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At present, the usage of various energy sources in the electricity grid has formed new challenges like power quality effectiveness, energy utilization, and voltage stabilization. With the recognition of smart grid, the maintenance of power quality (PQ) has been regarded as the challenging one. Primarily, APF are employed in an attempt to recompense the issues associated with power quality, as they can filter out promptly and responds vibrantly. Here, in this work, an IEEE 9 Bus System based on WSCC is introduced along with UPQC combined DPFC system. To accommodate a renewable energy source, one of the generators test system. MGWO approach-based PID device is combined with DC Source as a converter for 3-phase inverter. This arrangement is studied using Simulation in both cases with and without DPFC. In addition, the performance estimation is done in terms of parameters like load voltage and current, shunt voltage and series current, and grid current along with their THD values. Based on the outcome, it is found that the proposed UPQC–DPFC combination helps in effective harmonic elimination and increased power storage at the output side. [ABSTRACT FROM AUTHOR]

This research investigates the role of various energy storage systems (ESS) in improving the power system resiliency. Different ESS configurations are analyzed individually and in combination to assess their impact on system performance. Additionally, a fuzzy-based controller (PIλDN + FFOPI) is proposed as a secondary controller for load frequency control, with control parameters optimized using an improved Volleyball Premier League algorithm (IVPL). This algorithm leverages the powerful synergy of opposition-based learning and the versatility of the VPL algorithm, resulting in a highly effective and innovative approach. To validate the proposed approach, the modified Kundur's 2-area test system under deregulation is first utilized, and its effectiveness is confirmed through testing with both step and random load disturbances. Sensitivity analysis is conducted to evaluate system performance across a wide range of parameter variations. Furthermore, the modified IEEE 39 bus system is utilized to assess compatibility and scalability. Results demonstrate the effectiveness of combined ESS configurations and the fuzzy-based controller in enhancing system stability and reliability. This research contributes to power system engineering by offering insights into the benefits of energy storage systems for dynamic response enhancement. The proposed fuzzy-based control strategy, tuned by the IVPL algorithm, presents a promising approach for improving power system performance and stability. [ABSTRACT FROM AUTHOR]

Microgrid load flow studies have recently attracted a lot of attention due to the introduction of independent microgrids with decentralized sources. These microgrids can be operated in grid-connected mode as well as in islanded mode. But the islanded mode operation of microgrids has some inherent limitations that cannot be addressed by conventional load flow approaches. Recent research has suggested some modifications to the traditional methods by treating system frequency as a variable parameter and leaving out the concept of slack bus. In this respect, a novel load flow method has been presented for microgrids that operate as droop-regulated distributed generations (DGs) employing distributed slack bus. The Jacobian matrix has been modified, which leads to improved convergence. Further, a comparison of the modified decoupled Newton Raphson and the modified Newton Raphson load flow techniques has been presented. Several case studies for 6-bus and 38-bus test systems, demonstrate the feasibility of the proposed load flow approach. [ABSTRACT FROM AUTHOR]

Distributed generation offers a bright future for electric networks, but requires optimal allocation of dispersed resources and an acceptable optimization technique. This article proposes optimal integration of DGs and capacitor banks to optimize distribution network parameters. Imperialist competitive algorithm (ICA) has been used to optimize the distribution network parameters such as optimal location and capacity of Photo Voltaic Distributed Generator ((PVDG) & capacitor. Loss reduction, declination in C O 2 emission, and an enhanced voltage profile are major advantages of positioning DGs into the distributive topology. The proposed model has been validated and tested on IEEE-33 and Indian real system of 130 bus of Jaipur City for different load patterns. Furthermore, the results obtained from ICA have been verified by simulating the test systems on ETAP software. [ABSTRACT FROM AUTHOR]

In the case of a coastal power system with high wind power integration, the frequent occurrence of typhoons may threaten the structural safety of the network and induce rapid ramp events of wind power. This article proposes a dispatch strategy for a power system with high wind power integration under a typhoon environment, comprehensively considering the phenomena and problems that occur in real typhoon disasters. First, the fragility curve of the tower is modeled considering the joint effects of wind and rain. Second, a filtering technique is adopted to enhance the effects of the high outage probability towers on network reliability. Third, a wind power curtailment strategy that restricts the extremely rapid ramp of wind power during typhoons is developed. Finally, both the curtailment strategy of wind power and the structural failure of the network are incorporated into the risk-based dispatch strategy during typhoon events. Analysis of the test system validates that the proposed dispatch strategy can improve the resilience of power systems during typhoons. Furthermore, the proposed method can also be used in other scenarios under extreme weather conditions, such as ice coating in power networks in which structural failures also occur frequently. [ABSTRACT FROM AUTHOR]

Inclusion of automatic voltage regulators (AVRs) and distributed generation units (DGs) in the distribution system (DS) will enhance the system performance if allocated optimally. Optimal allocation of AVRs and DGs is a complex combinatorial problem requiring a powerful optimization algorithm for solving the optimization problem. This paper proposes an improved pareto multi-objective backtracking search algorithm (IPMBSA) based Pareto front approach for optimal siting and sizing of DGs and AVRs. The proposed approach considers DS technical (such as minimizing of voltage deviation, power losses and voltage stability index), cost and emission indices as objective functions while solving the allocation problem. To evaluate the performance of the proposed approach, five different operational scenarios are considered for analysis on IEEE 33-bus, IEEE 69-bus and practical 43-bus Indian distribution test systems. The effectiveness of the proposed approach is highlighted by comparison of results obtained using a multi-objective approach based on NSGA-II and weighted sum method (WSM). Results propounded that allocation of DG along with AVR yielded better DS performance compared to the scenarios where only DG or AVRs are placed in DS. [ABSTRACT FROM AUTHOR]

Traditionally, directional overcurrent relays (DOCRs) have been used for protecting the meshed distribution systems with DGs. Recently, dual-setting DOCRs have been advocated as competent measures for such cases. Normal inverse (NI) type characteristics-based settings are usually utilized for the forward and backward direction operation of the dual-setting DOCRs. In this article, we aim to analyze the performance of reverse direction dual setting relays by using various curve settings and different fault locations. We propose the application of typical International Electro-technical Commission (IEC) curve settings namely NI, very inverse (VI), and extremely inverse (EI), and definite time settings for the reverse direction operation of dual-setting DOCRs while keeping the forward direction relay characteristics as NI type. The proposed scheme is tested using the modified IEEE-14 bus distribution system in the presence of synchronous-based distributed generations and using the IEEE-30-bus test system. The simulation results indicate that definite time settings for the mid-point and far-end faults provide considerably faster backup tripping times than the NI, VI, and EI characteristic curves. Whereas, in the case of near-end faults all characteristics provide the same tripping time. [ABSTRACT FROM AUTHOR]

This paper presents a modeling for D-STATCOM device into Monte Carlo probabilistic load flow algorithm. The model is used to improve the predictability and voltage profile of distribution networks. In this model, the D-STATCOM's bus is represented as a special generator bus which injects reactive power only. The injected reactive power of D-STATCOM is updated during the iterative process to maintain the voltage magnitude at the specified value. The model can be easily implemented in the original PLF code without deeply modifications. The probabilistic load flow (PLF) with D-STATCOM model is validated using various standard IEEE tests systems; 33-bus, and 69-bus systems. The PLF algorithm with DSTATCOM model has been evaluated based on MATLAB package. However, the obtained results prove the effectiveness of D-STATCOM implementation in the test systems regarding to predictability and voltage profile issues. Moreover, the standard deviation of the systems is decreased. [ABSTRACT FROM AUTHOR]

An oppositional-based learning approach with a real coded chemical reaction algorithm (ORCCRO) has been considered in this manuscript. The ORCCRO algorithm has been used here to find the near-global optimum solution for multi-objective economic-emission load dispatch problem with having nonlinear constraints. Emission extract from thermal power plants like NOx, inequality constraints like power generation operating limit and equality constraints like power balance consideration are considered here. ORCCRO follows the process to reach a stable state in lower energy with different molecular chemical collision. Oppositional-based learning mechanism has also hybrid here with RCCRO to find out more effective solution. Three different test systems are considered for simulation studies revealed that the ORCCRO method is much superior in comparison with other effective algorithms. The results obtained in these three test systems prove the robustness and the efficiency of ORCCRO. [ABSTRACT FROM AUTHOR]

This paper proposes a developed honey badger algorithm (DHBA) to solve the optimal power flow (OPF) problem. DHBA is based on the concept of honey badger algorithm (HBA), which improves problem-solving ability. The improvement is based on two main aims. These are, respectively, to develop a robust HBA using the dynamic fitness-distance balance technique and to improve the honey-finding behavior of honey badgers with a new spiral movement in the HBA algorithm. In this paper, simulation applications are performed on two IEEE (30/57 bus) test systems through 7 case studies (with statistical analysis) to prove the efficiency and the robustness of the DHBA. The efficiency of the proposed DHBA is tested in these two power systems and the obtained results are compared with other methods published in the literature. The obtained test results have clearly demonstrated the DHBA algorithm's potential to solve the OPF problem compared to the standard HBA. Active power losses, one of the important results of the study, are calculated as 2.9062 MW with standard HBA and 2.853 MW with DHBA (for the IEEE 30 test bus system). [ABSTRACT FROM AUTHOR]

Distribution network reconfiguration (DNR) can be defined as an optimization problem in the power system that is done through changing the switching status to reduce loss and operating cost. Moreover, optimal capacitor allocation in the distribution network provides benefits such as loss reduction and improved voltage profile by reactive power compensation. Thus, this study provides a multi-objective framework for DNR and capacitor allocation problem in the presence of distributed generation (DG) sources. In the common DNR studies, the requirement of reliability is not usually fulfilled, usually loss and voltage deviation are often chosen as the objective functions. In this paper, the multi-objective problem is considered as a combination of energy not supplied (ENS) and emission produced by DG units and grid, moreover network loss is defined as the other objective function. The simultaneous presence of DG units and capacitors has made the problem more complicated, and there will be a demand for a precise approach to solve the multi-objective optimization problem. Hence, an enhanced artificial bee colony optimization (EABCO) method is proposed to tackle the complexity of the optimization problem. In order to shown the efficacy of the proposed approach, it is tested on a 33 and 86- node systems, the obtained results of EABCO method are compared with common evolutionary, hybrid and state-of–the-art algorithms. By implementing the proposed approach in two small-scale test systems, approximately 74% and 15% reduction in ENS are achieved compared to the initial value before distribution feeder reconfiguration. [ABSTRACT FROM AUTHOR]

Economic Load Dispatch (ELD) is the most inherent necessity in power system operation to minimize the cost as well as the accomplishment of load demand abundantly. The main purpose of ELD is to satisfy load demand with the minimization of cost. Distinct techniques have been used for resolving the ELD problem. This paper introduces a robust and effective technique named Artificial Eco System Optimization (AEO) Algorithm to solve ELD. AEO is a population-based optimizer stimulated by the flow of energy into the Earth's ecosystem. This algorithm shows three distinct functions of living organisms, including production, consumption, and decomposition. By accomplishing three operator producer, consumer, and decomposer whole algorithm works and balances between the exploitation and the exploration phases of the technique. For solving the ELD problem, AEO has been implemented on multiple test systems with an account of different restrictions and AEO has given better results than different several novels, previous and hybrid optimization techniques. The outcomes confirm the robustness, expediency, effectiveness, and efficacy of AEO in terms of computational time and vicinity to the global optimum solution. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to assess the reliability of closed-ring grids by combining the total loss of continuity approach and the classical Monte Carlo simulation. The proposed method is called the Modified Monte Carlo Simulation (MMCS). The MMCS method is tested by Roy Billinton Test System (RBTS) Bus-2 and Bus-4 in three different scenarios: radial, open-ring, and closed-ring. Besides, the method proposed is applied to a real 6-bus closed-ring distribution system. The sensitivity analysis based on fuzzy logic is applied to determine the uncertainties associated with the reliability input data. It is shown that the MMCS method is appropriate to assess the reliability of both open-ring and closed-ring systems, and the sensitivity analysis is crucial to draw the real picture of reliability assessment, and an essential tool for power utilities to determine the most risk parameters that significantly deteriorate system reliability. [ABSTRACT FROM AUTHOR]

The Phasor Measurement Unit (PMU) is a modern metering device installed to monitor and control the power system network. However, the number of PMUs and their placements ought to be optimized to satisfy the techno-economic demand. In this paper, the PMU placement problem has been expressed as a multi-objective problem. Modified whale optimization algorithm (MWOA) is proposed to solve Optimal Placement of PMUs (OPP) problem formulation aiming at minimizing the required number of PMU installation subjected to complete network observability and maximizing the reliability for better operation of power systems. Here, the simultaneous optimization of the two conflicting objectives is performed using a fuzzy-based modified whale optimization algorithm (FMWOA). Besides, single objective optimization problems with and without considering the zero-injection bus constraint and multi-objective optimization problem with zero injection bus constraint have been investigated. The proposed method is validated on small and larger test systems, namely IEEE 14, 30, 57, 118 bus systems, and the polish 2383-bus system. Also, the proposed algorithm results are compared with those of previously published for better clarity. [ABSTRACT FROM AUTHOR]

The solution of Combined Economic and Emission dispatch (CEED) problems aims to minimize the operating fuel cost and emission levels simultaneously, while satisfying load demand and operational constraints. The CEED problem can be formulated as a nonlinear optimization problem with equality and inequality operating constraints. Moth-flame optimization algorithm (MFO) is one of the newest bio inspired optimization techniques. However, this paper proposes a modified moth-flame optimization algorithm (MMFO) to find the optimal solution of CEED problems. MMFO is mainly based on the concept of MFO with modification the path of moths in new spirals around the flame. The developed MMFO algorithm can be used to improve the convergence characteristics of CEED optimal solutions compared to other optimization algorithms. The performance of MMFO is compared with different optimization techniques. Valve point effect, environmental emissions, and transmission line losses are included in the CEED analysis to provide more practical results. MMFO is validated using different standard test systems. The simulated results show the effectiveness and the superiority of the developed MMFO against other well-known optimization techniques. [ABSTRACT FROM AUTHOR]

The transmission system structure may sometimes be modified depending upon the power generation and demand at various locations in the power system. Usually, this leads to updates/changes in the relaying installations and makes the overall system to be more expensive. Therefore, it is vital to ensure the reliability of relaying installations with adaptiveness. This paper introduces an improved sequence current-based adaptive pilot relaying scheme. The scheme with its fixed settings can protect the compensated/uncompensated transmission networks with any structures against any type of faults with low impedance faults or high impedance arcing faults. The performance of the proposed scheme has been scrutinized using EMTDC/PSCAD simulation for almost all the adverse cases of faults for different test systems having different structures including a 9-bus WSCC system, IEEE 14-bus system, and TCSC-compensated line. The obtained results indicate that the scheme is robust, accurate, selective, and consistent for all the cases investigated. [ABSTRACT FROM AUTHOR]

—This paper provides a computational methodology based on monarch butterfly optimization (MBO) to find a solution to the problem of cost-based unit commitment (CBUC). The binary variables of unit commitment problems are handled by modifying the continuous-time nature of the monarch butterfly algorithm. Thermal unit generation, uptime, downtime, ramp rate limits as well as system reserve are considered in the test systems. The computational approach has many parts that not only minimize the cost function but also handle the mixed constraints of the commitment problem. The effect of thermal turbine valve-point loading is also taken into consideration. The computational technique has been used to solve a ten-unit original system and five scaled-up adaptations obtained from this base system. The results obtained are in agreement with the recent results available in the literature. Comparative analysis shows the effectiveness of the proposed MBO-based solution methodology in terms of operating costs and execution time in relation to other techniques. [ABSTRACT FROM AUTHOR]

The voltage stability analysis can be carried out using different continuation techniques. The continuation power flow that evaluates all power-flow solutions at different loading levels, is typically considered the most standard one. This approach is mainly based on two stages called predictor and corrector. The standard Newton–Raphson method is usually used at the corrector stage. In this paper, several corrector techniques based on efficient Newton-like methods are proposed in order to speed up the solution of continuation power flow. Consequently, two high order Newton-like methods as well as a fast corrector technique based on the Dishonest NR method have been proposed. A comprehensive study is addressed in order to check the suitability of the proposed corrector techniques compared with the standard Newton–Raphson (NR). Several small, medium, large and very large-scale test systems are used to achieve the validation. The obtained results prove the effectiveness and superiority of proposed techniques compared with the standard NR which conventionally used in corrector stage of the continuation power flow analysis in term of computational time. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to solving the problem of loss allocation by assigning the losses to generators and consumers, which are the two non-regulated agents of the market. This proposed method suggests assigning the losses of a network line to the nodes which are connected to it as a function of the direction of the active power flow through the line. The nodes with connected loads will be assigned the losses of the lines carrying incoming active power flows at the node, while the nodes with generators connected will be assigned the losses of the lines carrying outgoing power flows. This allocation will be weighted according to the number of allocations carried out in the rest of the network nodes and also taking into consideration the power injected into the node. This heuristic method is developed and illustrated with simple examples, both the procedure as the algorithm. The method has been tested on the IEEE 30 bus test system and the results have been compared with other methods so as to show its effectiveness. [ABSTRACT FROM AUTHOR]

The operation of distribution systems benefits from an efficient voltage and reactive power control, which nowadays is generally achieved by local and independent actions performed by voltage regulators, on-load tap changer transformers, and capacitor banks. However, the modernization of distribution systems has been accompanied by the integration of a communication infrastructure and new controllable equipment allowing the development of innovative procedures to control the voltage and reactive power. In this context, an alternative is the implementation of an Integrated Volt/Var Control (IVVC), consisting of the integration of voltage and reactive power controls in a centralized structure. This work investigates a hierarchical Volt/Var control methodology that considers the use of both local and centralized controls in a coordinated manner aiming to optimize distribution system operation and overcome the disadvantages of using either of the approaches separately. In this methodology, the centralized control acts when the local control is not enough, overriding its commands. The methodology is tested in a distribution system with photovoltaic generators and considers the use of inverters' advanced functions into the hierarchical control. The results show that the proposed methodology allows improvements in the performance of the test system operation increasing its efficiency. [ABSTRACT FROM AUTHOR]

Transmission system expansion leads to excessive short-circuit currents that exceed the capacity of circuit breakers. To avoid over short-circuit current; transmission system operators make various alterations in the transmission system by changing the topology of the system. The feeders can be distributed to different buses in substations through disconnecting coupling circuit breaker between buses. Having been interchanged, the transmission system may face up a lot of problems even in single outage. Therefore, the optimal positions of feeders in substations are important in order to maintain system security. However, this optimization problem has non-convex properties due to AC load flow equations and it has a multi-objective structure to provide the limitation of short-circuit current and security of N-1 contingency. The constraints are the short-circuit current, voltage and transmission line limits in the single contingency. In this paper, the Genetic Algorithm and Binary Particle Swarm Optimization methods were utilized to find a near-optimal bus layout. Algorithms coding was made with Python programming language and PSS/E program was used to obtain power flow and short-circuit data. The results of applying the methods to the IEEE 14-bus test system demonstrated the effectiveness of the methods to take overloads away and restrict short-circuit current and hold voltage in its limit. [ABSTRACT FROM AUTHOR]

Wide-area power system monitoring based on phasor measurement units allows collecting a set of physical variables for evaluating the system security and stability, as well as for detecting power system disturbances. However, trends, noise and non-Gaussian distribution in measurements are important challenges for carrying out the detection, localization and visualization of power system disturbances. In this paper, a methodology that combines independent component analysis with statistical indices for detecting and visualizing anomalous dynamic events from wide-area measurements is proposed. From the statistical indices, two charts are also proposed to provide a better understanding of the system disturbances. Finally, a set of simulated data obtained from a transient stability model of the New England/New York test system is used to demonstrate the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

A short-term electric power and heat generation augmentation planning (EPHGAP) is portrayed and evaluated here. The objective of EPHGAP is to find out the most cost-effective and dependable expansion plan for meeting the forecasted electrical power demand and heat demand over a long-range horizon while fulfilling a large number of technical, cost-effective, reliability, and social constraints. The EPHGAP problem is a big-dimensional highly constrained mixed integer nonlinear programing (MINLP) problem. The general algebraic modeling system (GAMS) environment has been used to implement the proposed formulation, and the EPHGAP problem is solved by using Basic Open-source Nonlinear Mixed Integer (BONMIN) solver. An archetypal test system with existing thermal power plants, cascaded hydropower plants, cogeneration units, heat-only units and candidate cogeneration units, and cascaded hydro plants is considered to evaluate the proposed methodology. Simulation outcomes of the test system have been matched up to those acquired by differential evolution and particle swarm optimization. It has been observed from the comparison that the recommended BONMIN solver has the capability to bestow with superior quality solution. [ABSTRACT FROM AUTHOR]

This paper presents a novel current injection-based Newton-Raphson power flow algorithm with new PV bus representation (rCINR − P V) for improving the convergence characteristics. In this proposed algorithm, rectangular coordinates are used to represent all non-linear current injection equations. Test results are produced to discuss the reasons behind the non-convergence of different PV bus representation schemes, also their performance comparison was done on the unbalanced 3-phase radial (18-Bus, 28-Bus, 84- Bus and 140-Bus) and meshed (6-Bus, 14-Bus, 24-Bus, 30-Bus, 57-Bus, 118-Bus and 300-bus, and 1354-Bus) test systems. Experimental results show that the proposed power flow method provides better convergence property for distribution system with a large number of PV buses. Also, the modification leads to a smaller Jacobian matrix and therefore reduces computational time. [ABSTRACT FROM AUTHOR]

This research proposes a parallel and distributed computation approach for the fast decoupled load flow (FDLF) analysis applicable to both transmission and distribution networks of large electrical power systems. In this approach, the overall repetitive FDLF computations are performed by the respective control centers identified for each sub-system, the sub-systems being formed by partitioning the system through a network tearing procedure splitting the identified buses. The data of each subsystem are stored at their own control centers and hence the subsystems are solved using message passing distributed memory architecture. The computations performed by the control centers in various sub-systems are coordinated from a regional control center. The investigations on IEEE 118 bus standard test system indicate that the proposed approach provides faster solution than the conventional approach, without affecting the solution accuracy. The effectiveness of the proposed technique over the conventional approach become more visible when it is applied for the load flow analysis of large scale systems spread over a wide geographical area. [ABSTRACT FROM AUTHOR]

This paper proposes a novel particle swarm optimization (PSO) algorithm with population reduction, which is called modified new self-organizing hierarchical PSO with jumping time-varying acceleration coefficients (MNHPSO-JTVAC). The proposed method is used for solving well-known benchmark functions, as well as non-convex and non-smooth dynamic economic dispatch (DED) problems for a 24 h time interval in two different test systems. Operational constraints including the prohibited operating zones (POZs), the transmission losses, the ramp-rate limits and the valve-point effects are considered in solving the DED problem. The obtained numerical results show that the MNHPSO-JTVAC algorithm is very suitable and competitive compared to other algorithms and have the capacity to obtain better optimal solutions in solving the non-convex and non-smooth DED problems compared to the other variants of PSO and the state of the art optimization algorithms proposed in recent literature. The source codes of the HPSO-TVAC algorithms and supplementary data for this paper are publicly available at . [ABSTRACT FROM AUTHOR]

Load shedding is an emergency strategy that mitigates substantial mismatch between the generation and the loads. It generally sustains system stability during/after severe disturbances. This article proposes robust, simple, and innovative Under-Frequency Load Shedding (UFLS) technique based on Multi-Objective Particle Swarm Optimization (MOPSO). MOPSO has the objectives of: minimizing the amount of the dropped load and maximizing the lowest swing frequency. The functionality and feasibility of the proposed MOPSO are corroborated via comprehensive comparison with traditional, adaptive, Single Objective PSO (SOPSO), and Genetic Algorithm (GA) UFLS schemes. IEEE 9-bus and 39-bus systems are used cases for examining the reliability, applicability, and viability of the proposed MOPSO. Different scenarios as: outage of single, multiple generating plants and load increase are applied in the test systems, while load shedding is executed via MOPSO, SOPOS, GA, traditional, and adaptive UFLS approaches. The DigSilent power factor software is used for simulating the test systems while subjected to the different disturbance levels. MATLAB is used for coding SOPSO, MOPSO, adaptive, and GA algorithms. The results show that MOPSO-based UFLS relay produces higher lowest swing frequency and lower amount of dropped load than SOPSO and GA. MOPSO requires less computation requirements than GA approach. [ABSTRACT FROM AUTHOR]

In this paper is proposed a reconfiguration methodology with the presence of Distributed Generation (DG), aimed at achieving the minimum power loss, minimum number of switching operation and minimum deviation of bus voltage while satisfying all constraints using improved shuffled frog leaping algorithm (ISFLA).The performance of the proposed method is examined on 33 and 69 bus IEEE test distribution systems. The ISFLA performance is evaluated with the well-known algorithm including of harmony search algorithm (HSA), refined genetic algorithm (GRA), particle swarm optimization (PSO), differential evolutionary (DE) and conventional SFLA. Simulation results showed that the total power loss and voltage bus minimum in primary distribution network can be reduced significantly. Also the results in different scenarios are showed that the simultaneous reconfiguration and DG placement method is better in less losses and also in more minimum voltage. Moreover, the ISFLA superiority is proved in comparison with the HAS, GRA, PSO, DE, and SFLA in view of more convergence speed and accuracy and also converges in less number iteration. Also, the performance of the proposed method is favorable compared to previous studies. [ABSTRACT FROM AUTHOR]

A static multipoint method to locate harmonic sources in high-voltage electric power systems based on the least median of squares approach is presented. Because of statistical robustness, the least median of squares method is used, even in the presence of multiple erroneous measurements. The special features of the method are described in this article. IEEE-30 bus test system with three harmonic sources and ± 1 % uniformly distributed erroneous measurements is solved with the least median of squares, Heydt's and Euclidean norm methods. Several harmonic sources are correctly located with the least median of squares method. The least median of squares approach estimated harmonic bus voltages and currents is close to the actual values. With Heydt's and the Euclidean norm methods the harmonic sources cannot be located in the presence of ± 1 % uniformly distributed erroneous measurements. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm to find the harmonic power flow path for every generator and demand is proposed. In the proposed algorithm, the exact knowledge of harmonic power values is not required to determine the path. Our approach is based on Bialek's tracing method, which specifies the contribution of each nodal generation/demand in power flow of a particular line. Our approach is faster than Bialek's method in terms of computation due to the fact that upstream and downstream distribution matrices as well as nodal demand and generation matrices have a much simpler structure. Our method resolves electricity tracing for harmonic problems in both upstream and downstream aspects, resulting in two sets of answers: one for the harmonic power flow path of generator nodes and the other for that of demand nodes. To illustrate our algorithm, a step-by-step solution to a sample case study is provided here using the proposed algorithm. To verify our method, the results of our algorithm for a sample 5-bus power network and the IEEE 14-bus test system are compared to those of Bialek's method. Finally, the proposed method is applied for harmonic frequency and used to find the path of harmonic power flow in a network. [ABSTRACT FROM AUTHOR]

The article presents the estimation of power distribution systems Expected Energy Not Supplied (EENS) index by incorporating time-varying load models of different customer sectors. An application of a new and efficient advanced Monte Carlo simulation (MCS) with controllable accuracy called Multilevel Monte Carlo (MLMC) method is proposed for this estimation. The purpose of the proposed method is to increase the simulation speed of EENS estimation. The method could be easily replaced by the traditional MCS-based estimation which requires huge computational effort for achieving high level of simulation accuracy. Five distribution networks with seven different load models of Roy Billinton Test System are chosen as test distribution systems. To verify the effectiveness of the proposed method, computational time and estimated values of EENS using MLMC method are compared to the results from MCS. The computation performance of EENS estimation can be influenced by different factors and criteria which are also explored in this study. The results presented in the article show that acceptable results can be obtained using the proposed method while substantial reduction of computational effort is also achieved. [ABSTRACT FROM AUTHOR]

In modern power systems, efficient methods like demand side management (DSM) are needed for handling the peak load management problem. An intelligent DSM approach not only gives advantages to utilities but also provides indirect benefits to generating companies. This article introduces a combined model of multi-objective dynamic optimal power flow (MODOPF) and a game theory-based DSM technique. In this article, a single utility company and multiple residential energy consumers are considered for the game theory-based DSM technique. Here, the day ahead load shifting DSM technique is implemented with the help of a day-ahead pricing strategy and an energy consumption game. The total generation cost and transmission losses are considered as the main objectives in the proposed MODOPF problem. These two objectives were optimized individually and simultaneously using harmony search (HS) algorithm with different DSM participation levels for the investigation of generation side benefits. The proposed combined model was tested on two different test systems such as IEEE 30 bus and 118 bus. From the simulation results, it is clear that the combined model consisting of MODOPF and DSM is able to achieve a better economic and secure operation when compared to MODOPF alone. [ABSTRACT FROM AUTHOR]

This article studies deterministic and stochastic algorithms for placing minimum number of phasor measurement units (PMUs) in a power system in order to locate any fault in the power system. The optimization problem is initially formulated in a mixed integer linear programing framework with binary-valued variables as well as in a binary integer linear programing model. Then, the optimization problem is formulated as an equivalent non-linear programing model, minimizing a quadratic objective function subject to equality non-linear constraints defined over a bounded and closed set. The problem is solved by using a Sequential Quadratic Programming algorithm. The non-linear program is illustrated with a 7-bus test system. Also, stochastic algorithms such as binary-coded genetic algorithm and particle swarm optimization have been implemented in solving the optimal PMU placement under fault condition. The accuracy of suggested algorithms is independent from the fault type and its resistance. The optimization models are applied to the IEEE systems. The numerical results indicate that the proposed algorithms locate minimizers at the optimal objective function value in complete agreement with those obtained by branch-and-bound algorithms. [ABSTRACT FROM AUTHOR]

In this article, a combined optimization approach (COA) based on Salp Swarm Algorithm (SSA) and loss sensitivity indices is proposed to determine the optimal allocation of shunt capacitors (SCs) in radial distribution networks (RDNs). SSA is considered a new efficient optimization algorithm. However, COA is mainly based on three-stage procedures that reduce the search space and the total computation time is reduced. In the first stage, two loss sensitivity factors called voltage loss sensitivity factor (VLSF) and reactive power loss sensitivity factor (QLSF) are employed to select the candidate buses. Then, these candidate buses are normalized (the buses with voltage magnitudes greater than 1.01 p.u. are eliminated from search space. Finally, the SSA optimization code is used to determine the optimal siting and size of SCs after candidate buses normalization. In this study, the minimization of power loss and energy cost are taken as objective functions. The proposed algorithm is validated using different standard distribution systems such as, 69-bus, 85-bus test systems. In addition, the application of the COA is applied on real radial distribution system of the East Delta Network (EDN) as a part of the unified Egyptian network. However, the numerical experiments proved that the proposed algorithm can generate optimal solutions for losses reduction and capacitor allocations with quality better than many existing optimization algorithms. [ABSTRACT FROM AUTHOR]

Distribution company (DISCOM) bids into day-ahead (DA) electricity market to serve the DA schedules of its loads put together along with distributed generation (DG) schedules. At real time (RT), the loads/DGs (participants) may deviate from their DA schedules and this deviation has to be settled at RT price. Any deviation by a participant on a feeder will change the total network losses. This leads to deviation penalty (cost) to DISCOM which should be allocated to the responsible participants. This deviation cost consists of two parts: first is due to deviation in DA power schedules and second is due to the change in network losses by these power deviations. In this article, the problem of allocating deviation cost is formulated as cooperative game and Shapley value is used to allocate this deviation cost. The deviation in schedules of DGs has also been modeled into game framework. The method has been tested on a system with different scenarios of power deviation of participants in RT. The results obtained are stable and consistent for both loads and DGs in deviation cost allocation. [ABSTRACT FROM AUTHOR]

Traditional overload protection depends on pre-set values and cannot reflect the current tolerance capability of the line. If the current of a line exceeds the setting value of its overload protection, then it will be subsequently tripped off and cause power flow transferring, which may trigger the cascade tripping of power grid. So it is of significant importance for the overload protection to accurately evaluate the real-time safety status of transmission line and coordinate with power system control to eliminate the overload. In this article, starting from the mechanism analysis of conductor heat transfer, a thermal network model is established by focusing on radial and circumferential heat transfer paths. The temperature rise response of the network node is obtained through nonlinear iteration. The calculation model, which is verified by a test platform, is better than standard models. Then, the current tolerance capability calculation model of the whole line is constructed on the basis of the thermal network and applied to improve the overload protection. The proposed multi-parameter overload protection can effectively prevent unnecessary tripping to avoid the expansion of accidents. Finally, the validity of the proposed protection is verified by the New England 10-machine 39-bus test system. [ABSTRACT FROM AUTHOR]

Intensive researches have been investigated the security aspect of optimal power flow (OPF) problem. The primary objective of them is to ensure the reliable and continuous supply to the consumers as economically as possible. Although all of these researches offer valuable solution to enhancing security constrained OPF (SCOPF), they avoided a discussion on the operation cost of power system versus the security constrains. The understanding of relationship between the operation cost and system security leads to make best decisions on tradeoffs between operating cost and system reliability. The main objective of this article is to solve preventive/corrective SCOPF (P/C-SCOPF) problem considering the expected power not served (EPNS) index as security constraint. Also, the relationship between operation cost and EPNS index is discussed in detail. In this article, well-known nondominated sorting genetic algorithm (NSGA) is used to determine the precise relationship between operating cost and the security constraint (EPNS), for the first time. This would result in illuminating information that can be utilized to make a reasonable decision on the best tradeoffs between operating cost and reliability of system. The proposed approach has been evaluated on IEEE 14 and 57 bus test systems and results have been discussed. [ABSTRACT FROM AUTHOR]

This paper presents a developed predictor formulation for performing the time-series power-flow simulation of balanced and unbalanced distribution systems. The developed technique uses the changes in reactive and active powers of loads during the 24 hr in order to predict the updated voltage magnitudes and phase angles, respectively. The Lagrange linear interpolation is used as a predictor approach in the developed formulation. The developed technique is compared with the traditional technique that uses the previous solution as predictor values for the next solution. The conventional and developed techniques are implemented into forward/backward sweep for the three-phase radial distribution power-flow algorithm. The iterations number and computation time of the power-flow algorithm are significantly reduced in the case of using the developed technique compared with the previous solution technique. To prove its effectiveness, the developed technique is adopted for IEEE test systems, such as the radial balanced 69-node and unbalanced IEEE 123-node feeder. All calculations are performed using C++ programming. [ABSTRACT FROM AUTHOR]

This paper presents a new fast control strategy method for enhancing the fault-ride-through performance of monopolar high voltage direct current systems in case of a DC line fault. The proposed method is solely based on a novel control strategy algorithm, which will be functional after detecting the DC internal faults. The new control method is able to prevent the DC voltage from becoming negative during the force alpha period and is also able to exceed the recovery speed of the system by switching the controlling method from current controller to gamma controller during the recovery process. These two facts are the main ideas behind the new control strategy that will improve the recovery process of the system by a great margin. To evaluate the reliability of the proposed method, the Hydro-Quebec monopolar high voltage direct current test system using MATLAB/SIMULINK environment is used. It will be shown that the proposed method is not only functional for recovering the system in case of any DC fault occurrence but also more economical and well applicable on the existing high voltage direct current networks. [ABSTRACT FROM AUTHOR]

—In this study, a hybrid algorithm which combines the NSGA-II with a modified form of the marginal histogram model Estimation of Distribution Algorithm (EDA), herein called the NSGA-II/EDA is proposed for solving the multi-objective economic/emission power dispatch problem. The goal is to improve the convergence while preserving the diversity properties of the obtained solution set. The effect of variable interaction on the marginal histogram EDA model is reduced by performing multi-scale Principal Component Analysis on the population of solutions. Also, the concepts of non-domination and elitism have been introduced into the marginal histogram model in order for it to handle multiple objectives. Several optimization runs were carried out on the standard multi-objective test problems, including the IEEE 30- and the 118-bus test systems. Standard metrics are used to compare the performance of the developed hybrid approach with that of other multi-objective evolutionary algorithms. The effectiveness of the proposed approach in improved convergence, with good diversity is demonstrated. [ABSTRACT FROM AUTHOR]

Carbon capture and storage technology is becoming a promising alternative to mitigate the CO2 emissions from the power generation sector. After retrofitting the conventional power plants with carbon capture devices and carbon transmission infrastructures, the operating characteristic of power plants will change. To adapt to the new dispatch background, this paper established a multi-period dispatch model with generation cost and carbon emission cost as objectives, and the operating characteristics of carbon capture power plants (CCPPs) as well as carbon transportation systems are taken into account. Finally, an integrated IEEE 118-bus test system combined with the 14-node carbon transmission system is applied to validate the effectiveness of the proposed model. Moreover, the effects of carbon transmission networks on the dispatch results are investigated and the sensitivity analysis of the carbon price and carbon transmission capacity is conducted on the test system. [ABSTRACT FROM AUTHOR]

Growing environmental concerns associated with electric power generation, and the awareness toward the use of renewable energy has caused widespread and rapid increase in the installation of wind-power systems. The uncertain and intermittent nature of wind power has led to growing problems in integrating wind power in power systems as the wind-power penetration continues to increase. One of the prime requirements of operating a power system with wind power is maintaining the system reliability by committing an appropriate amount of power from available generation sources in the lead time considered. Commitment of wind power is a very crucial task that requires accurate wind-power forecasting. This article presents a time series model to recognize the variability in wind and presents a conditional probabilistic method to quantify the wind-power commitment risk during system operation. The method is applied to assess the short-term operational risks with wind power and the operating capacity credits of a wind farm using the Roy Billinton Test System test system. [ABSTRACT FROM PUBLISHER]

The application of phasor measurement unit (PMU) measurements and a robust linear matrix inequality-based control based on a polytopic model of the system used to damp inter-area oscillations is investigated. The closed-loop eigenvalues are excluded from a region of the complex plane, guaranteeing that low-frequency modes must be damped. A 68-bus 16-generator system is used as a test system. Three DC lines, three static var compensators, and remote PMU frequencies as added inputs to selected power system stabilizers are used as the example control. Ten different system conditions are used as the vertices of the polytope. The system size is reduced using selective modal analysis. [ABSTRACT FROM AUTHOR]

The dynamic security-constrained dispatch of an electric power network is a difficult task facing an independent system operator mandated to provide equitable and fair transmission services in an open-market environment. In this article, a novel technique based on iterative stability-constrained optimum power flow is proposed. The particle swarm optimization methodology is employed to maximize the social welfare with consideration of static and dynamic functional operating constraints and dynamic loading margin requirements with respect to normal condition and contingencies. Furthermore, since the pattern of load increase is difficult to predict in the new market environment, a new method for determining the sensitive loading direction associated with a dynamic loading margin is proposed. An IEEE 14-bus test system with both supply and demand bidding is used to illustrate and test the proposed technique. [ABSTRACT FROM AUTHOR]

On-line determination of proximity of a power system to voltage collapse is essential for operating the system with an adequate security margin. This article presents a new method of estimating the voltage stability margin, which uses local measurements and calculates an index that is based on the basic definition of voltage stability. The proposed technique is simple and computationally less demanding. This technique uses the information about the current operating point through local signals and determines the voltage stability margin. It calculates the change in complex power (S) supplied to the load with change in load admittance (Y), i.e., dS/dY. The proposed method has been applied on the IEEE 14-bus and IEEE 57-bus test systems. The technique has been tested for a variety of operating conditions and compensations. The results show that the proposed method can accurately predict the proximity to voltage collapse at each bus. The method is computationally efficient and suitable for on-line monitoring of voltage stability margin. [ABSTRACT FROM AUTHOR]

Controlled splitting of an interconnected power system is the last defense line against wide-area blackout. As a special protection scheme, the methodology of system splitting is a comprehensive decision-making problem. This article introduces a novel approach for separation of the integrated power systems into several stable islands. The proposed method combines both the dynamic and static characteristics of interconnected power networks and determines the proper splitting schemes. The presented algorithm searches for proper islanding strategies using the Krylov projection method and a new optimization algorithm to find the proper splitting points such that the total load shedding is minimized. The method reduces the huge initial search space of islanding strategies by considering dynamic characteristics of integrated power systems. A spanning-tree-based Prim algorithm is used to find all possible combination of the islands. The speed of the proposed algorithm is remarkably high, and it can be used for real-time splitting of the power systems. The algorithm is applied to an IEEE 118-bus test system. Results show the effectiveness and capability of the method for determining fast and accurate proper islanding strategies. The stability of the islands is verified by time domain simulation. [ABSTRACT FROM AUTHOR]

A fuzzy set theory approach for handling parameter uncertainties in saddle node bifurcation analysis of power system voltage stability problem is proposed. Unlike the conventional way of assigning crisp values to parameters, a fuzzy membership distribution is assigned to model them. Advantages of the proposed scheme over that of the crisp parameter assignment are notable. Besides incorporating parameter uncertainties in the analysis, it also enables to foresee the uncertainties in state variables through a set of fuzzy patterns presented in this article. Numerical findings justifying the fuzzy set theory application to saddle node bifurcation analysis of IEEE 14-bus test system are presented in a concise manner. [ABSTRACT FROM AUTHOR]