IEEE 33-bus Network Research Articles

Optimal Placement and Sizing of TCSC for Improving the Voltage and Economic Indices of System with Stochastic Load Model

In this paper, an efficient method is proposed for optimal allocation and sizing of Thyristor Controlled Series Compensator (TCSC) to improve the technical and economic indices of a power network with deterministic and stochastic load models. First, the compensator allocation is done in the transmission system with the deterministic load model. After calculating the technical and economic indices of the network in the presence of a deterministic load model, the proposed method is applied to the system with a stochastic load model. The two-point estimation method is used for simulating the stochastic conditions. The indices of voltage deviation and economics of the system are optimized for selecting the optimal location and size of TCSCs. The economic index comprises loss cost, cost of the produced active power of generators and also the costs of installation, operation and maintenance of TCSCs. The multi-objective particle swarm optimization (MOPSO) is utilized to optimize the objective functions. After the multi-objective optimization, the fuzzy decision method is employed to extract one of the Pareto-optimal solutions as the best compromise one. For evaluating the proposed method, comprehensive simulations have been performed on the IEEE 39-bus network by using MATLAB/Matpower software. The simulation results clearly prove the remarkable performance of the proposed method in improving the technical and economic indices of the system.

Power swing detection and blocking of the third zone of distance relays by the combined use of empirical‐mode decomposition and Hilbert transform

This study aimed to develop a new method for detecting power swings and faults that may occur during these swings based on the combined use of empirical-mode decomposition and Hilbert transform. Power swings including line disconnection, fault occurrence, large sudden changes in the demand load, and reclosing, can cause a distance relay to malfunction and sever healthy lines from the network. Therefore, power swings and their simultaneous faults can pose a major challenge to protect the power systems. The proposed method in this study was tested on the standard IEEE 39-bus network for different power swing and fault states. It was also implemented on a distance relay manufactured by Vebko-Amirkabir Co. The evaluations show that the proposed method completely outperforms the conventional industrial method and other available methods in the literature. Since the proper functioning of this method depends on the choice of a threshold value, the current study also provides a simple and practical way to determine this threshold.

Optimization of planning cost of radial distribution networks at different loads with the optimal placement of distribution STATCOM using differential evolution algorithm

This paper presents an optimization of planning of distribution systems with the allocation of DSTATCOM based on maximization of a net cost profit/savings analysis approach by using the differential evolution algorithm. In the proposed approach, the optimal placement of DSTATCOM, and reactive power compensation at a certain location, and the improvement of voltage profile are obtained by three objective functions: (1) minimization of the size of DSTATCOM, (2) minimization of network power loss, and (3) maximization of net cost profit/savings by minimizing the total planning cost of DSTATCOM installation scheme. Present worth factor is adopted to evaluate the net cost profit/savings of the DSTATCOM installation scheme for a certain planning horizon. The appropriate mathematical modeling of DSTATCOM is used to incorporate it suitably in the forward–backward sweep load flow algorithm of radial distribution networks to provide the reactive power compensation. The recommended method is validated on the IEEE 30-bus, 33-bus and 69-bus distribution networks.

Optimal Allocation of UPFC and IPFC in Network Considering Sensitivity of Line Flows under Single Line Contingency

This paper presents, optimal location for deployment of Unified Power Flow Controller (UPFC) and Interline Power Flow Controller (IPFC) in network considering sensitivity of line flows under single contingency. A sensitive approach is proposed which is considered based on Ranking Index (RI) and Performance Index (PI). A unitary change of power flow (PF) in each transmission line after outage of a branch element can be obtained from proposed index. The proposed Index is used to quantify loading level of network after a given outage. Contingencies are structured in descending order depending on value of proposed Index. Sensitivity factors are obtained by differentiating PF indices subject to parameters of UPFC and IPFC devices. Optimal deployment of UPFC and IPFC device is considered by the value of sensitivity factors attained by considering line outages in order of their severities which is given by proposed Index. The efficacy of proposed approach is computed and programmed on 5bus and IEEE 14bus networks under MATLAB environment.

Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm

The integration of network reconfiguration and distributed generation (DG) can enhance the performances of overall networks. Thus, proper sizing and siting of DG need to be determined, otherwise it will cause degradation in system performance. However, determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space. This search space mostly contains non-radial network configurations. Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution. To reduce the searching complexity, this paper considers the discretized network reconfiguration via dataset approach. Water cycle algorithm (WCA) is used to obtain the near optimal solution of network reconfiguration, and sizing and sitting of DG. In addition, the power factor of DG is also optimized to reduce the power loss. The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor. The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima. The proposed method outperforms other technique such as harmony search algorithm (HSA), fireworks algorithm (FWA), Cuckoo search algorithm (CSA) and uniform voltage distribution based constructive algorithm (UVDA) and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20% and 27.88%, respectively.

Optimal reactive power dispatch using θ-social mimic optimization (θ-SMO)

The social mimic optimization algorithm (SMO) and its enhanced version (θ-SMO) is presented in the current study for the optimal dispatch problem of the reactive power (ORPD) with continuous and discrete control variables in the IEEE standard networks. The feasibleness and functioning of the θ-SMO and SMO algorithms are indicated for the IEEE 57-bus, and IEEE 118-bus standard networks. The outcomes of the simulation were compared, and it was shown that the optimization efficacy of these algorithms is higher than other rooted algorithms, such as optics in-spired optimization (OIO), the social spider algorithm (SSA) algorithm, and biogeography-based optimization (BBO). Results obtained for ORPD problem indicate better performance concerning the θ-SMO algorithm’s solution quality compared to original SMO algorithm and other algorithms.

Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm

Aiming to improve the operation economy and power quality of distribution systems subject to the fluctuating and stochastic power outputs of distributed generation (DG) units and electric vehicles (EVs), a multiobjective optimization model for network reconfiguration and its corresponding solution method are proposed. First, a dynamic reconfiguration model is constructed based on the power loss rate (PLR) as well as the active power loss, the load balancing index and the maximum node voltage deviation, which serve as the optimization indexes. Second, the Levy flight and chaos disturbed beetle antennae search (LDBAS) algorithm is presented based on the grey target decision-making technique, which can not only improve the computational efficiency but also find the most satisfactory solution for the proposed dynamic reconfiguration model. Considering the uncertainties of loads and DG outputs, the influence on the load curve of EV connecting to the distribution network at different penetration rates and under different charging/discharging modes is analysed. Additionally, the modified IEEE 33-bus and 118-bus test radial distribution networks are simulated to verify the effectiveness and superiority of the presented reconfiguration model and the improved LDBAS method, and the results illustrate that the proposed reconfiguration method can improve the operation economy and power quality of the distribution system and encourage the penetration of EVs.

A two-layer model to dispatch electric vehicles and wind power

In this paper, the optimal charging and discharging schedules of electric vehicle (EV) are studied considering wind power under the condition of distribution network. In view of the uncertainty of EV charging-discharging demand and wind power output, the Markov decision process is adopted to model the randomness of supply and demand. Considering the dimensional disaster caused by dispatching a large number of EVs’ charging and discharging behavior in a centralized way, this paper proposes the two-layer dispatching model based on Markov decision process. First, the lower EV agents are responsible for collecting the real-time charging-discharging demands for EV and report to the upper dispatching center. Then the upper dispatching center gives the optimal charging and discharging power according to the real-time distribution operating status, wind power output and the EV information reported by each EV agent. Last, the lower agent gives the optimal charging-discharging sequence of each EV according to the upper optimal power. The goal of the upper dispatching center considers the power losses in the distribution network, load variance and the matching degree between EV charging-discharging and wind power output. The goal of the lower EV agent considers the EV charging-discharging fees and costs by EV battery losses. When deciding the optimal charging strategy, we design the two-layer Rollout algorithm to decide the optimal charging-discharging strategy considering the impact on future strategy decisions by current strategy decisions. Finally, the optimal results under four different strategies are simulated on the IEEE 30-bus distribution network system. The simulation results show that the proposed model and strategy can effectively reduce the distribution network losses and load variance, and greatly improve the utilization rate of wind power. Compared to the cost of uncoordinated EV charging, EV charging-discharging fees and battery loss costs by the proposed strategy have been greatly reduced.

Optimal Sizing and Setting of Distributed Power Condition Controller in Isolated Multi-Microgrid

In the present research, optimal placement and parameter tuning of an improved custom power device called Distributed power condition controller (DPCC) for enhancing the voltage profile and reducing losses in an isolated multi-microgrid (MMG) under critical situations have been investigated. The relative capacity credit of the intermittent renewable sources is typically 25–50 percent. When a critical situation such as generation reduction, DG outage in each MG, overload or line contingency occurs in the MMG, the voltages at some buses fluctuate more than the allowed level and power losses arise which is harmful to vital applications. In this paper, the butterfly optimization algorithm and grasshopper optimization algorithm are suggested to search the optimal placement and parameter tuning of DPCC for enhancing the voltage profile and reducing losses under critical situations. A modified IEEE 33-bus network with four distributed generation is employed to create a sample isolated MMG. Eleven different case studies in seven scenarios are considered to evaluate the high capability of DPCC in regulating voltage and reduce losses. It is found from theory studies and simulation results that optimal placement and parameter tuning of DPCC successfully improve the MMG performance.

Transmission Line Capacity Enhancement with Unified Power Flow Controller Considering Loadability Analysis

This paper proposes transmission line capacity enhancement with optimal location and sizing of UPFC on IEEE 14-bus network. This is necessary because of the increase in load growth with every passing day without an equivalent increase of line capacity which has brought many power systems closer to their stability limit. The dynamic and practical application of this proposed method is achieved by increasing linearly, the loading factor (λ) from 1.25 to 1.50 of the base case value of 1.0 and then, its effect is investigated. In each of the increment, the power flow result is obtained using Newton-Raphson method, while the optimal location and sizing of UPFC are done using Grey Wolf Optimization (GWO) technique. The voltage deviation before and after the installation of the FACTS device is also studied at each load variation. This approach will help the bulk dispatcher of power to plan ahead so as to meet and supply the ever-growing in the demand for adequate and reliable power system as a result of population growth, improved living standards and technological advancement. The efficacy of the proposed method is verified on a standard IEEE 14-bus system. The simulation results show the effectiveness and suitable performance of the proposed methodology at enhancing transmission capacity and deferring or eliminating for transmission line upgrading.

Alleviating the impact of DGs and network operation modes on the protection system

Integration of distributed generations (DGs) into distribution networks leads to a significant change of fault current behaviour in magnitude and direction, causing loss of existing protection settings, as does the network operation in two modes. This study proposes an active protection scheme for digital protection system of medium-voltage distribution network to overcome those drawbacks. The method adds a new feature in the fault current detectable by digital relays and makes the relay settings independent of fault current contribution of DGs and upstream grid. The feature is created by injecting a current with frequency rather than the fundamental frequency only under fault conditions. The relays extract the injected current and ignore the DGs and upstream grid contributions. If the relay settings are determined based on the injected current, the relay can operate with a fixed setting despite the variations of fault current level. As a result of the proposed method, the possibility of connecting DGs and operating network in two modes without any effect on relay settings is provided. The proposed protection scheme does not require communication links. The effectiveness of the proposed method is verified by simulating IEEE 33-bus network in PSCAD/EMTDC software.

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters.

Reduction of non-linear many objectives for coordinated operation of integrated energy systems

This paper establishes a model that considers different types of indices for the coordinated operation of integrated energy systems (IES), such as economic indices, environmental indices, security and stability indices. A many-objective optimization problem (MaOP) is developed to treat each index independently as objectives to participate in the optimization rather than constraints. In order to reduce the dimensionalities of objectives and improve the computing efficiency, a kernel matrix based principal component analysis (KM-PCA) method is proposed to achieve the reduction of non-linear many objectives. In the KM-PCA method, the initial correlation matrix of principal component analysis (PCA) is transformed to a kernel matrix by using the maximum variance unfolding (MVU) method. The KM-PCA aims to generate a smaller set of conflicting objectives with maximum information retention of the original objectives. Simulations studies are conducted on a test IES consisting of a modified IEEE 30-bus electricity network, a 15-node gas network and three distributed district heating and cooling units (DHCs) to verify the effectiveness of the KM-PCA method, and a final solution is selected for the coordinated operation of IES.

An MIP-based model for the deployment of fault indicators and sectionalizing switches in distribution networks

Fault indicators (FIs) and sectionalizing switches (SSs) are of great importance in distribution automation for reliability enhancement and efficiency improvement. However, their types and locations have great effects on the resulting service quality. This paper intends to develop a model for the optimal simultaneous allocation of FIs and SSs in a complex distribution network based on reliability and cost-benefit analyses. Three position matrices are obtained by preprocessing the topology of distribution networks to enable the establishment of the proposed model. Furthermore, a quantification method for the customer interruption duration under different contingencies is constructed to achieve a more precise and practical reliability evaluation. The resultant optimization problem is formulated as a mixed-integer linear programming that can obtain the global optimal solution in a finite number of iterations. An IEEE 33-bus network and a real urban distribution system are used to verify the effectiveness and efficiency of this model. The obtained outcomes show that simultaneously considering the placement of FIs and SSs can expedite the fault location and isolation processes, reduce the overall costs of the system and improve the service reliability.

Investigation of Power Networks and their Patterns by Mathematical methods in order to Voltage Stability Enhancement

Authors in the research paper has considered IEEE 14-bus and 34-bus test network for creation generation and load patterns. This paper aims at analysing the potential impacts that distributed generation (DG) might have on voltage stability of electrical power networks. It is expected that increasing amounts of new generation technologies will be connected to electrical power systems in the near future. Most of these technologies are considerably smaller scale than conventional synchronous generators. In this paper, the impact of DG pattern (size and location of DG) on the voltage stability of two test system is investigated. The simulation methodology is discussed as well. It is found that the effects of DG the voltage stability of a power system strongly depend on the size and location of the distributed generators. The results show that install of DG on the weak bus, improve loadability limit and voltage stability and decrease loss of system. By investigating and reviewing the results of similar patterns in these two systems, the different generation and load patterns impact mechanism of DG units over the behaviour of the systems in terms loadability limit and voltage stability is achieved.

Peer-to-peer electricity market analysis: From variational to Generalized Nash Equilibrium

We consider a network of prosumers involved in peer-to-peer energy exchanges, with differentiation price preferences on the trades with their neighbors, and we analyze two market designs: (i) a centralized market, used as a benchmark, where a global market operator optimizes the flows (trades) between the nodes, local demand and flexibility activation to maximize the system overall social welfare; (ii) a distributed peer-to-peer market design where prosumers in local energy communities optimize selfishly their trades, demand, and flexibility activation. We first characterize the solution of the peer-to-peer market as a Variational Equilibrium and prove that the set of Variational Equilibria coincides with the set of social welfare optimal solutions of market design (i). We give several results that help understanding the structure of the trades at an equilibrium or at the optimum. We characterize the impact of preferences on the network line congestion and renewable energy surplus under both designs. We provide a reduced example for which we give the set of all possible generalized equilibria, which enables to give an approximation of the price of anarchy. We provide a more realistic example which relies on the IEEE 14-bus network, for which we can simulate the trades under different preference prices. Our analysis shows in particular that the preferences have a large impact on the structure of the trades, but that one equilibrium (variational) is optimal. Finally, the learning mechanism needed to reach an equilibrium state in the peer-to-peer market design is discussed together with privacy issues.

Toward a More Reliable System for Contingency Selection in Static Security Analysis of Electric Power Systems

The reliable supply of electricity plays a key role in the contemporary way of life. In order to provide more benefits to the population, electric networks are getting bigger to produce more energy. This growth, while necessary, brings problems in operation and maintenance, since the networks are more complex. This complexity requires that network security analysis should be performed in real time to avoid decision errors when disconnecting a device from the network or predicting the possibility of operating output from an undersized device. In this article, an intelligent system for contingency selection in the static security analysis of electric power systems is proposed. The severity of contingencies indication is the first step to develop control actions and maintain the system operation integrity. We propose and evaluate the contingency selection as a combinatorial optimization problem, employing an ACO metaheuristic to model the situation. The system is evaluated over the IEEE 30-bus network and a real 810-bus network, considering double outages of branches. Results show an accuracy close to five-nines for severing contingencies.

Distributionally Robust Chance-Constrained Optimal Power Flow Assuming Unimodal Distributions With Misspecified Modes

Chance constrained optimal power flow (CC-OPF) formulations have been proposed to minimize operational costs while controlling the risk arising from uncertainties like renewable generation and load consumption. To solve CC-OPF, we often need access to the (true) joint probability distribution of all uncertainties, which is rarely known in practice. A solution based on a biased estimate of the distribution can result in poor reliability. To overcome this challenge, recent work has explored distributionally robust chance constraints, in which the chance constraints are satisfied over a family of distributions called the ambiguity set. Commonly, ambiguity sets are only based on moment information (e.g., mean and covariance) of the random variables; however, specifying additional characteristics of the random variables reduces conservatism and cost. Here, we consider ambiguity sets that additionally incorporate unimodality information. In practice, it is difficult to estimate the mode location from the data and so we allow it to be potentially misspecified. We formulate the problem and derive a separation-based algorithm to efficiently solve it. Finally, we evaluate the performance of the proposed approach on a modified IEEE-30 bus network with wind uncertainty and compare with other distributionally robust approaches. We find that a misspecified mode significantly affects the reliability of the solution and the proposed model demonstrates a good trade-off between cost and reliability.

Improvement in Recloser–Fuse Coordination Technique Based on Modification Factor

This paper presents a new adaptive technique to restore coordination between recloser and fuse of a distribution network in presence of distributed generations (DGs). The proposed technique is based on the derivation of modification factor (MF) which is defined as the ratio of the preset value of positive sequence impedance seen by a recloser (Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1preset</sub> ) to its calculated value (Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1cal</sub> ). Based on the value of MF, the recloser fast time- current characteristic is altered. The value of Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1cal</sub> is obtained by acquiring samples of currents and voltages at the location of the recloser. Performance of the proposed scheme has been evaluated by modeling IEEE 34-bus network in real time digital simulator (RTDS)/RSCAD environment. At the same time, appropriateness of the proposed scheme has been verified on a practical setup developed in the laboratory. The results obtained from simulations as well as from the laboratory prototype indicate that the proposed scheme is able to restore coordination between recloser and fuse with a high as well as a low penetration of DG. At the end, a comparative analysis of the proposed scheme with the previously published schemes proves its superiority in restoring the recloser-fuse coordination.

A novel hierarchical distributed framework for optimal reactive power dispatch based on a system of systems structure

Optimal reactive power dispatch is one of the major issues in operation of power systems which aims to minimize losses, voltage stability, voltage deviation, etc. through an optimal adjustment of control variables. Recently, some alterations have been involved in control procedures, management and scheduling of these systems due to the power systems restructure, electricity markets and smart grids. These changes are notable in methods used for optimal dispatch of reactive power as well. According to the hierarchical structure of the power grids, this paper presents a hierarchical distributed framework based on a System of Systems (SoS) concept. In this structure, every section of the grid is controlled by a smart agent. Agents are interconnected and exchange the required data via a telecommunication network. In this paper, the amounts of active and reactive power exchanged between agents are considered as boundary and common parameters. Our proposed method is implemented on the IEEE 118-bus network connected to 7 active power distribution networks. The results are compared to the ones obtained from a distributed method based on an Incident Command System (ICS) and a centralized control method. It turns out that the proposed method outperforms the other two competing methods.