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This paper addresses the challenge of protecting electrical networks in the presence of distribution generators (DGs). The use of DGs affects fault currents, leading to miscoordination between protection relays and causing constraints on network reliability. To tackle this issue, the authors propose an adaptive protection scheme (APS) based on a modified pelican optimization algorithm (MPOA) and active database management system (ADBMS). The APS coordinates directional overcurrent relays and distance relays, while the MPOA simulates a pelican mating strategy and includes a modified internal equation. The proposed APS is further upgraded with ADBMS to save system resources by storing relay settings in the database and calling them when the state of DGs changes without running optimization algorithms. The effectiveness of the proposed APS is validated on the Institute of Electrical and Electronics Engineers (IEEE) eight‐bus test system and the IEEE 14‐bus distribution network. Results indicate that the APS can effectively protect electrical networks in the presence of DGs, while the ADBMS upgrade saves system resources. [ABSTRACT FROM AUTHOR]

In this paper, a new distributed multi-agent framework based on the three layers' fog computing architecture is developed for real-time microgrid economic dispatch and monitoring. To this end, the changes of load at any time will be tracked by the proposed technique, considering unit sudden exits and entries. Moreover, to make the system more realistic, different renewable energies, including photovoltaics (PVs), wind turbines (WTs), fuel cells (FCs), and microturbines (MT) are considered in the proposed technique. To overcome the complexity of the problem, by using advantages of fog computing, a new fast consensus-based optimization algorithm is used, which is modified based on the fuzzy adaptive leader technique. Finally, the proposed technique is simulated and tested on microgrids with 6 and 14 buses, respectively. Simulation results demonstrate and validate the effectiveness of the proposed technique, as well as the capability to track the changes of load with the interactions in real-time and the fast convergence rate. • We developed a three-layer framework based on fog computing for MG. • We developed a modified distributed consensus-based technique to achieve the optimal dispatch solutions. • We simulated and analyzed the proposed model on two IEEE standard test system with two different scenarios. [ABSTRACT FROM AUTHOR]

This paper discusses an energy management system–based demand response scheduling strategy in distribution system. The proposed strategy includes customer payment minimization and network loss minimization as responsive load scheduling objectives through centralized approach. Two types of optimization strategies each based on payment minimization and network loss sensitivity are discussed in this paper. Thus, the proposed scheduling strategy can effectively resolve the optimality issue between different objectives of the distribution system scheduling under demand response penetration. The demand response scheduling strategies are simulated using standard IEEE 37 bus distribution test system through different cases of scheduling and optimization scenarios. The simulation results are presented, discussed, and compared with the base test cases without demand response penetration and without optimization strategies under demand response penetration to demonstrate the effectiveness of network loss, sensitivity consideration and optimization strategies in carrying out distribution system scheduling. In addition, sensitivity analysis is performed. The variation of distribution network performance is analyzed for various test cases and scenarios at different penetration levels. [ABSTRACT FROM AUTHOR]

High-impact low-probability weather hazards threaten the power network operation. One of the existing solutions is to reinforce the network with further investment, while the network hardening is restricted by environmental policies and financial conditions. Flexibility methods become increasingly important to enhance network reliability and resilience at low costs. Emergency loadings and probabilistic thermal ratings for overhead lines (OHLs) are the common flexibility options to the network operators. So far, the reliability and resilience impacts of such operations of OHLs and their associated ageing risks are not thoroughly investigated in the up-to-date literature. This study presents a novel resilience enhancement method against windstorms using available emergency demand response in the network and emergency loading of OHLs. The proposed methodology framework can capture the enhancement of network resilience from emergency loading and emergency demand response to provide extra flexibility and minimise network ageing. It is a novel optimisation approach to quantify the trade-off between enhanced network resilience and ageing accounting for operators' preferences regarding the criticality of an individual line's ageing. The proposed method is applied on the IEEE 24 bus reliability test system with having network resilience improvements up to 39% in the conditional value at risk of the energy not supplied and ageing minimisation up to 44%. [ABSTRACT FROM AUTHOR]

Natural disasters, faults, or the sudden outage of major energy resources can create resilience issues in power systems. Modern distribution systems can reconfigure due to the use of automated protection and control techniques and the proliferation of distributed generators (DGs). If there are several DGs located nearby, distribution systems can be clustered into microgrids in an emergency condition. Clustering of distribution systems offers many benefits to achieve high system resilience. Moreover, demand response (DR) is an efficient way of increasing the operation quality and improving the resilience of the power system. This study discusses the impact of DR on the resilience of dynamically-clustered distribution systems. Accounting for the DR while clustering the distribution system can be beneficial for distribution system customers from the resilience and power quality points-of-view. To this end, the distribution clustering is performed using two different objective functions to improve its resilience and voltage profile. DR is formulated as new constraints applied to the distribution system clustering optimisation problem. This study proposes a multi-objective optimisation function that is solved by using an exchange market algorithm, Pareto efficiency method, and fuzzy satisfying approach. The simulations are performed on IEEE 33-bus test system. [ABSTRACT FROM AUTHOR]

With the ongoing automation driven by the push toward the smart electric grid and the advancement in associated cyber infrastructure, the interaction between physical [electric transmission and distribution (T & D) systems], cyber (communication, automation, and control), and human (grid operators and decision-makers) is increasingly becoming more complex. This creates the requirement of analyzing the effect of the transmission system on the distribution system and vice versa with consideration of the additional complexity of the cyber infrastructure. Such an integrated testbed will also help with resiliency analysis, where resiliency refers to the ability of the system to continue serving energy to the critical loads even with limited extreme contingencies. Interaction of the physical power grid with the cyber layer can be effectively modeled using real-time (RT) simulator for developing and validating various operational and control algorithms. Testbeds using RT simulators with multiple capabilities have been developed at different institutions. Still, no single existing testbed can offer full scalability while simultaneously meeting high fidelity requirements for resiliency experimentation. Co-simulating federated testbed assets can provide a scalable experimentation platform that can be leveraged for verification and validation. In this article, an architecture is developed for federated cyber-physical testbed. A local federation with two real-time simulators is developed: real-time digital simulator (RTDS) and OPAL-RT have been interfaced using VILLAS framework for end-to-end testing. Also, a real-time linear predictor is developed and integrated here to address the communication latency impact on geographically allocated federated RT simulation. Finally, resiliency analysis tools are formulated and utilized for T & D systems. As an illustrative use case, the resiliency of a T & D test system is simulated, and the results are analyzed. A 179-bus Western Electricity Coordinating Council (WECC) transmission system is developed using OPAL-RT/ HYPERSIM, and a modified IEEE 13 node feeder system is modeled in RTDS/RSCAD and interfaced for resiliency analysis. [ABSTRACT FROM AUTHOR]

With the increasing integration of distribution generations (DGs), active distribution networks (ADNs) need to address the new challenges in voltage control. Meanwhile, the traditional centralized method in reactive power optimization usually leads to a heavy computational burden for large-scale distribution networks. A distributed voltage control model with a novel network partitioning method is proposed in this study, where the capacity curve of DGs and the regulation of electrical storage systems (ESS) are specially addressed. According to the number of decision variables and the number of constraints in the optimization model, the computational complexity can be utilized in the network partitioning method with the power balance and the electrical distance to automatically partition a distribution network in an optimal manner. Taking the coordination between two boundary sub-areas into consideration, a distributed voltage control strategy is developed and solved by a distributed solution method based on Lagrangian dual relaxation. Finally, numerical studies based on two IEEE test systems and a practical 152-bus system are performed to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a measurement-based method to determine distributed energy resource (DER) active- and reactive-power setpoints that minimize bus voltage deviations from prescribed reference values, bus active- and reactive-power deviations from desired setpoints, as well as cost of DER outputs. Central to the proposed method is the estimation of a linear sensitivity model from synchronized voltage and power-injection data collected from distribution-level phasor measurement units installed at only a subset of buses in the distribution system. As new measurements become available, the linear sensitivity model is updated via the recursive weighted partial least-squares estimation method. The estimated sensitivity model is then embedded as an equality constraint in a convex quadratic optimization problem, which can be solved via, e.g., the alternating direction method of multipliers. Numerical simulations involving the IEEE 33-bus distribution test system illustrate key benefits of the proposed method, including (i) eliminating the need for an accurate offline system model, (ii) adapting to online network-topology and operating-point changes, and (iii) being robust against delays potentially attributed to communication, computation, and actuation. Additional numerical simulations involving larger test systems demonstrate computational scalability. [ABSTRACT FROM AUTHOR]

An improved version of power flow-controller (PFC) which is based on multi-winding transformer (MWT) is presented in this paper. The objective of this article is to control the power flow in a power-line to alleviate overload in a heavily loaded system and increase power flow of an under loaded line. The novelty of multi-winding transformer based power-flow controller is the use of unequal voltage ratio in the tap-changer windings of MWT with bi-directional switches to provide a compensating voltage required to achieve the desired power flow. This new model drastically increases the number of compensating points to make it more compact with higher flexibility. It aims to utilize the full potential of a line (bound by its thermal limits) to contribute in power flow by providing several times higher resolution with limited number of switches and reduced amount of copper and iron volume compared to existing state-of-the-art technology. The proposed MWT model has been included in Newton Raphson Load Flow (NRLF) method for power flow analysis. The feasibility of the model has been realized using a standard 5 bus test system and a modified IEEE 57 bus system. Operation of the PFC has been demonstrated using a hardware laboratory prototype for generating nearest compensating points (voltage vectors) corresponding to the obtained compensating voltages after load flow solution. The results obtained are verified by simulating the controller in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Technological developments in protective devices have established the basis for appearance of numerical overcurrent relays (OCRs), which enable the users to apply their desired time-current characteristics (TCCs). This study propounds novel stepwise and combined stepwise–piece-wise linear TCCs and presents clear procedure to utilise them for coordinating OCRs in large meshed power systems. The TCCs keep constant time interval between the main/backup relay pairs within entire fault current range. They are examined first by coordinating the OCRs in a 4-bus power system and by coordinating the ground fault OCRs in a practical 60 kV looped power system. Then, the OCRs of the IEEE 14-bus test system, which is a rather large meshed power system with 39 OCRs and 102 main/backup pairs, are coordinated by using the novel TCCs. The same relays in the aforesaid power systems are coordinated using some non-standard TCCs recently introduced in the literature. The comparison verifies that the lowest operating times are achieved by using the novel TCCs. The devised TCCs are simply formed as look-up tables to be exactly set on the existing industrial relays. This fact is verified by setting them on an industrial OCR, and then, by testing the relay through the current injection method. [ABSTRACT FROM AUTHOR]

This study presents a new re-scheduling method for generating units in the form of optimal power flow (OPF) problem, considering small signal stability (SSS) constraint of power system in normal operation and N−1 contingency of transmission lines outage. In base case, total operation cost is minimized, considering voltage stability margin and N−1 line contingency. The SSS of system is studied by using modal analysis. In case of unstable modes in the generator(s) rotor angle, the generators scheduling should be re-dispatched. Using modal analysis and sensitivity matrix, the generators are divided into three groups: increasing power generators, decreasing power generators, and unchanged power generators. In order to increase the accuracy of re-scheduling program, two new technical and economic indexes are introduced. The output power of the candidate generators is increased/decreased based on the indexes to stabilize generator(s) with unstable rotor angle (URA). The salient feature of proposed method is its capability on stabilizing system with one or more URA generators with minimum changes in base case OPF results. The Validity of proposed method is studied on IEEE 39-bus 10-machine, and IEEE 69-bus 16-machine test systems. The obtained results verify effectiveness of proposed re-dispatch algorithm in case of single or multiple URA generator(s). [ABSTRACT FROM AUTHOR]

With the penetration of distributed generation (DG) units, the power systems will face insecurity problems and voltage stability issues. This paper proposes an innovatory method by modifying the conventional continuation power flow (CCPF) method. The proposed method is realized on two prediction and correction steps to find successive load flow solutions according to a specific load scenario. Firstly, the tangent predictor is proposed to estimate the next predicted solution from two previous corrected solutions. And then, the corrector step is proposed to determine the next corrected solution on the exact solution. This corrected solution is constrained to lie in the hyperplane running through the predicted solution orthogonal to the line from the two previous corrected solutions. Besides, once the convergence criterion is reached, the procedure for cutting the step length control down to a smaller one is proposed to be implemented. The effectiveness of the proposed method is verified via numerical simulations on three standard test systems, namely, IEEE 14-bus, 57-bus, and 118-bus, and compared to the CCPF method. [ABSTRACT FROM AUTHOR]

Optimal placement of FACTS devices attempts to improve power transfer, minimize active power loss, enhance voltage profile and improve voltage stability, thereby making the operation of power systems more flexible and secured. The classical methods experience difficulties in solving the FACTS placement problem (FPP) with discontinuous functions and may diverge or result oscillatory convergence. Besides the number of FACTS devices for placement should be given as an input while solving the problem. The solution methods then attempts to forcefully place all the specified number of devices in the power system, but in reality, the system may require an optimal number of FACTS for placement. The application of swarm-intelligence based optimization algorithms strives to overcome the drawbacks of classical methods. This paper presents a new solution method for FACTS placement problem using improved harmony search optimization (IHSO) with a newly suggested dissonance mechanism that avoids badly composed music, with a view of avoiding the sub-optimal solutions. Besides, the method requires to specify only the maximum number of FACTS devices for placement and places only the optimal number of devices within the specified maximum number of devices. The paper also includes simulation results of three IEEE test systems for exhibiting the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Distribution system state estimation (DSSE) is one of the key functions used by distribution system operators (DSOs) for the management and control of the distribution grids. In general, distribution networks are featured by a very large number of nodes. Thus, performing the state estimation (SE) of the whole network is computationally demanding. From the system observability point of view, the scarcity of the installed measurement units in the distribution systems is a huge barrier to perform DSSE. Moreover, the unbalanced nature of distribution systems makes estimators based on the positive-sequence model unfit. To tackle these issues, this article presents a new data-driven three-phase state estimator based on an artificial neural network (ANN) and sparse measurements from phasor measurement units (PMUs), together with its observability assessment. Unlike existing estimators performing weakly under non-Gaussian noise, the proposed estimator provides accurate estimates. The proposed SE technique is executed extremely fast (in a few milliseconds). This feature facilitates the real-time monitoring of the distribution grids, as the estimators are coupled with the PMUs. In this context, PMUs play a crucial role as they can provide synchronized phasor measurements with a high reporting rate (ƒPMU > 1 Hz). To reduce the computational cost of the SE problem with distributed computation, multiple ANN three-phase estimators are executed in parallel and integrated in a multiarea SE architecture. The simulation results on the benchmark IEEE 123-bus test system support the feasibility of the solution. [ABSTRACT FROM AUTHOR]

Optimal placement of Distributed Generation (DG) in the distribution network is a significant solution to resolve the power loss issue. Selection of the optimal locations and sizes of the DG is a practical problem and challenging job to achieve the minimum loss. In this work, the optimal location and appropriate size of the DGs have been found out to minimize the total active power loss of the distribution system with less penetration level of the DG considering of 24 hours duration. A modified search algorithm has been proposed in this paper which is capable to obtain the best solutions. Moreover, several reputed soft computing techniques have been applied to solve the problem and validate the optimal results. Technical aspects like energy losses have been minimized instead of power loss and practical factors like hourly basis solar output, wind generation and load variation have been considered to make this work more realistic. The solution techniques have been tested on the IEEE 33, IEEE 69 and 118 radial distribution test bus systems and results have been compared with recent literature. The quality of the results establishes the efficiency of the proposed modified algorithm to solve the optimal location and sizing problem with the effect of PV and wind power variation along with the variable load. [ABSTRACT FROM AUTHOR]

In planning and operation processes of power systems, the most critical and outstanding problem is the optimal scheduling of reactive power resources. The current research study considered real power loss as well as the deviation of voltage magnitude as objective functions since these two play important roles in a power system's operations and control. Due to the above-mentioned considerations, bi-objective optimization takes a form here. In the recent times, lot of meta-heuristic optimization techniques was implemented to elucidate ORPD problem. One such recently advanced algorithm named Interior Search Algorithm is utilized to find a solution for challenges in power system. It is observed that it is not producing accurate solution and convergence characteristic curve is also not smooth. In order to enhance the searching ability of ISA a new method called Levy Interior Search Algorithm (LISA) was proposed in this paper. In this two different strategies of LISA were proposed. In order to validate the proposed algorithm, LISA is implemented on five various standard test systems comprising IEEE 30-bus, IEEE 57-bus, IEEE 118-bus, IEEE 300-bus and IEEE 354-bus test systems. To conclude, application results of LISA are compared with the results of other optimization techniques reported in literature. The comparison reveals that the LISA Strategy-II outperformed all other optimization techniques in terms of robustness, accuracy and convergence speed. [ABSTRACT FROM AUTHOR]

In a competitive electricity power market, reactive power planning (RPP) is a pivotal matter for the power system researchers from operational and economical view points. RPP is concerned with the installation or removal of reactive power equipment in power system. This article proposes an effective way to find out the optimal parameter settings related to the system active power loss as well as operational cost. Genetic Algorithm (GA)-based strategy is applied to determine the optimal values of reactive power generation of generators, size of shunt capacitors, transformer tap settings prior to minimizing the system operating cost due to active power loss, installation cost of shunt capacitors at the weak nodes, and the cost of line-charging elements. The proposed approach is applied to IEEE 30 and IEEE 57 bus test system. Finally, a comparative analysis has been done to validate the efficacy of GA-based approach with some well-established meta-heuristic algorithms. [ABSTRACT FROM AUTHOR]

Summary: Energy sustainability and reliability issues have created great concerns globally, instigating various utilities to create interconnections with one another for system security and techno‐economic benefits. Capacity benefit margin (CBM) is the amount of transmission capacity reserved between interconnected systems for emergency power exchange between utilities. It is usually estimated by evaluating the reliability of the generating units of interconnected systems to know the amount of external generation required during emergency supply shortage. Various techniques have been employed in literature to evaluate CBM. However, despite the global awareness on the continuous shift from conventional power generation sources to renewable energy sources, the assessment of CBM in the presence of renewable energy has not been addressed. Moreover, existing techniques for CBM calculation are based on iterative optimization and may not scale well to more than one deficient area. To solve these issues, this article incorporates wind power (WP) generation in CBM computation. The proposed technique is based on graph theory and can be used to calculate CBM in the presence of multi‐deficient areas and renewable energy sources, in particular, WP. Simulations using the IEEE 24‐bus reliability test system in MATLAB show that the proposed technique is significantly better in terms of scalability and accuracy as compared to existing techniques. The proposed technique can be employed by utilities for CBM estimation in the presence of renewable energy sources. [ABSTRACT FROM AUTHOR]

We develop a multi-period stochastic optimization framework for identifying operating reserve requirements in power systems with significant penetration of renewable energy resources. Our model captures different types of operating reserves, uncertainty in renewable energy generation and demand, and differences in generator operation time scales. Along with planning for reserve capacity, our model is designed to provide recommendations about base-load generation in a non-anticipative manner, while power network and reserve utilization decisions are made in an adaptive manner. We propose a rolling horizon framework with look-ahead approximation in which the optimization problem can be written as a two-stage stochastic linear program (2-SLP) in each time period. Our 2-SLPs are solved using a sequential sampling method, stochastic decomposition, which has been shown to be effective for power system optimization. Further, as market operations impose strict time requirements for providing dispatch decisions, we propose a warm-starting mechanism to speed up this algorithm. Our experimental results, based on IEEE test systems, establish the value of our stochastic approach when compared both to deterministic rules from the literature and to current practice. The resulting computational improvements demonstrate the applicability of our approach to real power systems. [ABSTRACT FROM AUTHOR]

Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, which rotate in a power network according to the system impedances, may not necessarily result in an optimum harmonic power flow in terms of harmonic undesirable results such as harmonic losses or harmonic over voltage/current due to possible resonances. This paper proposes a new method to control the flow of the remaining harmonics at a power system level such that the effects of harmonics such as losses are optimized. This task is achieved by the use of series active power filters controlled in a different manner from their conventional methods. In this new application, the series active power injects a controlled harmonic voltage into a power system (e.g., a line, transformer, or other elements) to control the harmonic current (power) flow such that the overall performance of the power system is improved in terms of harmonic effects. The series active power filter in this new application is named as harmonic power flow controller (HPFC). In this paper, the theory, structure, applications, and the basics of the control method of a HPFC are described. To investigate the effects of the HPFC on the power network harmonics, an HPFC is used in the 14-busbar IEEE test system. To make the proposal more practical, an HPFC is designed for Iran north-west transmission system to alleviate the harmonic problem in this region. Simulations are carried out to show the effectiveness of the HPFC. Simulation results show that the HPFC can control the harmonic currents (power) and voltage consequently. In this paper, several control algorithms for an HPFC are also considered to achieve the desired harmonic voltages levels. [ABSTRACT FROM AUTHOR]

This paper proposes a novel two-stage game-theoretic residential photovoltaic (PV) panels planning framework for distribution grids with potential PV prosumers. One innovative contribution is that a residential PV panels location-allocation model is integrated with the energy sharing mechanism to increase economic benefits to PV prosumers and meanwhile facilitate the reasonable installation of residential PV panels. The optimization of residential PV panels planning decisions is formulated as a two-stage model. In the first stage, we develop a Stackelberg game based stochastic bi-level energy sharing model to determine the optimal sizing of PV panels with uncertain PV energy output, load demand, and electricity price. Instead of directly solving the proposed bi-level energy sharing problem by using commercial solvers, we develop an efficient descend search algorithm-based solution method which can significantly improve the computation efficiency. In the second stage, we propose a stochastic programming based residential PV panels deployment model for all PV prosumers. This model is formulated as an optimal power flow (OPF) problem to minimize active power loss. Finally, simulations on an IEEE 33-node and 123-node test systems demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The increasing penetrations of renewable energy in the electricity sector and plug-in electric vehicles (PEVs) in the transportation sector have increased the interests in introducing new methods to deal with uncertainties in power system studies. In this paper, a new distributionally robust optimization (DRO) via scenario wise ambiguity set is proposed to develop a collaborative bidding strategy for intermittent resources such as hydroelectric generation, wind farms, solar farms and electric vehicle aggregator in the day-ahead energy market. The proposed scenario wise ambiguity set is based on Wasserstein distance and is capable of considering both distributional information and statistical distance metric information in the ambiguity set. In this context, the robust counterpart of proposed DRO applying scenario based affine recourse approximation is developed in this paper. The proposed methodology is applied on a 3-bus test system as well as IEEE 118-bus test system to corroborate the effectiveness of the novel DRO model. [ABSTRACT FROM AUTHOR]

Energy systems, e.g., power systems and natural gas systems, are increasingly interdependent, which brings benefits under normal conditions and introduces risks under extreme weather events, e.g., hurricanes. A comprehensive method is proposed to reflect the spatial-temporal hurricane impacts on interdependent power and natural gas systems. Mechanism analysis based and data based component failure models are used to map hurricane effects on exposed component failure probabilities based on which system states are generated using Monte Carlo simulation. For system states with failed components, the integrated energy flow is developed to determine minimum joint load shedding considering inherent properties of each system and characteristics of interdependence coordinately. Operational metrics and infrastructure metrics are employed to quantify the service adequacy and network resistance of the interdependent energy systems, respectively. The modified IEEE 24-reliability test system and the 12-node natural gas system under a simulated hurricane are used to validate the effectiveness of the proposed method. Simulation results show the method can identify weak parts and quantify the performance of interdependent power and natural gas systems under hurricanes to provide information for effective and coordinative preparedness. [ABSTRACT FROM AUTHOR]

This paper presents an AC Optimal Power flow (AC-OPF) problem of a power system, considering wind energy. Wind energy is an environmental-friendly energy source to produce electrical power and it includes less operating costs compared with other sources of electrical power production. Wind generators also affect the operation cost of a power system as well as transmission losses, based on generators locations and speed of wind. In addition, wind speed is a parameter with uncertainty and considering this uncertainty is an important issue in operation of wind generators in the AC-OPF problem. The proposed AC-OPF formulation includes the integer variables in addition to continuous variables and studies the effects of wind energy, transformer tap settings, and shunt capacitors on fuel cost, transmission losses as well as up and down spinning reserves. To solve the AC-OPF model, an Improved Particle Swarm Optimization (IPSO) is presented. The IPSO algorithm in this work includes velocity mirror effect that causes improvement in the quality of the results. The proposed method is applied on modified IEEE 30 bus test system, and obtained results approve the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Large distributed generation (DG) penetration into the power system needs to be accompanied by proper planning to maximize the benefits and minimize the negative effects that may arise on the system. Determining the location and size of DGs in power systems is a complex issue because it involves hundreds or even thousands of buses and lines distribution. Various studies have been conducted to overcome these problems, including by developing existing methods or even discovering new methods. This study deals with location optimization and sizing DG in the radial distribution system to minimize power loss and voltage deviation. The location of the DG is identified using a loss reduction sensitivity factor (LRSF) while the size of the DG is determined using the improved method of symbiotic organisms search (SOS) called New Enhanced SOS (NeSOS). There are two methods developed in the NeSOS, namely random weighted inverse vector (RWIV) and dual-phase parasitism (DPP). DPP consists of classic parasitism (CP)and random weight parasitism (RWP). The NeSOS is programmed under MATLAB software and validated using 26 mathematical benchmark functions. NeSOS also tested on IEEE 33 and IEEE 69 bus test system and compared with other methods. The simulation results show that the convergence rate of NeSOS is 30% faster than SOS. NeSOS also provides an average power loss of 1.53% lower than other methods. [ABSTRACT FROM AUTHOR]

Due to high wind power penetration into power system, synchronous generators may no longer be the dominant generation, which implicitly requires participation of wind power plants (WPPs) in the load-frequency control (LFC). Frequency, a common variable throughout the entire power system, is the key variable for LFC, which causes equal contribution of all distant and nearby WPPs in LFC. Power transfer from distant WPPs to the event location may overload the middle transmission lines leading to cascading failures. This study proposes an online dispatch rescheduling algorithm for WPPs participating in the LFC task to prevent over loading of transmission lines and hence cascading failures following severe frequency contingencies. The WPP dispatch limits are calculated based on line ampacity for each generation unit participating in the LFC task. Numerical simulations carried out in DigSilent PowerFactory on 39 bus IEEE standard test system, demonstrates the efficiency of suggested online dispatch rescheduling technique for keeping the loading rate of transmission lines, bus voltages and system frequency in range. [ABSTRACT FROM AUTHOR]

Under the impact of various uncertainties, the potential operation risk of the distribution network is gradually gaining more and more attention in both security and economy. To comprehensively determine the risk level, an operational risk assessment method considering multiple risk factors is proposed. Firstly, probabilistic models are established including temporal distributions of electric vehicles and uncertainties of renewable energy. Secondly, a time-sequential security risk assessment method with several security indicators including overvoltage risk, undervoltage risk, line-overload risk and load-loss risk is established using probabilistic load flow and dynamical sensitivity weight analysis method. Thirdly, conditional value at risk model is presented for time-varying economic risk considering line-loss risk and operational profit or loss risk of distributed generations. Finally, a risk early warning standard is proposed to realise the visualisation of risk warning by defining the risk level and risk area. Simulations of different scenarios are conducted on the modified IEEE 34-bus radial test system and the results reveal that the proposed strategy is effective and practical. [ABSTRACT FROM AUTHOR]

The operation of the electricity delivery infrastructure is environmentally driven and vulnerable to a wide range of high-impact low-probability (HILP) hazards. Among different classes of HILP disasters, earthquakes are one of the most unpredictable hazards which may lead to widespread disruptions of mission-critical services and infrastructures. This article introduces a comprehensive framework for modeling and characterization of seismic hazards, vulnerability assessment of electric systems to the earthquake, and corrective actions and mitigation strategies ensuring operational resilience. The Monte Carlo simulation is employed to produce a realistically large set of possible earthquake scenarios to capture the stochastic nature of seismic hazards. An inclusive approach is then introduced based on the fundamental principles of fragility curves to assess the vulnerability of power generation facilities in the face of HILP earthquakes. A new seismic risk metric is suggested that takes into account both hazard and vulnerability probabilities, as well as the financial consequences due to postquake disruptions in power generation stations. Along with the generation redispatch strategy as a conventional mitigation solution following a nontrivial contingency, a new mitigation strategy centered on corrective network topology control is formulated to maximize the load outage recovery following HILP disruptions. The proposed decision support tool enables a swift restoration and improved resilience in dealing with the aftermath of the HILP earthquakes. Efficacy of the proposed framework is numerically analyzed and verified on both the IEEE 57-bus and IEEE 118-bus test systems. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) is a vital concern in an electrical network. In consequence of the intricacy of the power systems, the conventional formulations are not adequate for current situation. Hence, in this study, the multiobjective OPF (MOOPF) problem has been modeled to diminish the production cost, environmental emission, and losses and to enhance the voltage stability and voltage profile simultaneously. This study proposes the application of interior search algorithm (ISA) for resolving MOOPF problem. The simulations have been carried out on three various test systems such as IEEE 30‐bus system, IEEE 57‐bus system, and Tamil Nadu Generation and Distribution Corporation Limited, as a real part of 62 bus Indian utility system (IUS) to infer the efficacy of ISA in solving the OPF problems. The simulation results have been compared with other techniques. The comparison shows that ISA is used in resolving MOOPF problems. [ABSTRACT FROM AUTHOR]

Summary: AC optimal power flow (ACOPF) is a nonlinear and non‐convex problem that might include various constraints. The methods in the literature for solving this problem may suffer from premature convergence and high computational effort. In this study, ACOPF is formulated as a mixed‐integer linear programming (MILP) that allows problem modeling with a closer look at the limitations of actual operating conditions along with other common constraints. This article contributes to literature by presenting efficient MILP methods of the ACOPF problem in terms of various actual constraints, such as valve loading cost, prohibited operating zones, and the multi‐fuel units. The proposed methods aim at reducing the computational effort with a sufficient improvement in finding the optimal solution. Effectiveness and accuracy of the proposed methods are evaluated on the standard IEEE 30‐bus, 118‐bus, and the polish 2746‐bus test systems. Numerical results confirm the validity and quality of the proposed MILP methods with convexified various actual constraints (MILP_CVAC) for the ACOPF problem. A significant reduction is found in computing time to solve the ACOPF problem with the proposed MILP_CVAC methods due to the use of strong MILP solvers and the convexity of the model, without affecting the accuracy. In some cases, the results show several hundred times shorter computation time compared to nonclassical methods. [ABSTRACT FROM AUTHOR]

This paper proposes a robust and computationally efficient wide-area backup protection (WABP) scheme against asymmetrical faults on transmission systems using available synchronized/unsynchronized phasor measurements. Based on the substitution theorem, the proposed scheme replaces the faulted line with two suitable current sources. This results in a linear system of equations for WABP, with no need of full system observability by measurement devices. The identification of the faulted line is attributed to the sum of squared residuals (SoSR) of the developed system of equations. To preserve accuracy, the scheme limits the calculations to the assessment of the negative-sequence circuit of the gird. Relevant practical aspects that have not been properly addressed in the literature, namely the non-simultaneous opening of circuit breakers (CBs) and their single-pole tripping for single-phase to ground faults are investigated. The linearity of the formulations derived removes concerns over convergence speed and potential time-synchronization challenges. The proposed scheme is able to identify the faulted line and retain this capability for hundreds of milliseconds following the fault inception. More than 20 000 simulations conducted on the IEEE 39-bus test system verify the effectiveness of the proposed WABP scheme. [ABSTRACT FROM AUTHOR]

This article presents a new approach for classification and localization of voltage sags triggered by symmetrical and unsymmetrical faults in electricity networks. The proposed method utilizes five unique parameters of three-dimensional (3-D) polarization ellipse (PE) obtained from the mapping of three-phase voltage signals in 3-D coordinates. The decision boundaries, which are set by the parametric equations exploiting the five ellipse parameters, namely, elevation, azimuth, tilt angles, semi-major axis, and semi-minor axis, are used to classify the fault-initiated sags. The localization of faults is conducted from the parametric equations demonstrating the variation of ellipse parameters with respect to distance from the fault-location. These parametric equations would be helpful to make decision faster and thereby, eliminate the uncertainty in decision-making process. The applicability of the proposed method is tested and validated using real data measured by DOE/EPRI, the recorded waveforms of IEEE 1159.2 Working Group, and the data extracted from the simulation of faults at several feeders of IEEE 14-bus test system using RSCAD and Real Time Digital Simulator (RTDS) platform. [ABSTRACT FROM AUTHOR]

In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multiobjective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II. [ABSTRACT FROM AUTHOR]

Wind power application in producing electrical energy is an integral part of the increased eco-friendly generation. Accordingly, wind power producers may have a dominant position in some electricity markets. This study mainly concerns a strategic wind power investor who owns a number of units and seeks to optimise its expansion plans on sizes and sites of new generation capacities in a horizon year. Here, the investor is a price-maker in both day-ahead (DA) and intraday (ID) markets, while acts as a deviator in the balancing market. A stochastic bi-level model is proposed wherein the upper-level, the investor maximises the expected profit. Both DA and ID market clearings are considered in the lower-level (LL). The model is formulated as a mathematical program with equilibrium constraints (MPEC) by replacing the LL problem with its Karush–Kuhn–Tucker (KKT) conditions. The MPEC model is then converted to a mixed-integer linear programming model. A three-bus illustrative example and IEEE 24-bus reliability test system are used to demonstrate the effectiveness of the proposed model. The results confirm that the presence of the ID market in the investment model has increased the expected profits of the investor and also increases invested wind capacity. [ABSTRACT FROM AUTHOR]

The aim of the research work is to propose an integrated optimization technique, established with the integration of the invasive weed optimization (IWO) and Powell's pattern search (PPS) method. The IWO algorithm has been undertaken as a global search technique, which is inspired from the specific ecological behavior of weeds and has the ability to adapt to the changing environment. The local search PPS method is based upon a conjugate-based search and having excellent exploitation search capability, which helps to improve the solution obtained from IWO technique. The proposed technique is applied to solve optimal power flow (OPF) problem with the flexible AC transmission system devices. The OPF problem is a nonlinear, non-convex optimization problem and consists of continuous and discrete decision variables. The three objective functions comprise total fuel cost, pollutant emission and system transmission loss which are minimized sequentially. The proposed technique is tested on four standard IEEE test systems, and results are compared with the reported results in the literature and found promising. The results illustrate that the proposed technique performs better as compared to IWO technique in terms of the quality of solution and convergence characteristics. Further, t test is performed to validate the statistical performance of the proposed integrated optimization technique. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses a novel formulation and solution for the security constrained reserve management (SCRM) problem in both normal and N − 1 contingency conditions. Indeed, the SCRM problem is a modified version of the security constraint unit commitment problem which is updated with the operational reserve management and frequency stability constraints in both normal and N − 1 contingency conditions. The objective of this problem is to determine the optimal amounts of generation associated with different units and frequency regulation reserve (FRR) and allocate the FRR among the generation units. Therefore, the SCRM problem is a mixed integer nonlinear problem which is solved using the genetic algorithm in this paper. The powerful PLEXOS software is also utilized to solved and evaluate the results of the SCRM problem. To determine the effectiveness of the proposed method, some test systems, that is, IEEE 24‐bus, IEEE 39‐bus, and IEEE 118‐bus test systems are considered. Results confirm the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Summary: To sustain reliable and secured power system operation, distance relay designs with swing blocking/tripping logic. In order to obviate this event, relay is implanted with power swing blocking function. In order to accomplish this task, detection of swing phenomenon and its discrimination from fault event is essential. Under any dependable situation, the relay refuses to act in a normal way. Depending on the severity of the swing phenomenon, the distance relay releases the tripping/blocking command. Any unintended operation of distance relay during such a critical condition can affect the power system stability as well as security. An unstable and unsecured system can initiate cascaded events. By considering the possible variations in the system and fault condition, presence of series compensation and dependable situations, a secure and adaptive fault‐swing discrimination logic is developed. The presence of negative and zero sequence components can reveal the occurrence of an unsymmetrical fault. So, this paper mainly focuses on the symmetrical fault detection task. The response of the method is verified for the Western System Coordinating Council three machine nine bus system, IEEE 39‐bus test system, and Indian Eastern Regional Grid network, simulated using EMTDC/PSCAD software. Comparative assessment reports with the existing methods are also provided. [ABSTRACT FROM AUTHOR]

Topology control has garnered recent consideration for its value in leveraging the flexiblity of the power system. However, using even the latest technology, the AC optimal transmission switching (ACOTS) problem remains intractable. As such, most research addressing optimal topology control is based on the DCOPF, which has been shown to be particularly inaccurate for transmission switching decisions in the AC power system. This paper accelerates an existing mixed-integer linear power flow model which has been shown to be very accurate in approximating AC power flows. The aim of the new model is to identify transmission switching candidates to prevent load shed caused by contingency events. The methodology was tested on the IEEE 118-bus test case system and presents promising results. The model proposed herein was found to almost always identify AC optimal switching actions while significantly reducing the necessary solution time in comparison with the base model. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic coordination control strategy to enhance the reactive power capability of wind power plants (WPPs) which deploy doubly-fed induction generator-based wind turbines (DFIG-WTs). The proposed control architecture seeks to maximize reactive power availability during grid faults without violating the stable and thermal operational limits of the generator. To achieve this objective, the presented control topology calculates the maximum available reactive power that can be provided by the DFIG-based WPP under any disturbed operation of a power system. The reference value of the required reactive power compensation is thereafter calculated using an adaptive proportional-integral (PI) regulator which outperforms the traditional PI controller. The computed reference value is directly applied to the outer control of the rotor side converter (RSC) to regulate reactive power generation of the stator circuit. Furthermore, the $P-V$ droop characteristics of the induction generator is employed to adjust the active power reference of the RSC converter to increase the reactive power capability during grid faults. Meanwhile, de-rating the active power generation of the DFIG-based WT is accompanied with modifying the pitch angle of the rotor blades to balance the mechanical and electromagnetic torques and to avoid any stresses excreted on the mechanical parts of the WT. If rotor current limits are reached and more reactive power support is still required, the responsible control loop of the grid side converter (GSC) will be activated and augmented to enhance the overall reactive power capability of the DFIG-based WPP. Finally, the proposed control strategy is verified using Two area four machines and IEEE 68 bus test systems. [ABSTRACT FROM AUTHOR]

The fast urbanization process in developing countries creates an electricity load surge that poses serious congestion problems to the urban power grid (UPG). The current practice of system operators is to reconfigure the topological structure of the 110-kV high voltage distribution network (HVDN) in an attempt to adjust the load distribution and eliminate the UPG congestion. However, HVDN reconfiguration is a large scale, non-convex and non-linear optimization problem that is intractable to be solved in an efficient manner. In order to reduce the computing cost and overcome the difficulty in the solving process, new partition rules are proposed to divide the HVDN into multiple smaller regions. The topological structure of each region can be optimized either independently or interdependently based on the condition of the UPG. The solving process is modeled as a bi-level iterative line switching problem. At the upper level, the operational boundary (OB) of each regional HVDN is calculated based on a set of convex ACOPF constraints. At the lower level, the line switching scheme of each regional HVDN is derived based on the corresponding mixed integer second-order cone programming (MISOCP) model considering the OB. Then, the line switching result is examined by the AC power flow to identify whether there is any violation or not. This iterative process continues until all the violations are corrected in the UPG. The proposed method was validated by a modified IEEE 58-node test system and a practical 157-node UPG system. The simulation results showed that the proposed method is able to achieve a higher computational efficiency than the traditional method so it is promising for online applications. [ABSTRACT FROM AUTHOR]

This paper presents the application of information gap decision theory (IGDT) to deal with uncertainties associated with load forecasting in dynamic, environment constrained, coordinated generation and transmission expansion planning. Traditionally, the gaseous emissions are constrained over the whole system. Conventional methods cannot guarantee a practical expansion plan since huge emissions can still occur on some buses in the power system. This paper introduces a per-bus emission limit to avoid extreme emissions in highly populated areas. The effect of nodal emission limits is fully discussed and compared to a conventional method. The model is kept linear using the big M approach to decrease the model computational burden. Reliability is considered by limiting the estimated load not served in each year over the planning horizon. The cost of fuel transportation and fuel limits are considered in order to make the model more realistic and practical. The effectiveness of the proposed model is verified by implementation on Garver 6 bus, IEEE 30 bus, and 118 bus test systems. [ABSTRACT FROM AUTHOR]

This paper puts forward an intelligent method for online voltage stability margin (VSM) assessment based on optimal fuzzy system and feature selection technique, which has excellent performance for large power systems. The proposed VSM estimation method includes three key parts: feature extraction and selection part, estimator part and training part. In this method, power system's loading parameters are used as the main input of adaptive neuro-fuzzy inference system (ANFIS) and association rules (AR) technique is used to select the most effective loading parameters. In the training part, we used Harris hawks optimization algorithm (HHOA) to train the ANFIS efficiently. Using the proposed method, the VSM can be monitored online with high precision for both small and large systems and appropriate control measures can be applied if necessary. Knowing the exact amount of VSM and applying precautionary measures can prevent from voltage collapse, heavy financial losses and power supply interruption. The proposed method tested on 39-bus, 118-bus and 300-bus IEEE test system and the MATLAB simulation results demonstrate d that the propounded method has much better performance than other recently introduced VSM assessment approaches. Providing a VSM estimation method, which is effective for large power systems, selecting the most informative loading parameters and improving the ANFIS's performance using HHOA are the main contributions of this paper. • This paper proposes an intelligent online method for VSM estimation. • The proposed method tested on 39-bus, 118-bus and 300-bus IEEE test system. • The proposed method is effective for large power systems. • ANFIS performance is improved by HHOA. [ABSTRACT FROM AUTHOR]

Economic Dispatch (ED) is one of the major concerns for the efficient and economical operation of the modern power system. Actual ED problem is non-convex in nature due to Ramp Rate Limits (RRL), Valve-Point Loading Effects (VPLE), and Prohibited Operating Zones (POZs). It is generally converted into a convex problem as mathematical programming based approaches cannot handle the non-convex cost functions except dynamic programming, which also suffers from the curse of dimensionality. Heuristic techniques are potential solution methodologies for solving the non-convex ED problem. Artificial Algae Algorithm (AAA), a recent meta-heuristic optimization approach showed remarkable results on certain MATLAB benchmark functions but its application on industrial problem such as ED is yet to be explored. In this paper, AAA is used to investigate convex and non-convex ED problem due to valve-point effects and POZs while considering the transmission losses. The robustness and effectiveness of the proposed approach are validated by implementing it on IEEE standard test systems (3, 6, 13 and 40 unit Test Systems), which are widely addressed in the literature. The simulation results are promising when compared with other well-known evolutionary algorithms, showing the potential and stability of this algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer's effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In large-scale power systems, the wide-area damping controller (WADC) using remote input signals is an effective device that can be applied to deal with poor inter-area oscillation damping. However, its control effect will be degraded by communication uncertainties such as variable time delays in both input and output sides of WADC, partial and complete communication failures. This paper focuses on a new WADC design by regarding communication uncertainties. Such uncertainties are mathematically formulated and analyzed in order to signify its impact on the oscillatory stability. The signal restoration of input and output pairs of WADC is proposed to alleviate an adverse effect of communication uncertainties. Simulation study in an IEEE 50-machine 145-bus test system elucidates that the proposed WADC is superior to that of the conventional WADC without considering communication uncertainties in both performance and robustness. [ABSTRACT FROM AUTHOR]

This article presents an efficient and comprehensive method to find out the minimum number of and the corresponding locations of phasor measurement units (PMUs) guaranteeing full numerical observability of a power system as well as maximize the measurement redundancy in conjunction with preexisting conventional measurements. Furthermore, the effect of number of available channels of PMUs on their optimal placement can be taken into account. The proposed optimal PMU placement (OPP) formulation is extended to consider the case of two types of contingencies, single PMU loss and single branch outage. The objective of the OPP method is the numerical observability, unlike the majority of earlier works which are based on topological observability and do not always ensure numerical observability required for the successful execution of state estimation (SE). The problem is formulated as a binary semidefinite programming (BSDP) model with binary decision variables, minimizing a linear objective function subject to linear matrix inequality (LMI) observability constraints. The BSDP problem is solved using an outer approximation scheme based on binary integer linear programming. The effectiveness of the proposed method is verified on different IEEE test systems. [ABSTRACT FROM AUTHOR]

The abnormalities like (N-1) line contingencies are unavoidable and consequently can cause for either transmission system security margin decrement or power loss increment. Both the issues are primary objectives of the modern power system operation due to their significant effect on generation capacity and economics. This paper proposes Generalized Unified Power Flow Controller (GUPFC) for maintaining adequate security margin and performance improvement under (n-1) contingencies. At first stage, the optimal location of GUPFC device is proposed to determine based on (N-1) line contingency severity index. In second stage, the rating of the GUPFC device is optimized towards minimization of multiobjective function, which formulated using real power loss and security margin index. The parameters involved in the power injection modeling (PIM) of GUPFC and various system operational parameters are optimized using Particle Swarm Optimization (PSO) and Improved Particle Swarm Optimization (IPSO) algorithms towards minimization of multi-objective function. The case studies on IEEE 14-bus and IEEE 30-bus test system are validating the capability GUPFC device to minimize transmission loss and improve security margin significantly even under (n-1) line contingency and need of FACTS devices for real-time. [ABSTRACT FROM AUTHOR]

This paper presents a robust state estimation (SE) based on weighted least absolute value (WLAV) criterion for power systems having both traditional remote terminal units (RTU) and synchronizing phasor measurement units (PMU). It is known that WLAV‐based SE performs poorly when bad data occurred in leverage measurements. To improve the robustness of WLAV‐based SE, a technique for converting actual measurements to pseudo‐voltage measurements is proposed in this paper. Using these pseudo‐voltage measurements, a measurement model containing no leveraging measurement point can be formulated. The SE problem is formulated as a constrained nonlinear optimization based on WLAV criterion and solved by using a primal‐dual interior point algorithm. Several IEEE test systems with mixed measurements have been used to demonstrate the robustness of the proposed method. The results indicate that the proposed method yields superior SE accuracy even under extremely bad data conditions. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging. [ABSTRACT FROM AUTHOR]

Load Flow (LF) analysis is a fundamental and significant issue in electric power systems. Because of the nonlinearity of the power mismatch equations, the accuracy of the nonlinear solvers is important. In this study, a novel and efficient nonlinear solver is proposed with active applications to LF problems. The formulation of the Proposed Method (PM) and its workflow and mathematical modeling for its application in LF problems have been discussed. The performance of the PM has been validated on the IEEE 14-bus and 30-bus test systems against several existing methods. The simulation results show that the PM exhibits higher order accuracy, faster convergence characteristics, smaller number of iterations, and lesser computation times in comparison with the other benchmark methods. [ABSTRACT FROM AUTHOR]