: Unit Commitment (UC) and Economic Dispatch (ED), while adding a new dimension – Security. Load demand is changing continuously due to variation of load of industrial, residential and commercial sectors. Thus, it is very important to decide which generating unit should be kept on and how much power should be dispatched so that time varying load demand can be meet on Hourly basis and there should be no scope of occurrence of loss of load hour (LOLH). In the proposed research, the recently developed hybrid meta-heuristics search algorithm i.e. GWO-RES has been applied to solve the security constrained Unit Commitment and dispatch problem of Electric power system. The efficiency of the proposed hybrid algorithm has been tested for standard IEEE-14 Bus, 30-Bus and 56-bus system and it has been experimentally found that GWO-RES performs much better than hybrid GWO-PS and GWO-RS algorithm.