Showing papers on "Power-flow study published in 2019"

On Identification of Distribution Grids

Abstract: Large-scale integration of distributed energy resources into distribution feeders necessitates careful control of their operation through power flow analysis. While the knowledge of the distribution system model is crucial for this analysis, it is often unavailable or outdated. The recent introduction of synchrophasor technology in low-voltage distribution grids has created ample opportunity to learn this model from high-precision, time-synchronized measurements of voltage and current phasors at various locations. This paper focuses on joint estimation of admittance parameters and topology of a polyphase distribution network from the available telemetry data via the lasso, a method for regression shrinkage and selection. We propose tractable convex programs capable of tackling the low-rank structure of the distribution system and develop an online algorithm for early detection and localization of critical events that induce a change in the admittance matrix. The efficacy of these techniques is corroborated through power flow studies on four three-phase radial distribution systems serving real and synthetic household demands.

Unified Power Flow Algorithm for Standalone AC/DC Hybrid Microgrids

Abstract: Recent studies on power flow analysis of islanded microgrids have become increasingly important and different solutions have been proposed. However, they are often limited to only ac or only dc microgrids and hence, the power flow must be solved separately. This paper proposes a straightforward and efficient method to solve power flows of hybrid ac/dc microgrids simultaneously, based on the well-established Newton–Raphson approach. It considers the lack of slack bus during islanded operation, the coupling of ac frequency and dc bus voltage, as well as the droop control of distributed generators. To achieve power sharing between the ac and dc subgrids, this method incorporates the interlinking converter droop constants in the equation. The algorithm was tested on modified hybrid microgrids involving multiple ac–dc subgrids. The results are compared against results from time-domain simulations to validate the algorithm’s accuracy. The proposed technique can be easily implemented to aid the design and planning process of hybrid microgrids.

Power Flow Analysis in DC Grids: Two Alternative Numerical Methods

Abstract: This express brief proposes two new iterative approaches for solving the power flow problem in direct current networks as efficient alternatives to the classical Gauss–Seidel and Newton–Raphson methods. The first approach works with the set of nonlinear equations by rearranging them into a conventional fixed point form, generating a successive approximation methodology. The second approach is based on Taylors series expansion method by using a set of decoupling equations to linearize the problem around the desired operating point; these linearized equations are recursively solved until reach the solution of the power flow problem with minimum error. These two approaches are comparable to the classical Gauss–Seidel method and the classical Newton–Raphson method, respectively. Simulation results show that the proposed approaches have a better performance in terms of solution precision and computational requirements. All the simulations were conducted via MATLAB software by using its programming interface.

An Improved Defender–Attacker–Defender Model for Transmission Line Defense Considering Offensive Resource Uncertainties

Abstract: Developing efficient strategies for defending electric power systems against attacks is a major concern for contemporary power grids, especially when uncertainties are involved. This paper addresses the allocation of the defensive resource to minimize the damage when there are uncertainties regarding the resource that the attacker has. A multiple-attack-scenario (MAS) defender–attacker–defender (DAD) model is proposed by extending the conventional trilevel DAD model. The proposed model considers the uncertainties related to the offensive resource and the interactions involving the security personnel at the top-level, the attacker at the middle-level, and the power system operator at the bottom-level. The column-and-constraint generation algorithm is implemented by decomposing the MAS DAD model into an upper-level problem for the security personnel, and a lower-level problem for the attacker involving the optimal power flow analysis-based corrective power redispatch implemented by the power system operator. Case studies are performed based on the IEEE RTS79 and 57-bus systems, and the results validate that the proposed method is able to minimize the damage when uncertainties are involved in the offensive resource. This paper can offer meaningful insights into power system protection involving uncertainties.

Distribution Network Reconfiguration Using Selective Firefly Algorithm and a Load Flow Analysis Criterion for Reducing the Search Space

Abstract: This paper proposes an alternative to solve the distribution network reconfiguration (DNR) problem, aiming real power losses' minimization. For being a problem that has complexity for its solution, approximate techniques are adequate for solving it. Here, the proposition is a technique based on the firefly metaheuristic, named selective firefly algorithm, where the positioning of these insects is compressed in a selective range of values. The algorithm is applied to the DNR, and all its implementation and adequacy to the problem studied are presented. To define the search space, the methodology presented initially considers a set of candidate switches for opening based on the studied systems' mesh analysis. To reduce these possibilities, a refinement through a load flow analysis criterion (LFAC) is proposed. This LFAC considers the real power losses on each branch for a configuration with all switches closed, then, selecting possible switches to elimination from the set previously established. To demonstrate the behavior and the viability of the LFAC, it was initially applied on a 5 buses' and 7 branches' system. Also, to avoid getting stuck on results that may be considered not good, a disturbance resetting the population is set to occur every time a counter reaches a pre-defined number of times that the best solution does not change. Results found for simulations with 33, 70, and 84 buses are presented and comparisons with selective particle swarm optimization (SPSO) and selective bat algorithm (SBAT) are made.

A Novel Load Flow Algorithm for Islanded AC/DC Hybrid Microgrids

Abstract: This paper proposes a novel branch-based load flow approach for isolated hybrid microgrids. This evolving network configuration involves the application of a distinctive operational philosophy that poses significant challenges with respect to conventional load flow techniques. Hybrid microgrids are characterized by small-rating, droop-based distributed generators (DGs) and by variable but coupled frequency and dc voltage levels. In particular, the absence of a slack bus that results from the small DG rating impedes the application of traditional techniques such as branch-based methods. To overcome these limitations, a modified branch-based approach provided the basis for the development of the proposed algorithm. The new algorithm solves the load flow sequentially by dividing the problem into two coupled ac and dc subproblems. The coupling criterion is established by modeling and updating the power exchange between the subgrids, hence enabling an accurate and efficient formulation of the subproblems. For each subproblem, a modified directed forward-backward sweep has been developed to perform the load flow analysis based on consideration of the individual characteristics of each subgrid. Case study results demonstrate that the algorithm is applicable and effective for the steady-state analysis of several operational factors associated with an isolated hybrid microgrid system: 1) load changing; 2) converter outages; and 3) the probabilistic nature of renewable generation and loads.

Solar PV Grid Power Flow Analysis

Abstract: As the unconstrained integration of distributed photovoltaic (PV) power into a power grid will cause changes in the power flow of the distribution network, voltage deviation, voltage fluctuation, and so on, system operators focus on how to determine and improve the integration capacity of PV power rationally. By giving full consideration to the static security index constraints and voltage fluctuation, this paper proposes a maximum integration capacity optimization model of the PV power, according to different power factors for the PV power. Moreover, the proposed research analyzes the large-scale PV grid access capacity, PV access point, and multi-PV power plant output, by probability density distribution, sensitivity analysis, standard deviation analysis, and over-limit probability analysis. Furthermore, this paper establishes accessible capacity maximization problems from the Institute of Electrical and Electronics Engineers (IEEE) standard node system and power system analysis theory for PV power sources with constraints of voltage fluctuations. A MATLAB R2017B simulator is used for the performance analysis and evaluation of the proposed work. Through the simulation of the IEEE 33-node system, the integration capacity range of the PV power is analyzed, and the maximum integration capacity of the PV power at each node is calculated, providing a rational decision-making scheme for the planning of integrating the distributed PV power into a small-scale power grid. The results indicate that the fluctuations and limit violation probabilities of the power system voltage and load flow increase with the addition of the PV capacity. Moreover, the power loss and PV penetration level are influenced by grid-connected spots, and the impact of PV on the load flow is directional.

Real Time Security Assessment of the Power System Using a Hybrid Support Vector Machine and Multilayer Perceptron Neural Network Algorithms

Abstract: In today’s grid, the technological based cyber-physical systems have continued to be plagued with cyberattacks and intrusions. Any intrusive action on the power system’s Optimal Power Flow (OPF) modules can cause a series of operational instabilities, failures, and financial losses. Real time intrusion detection has become a major challenge for the power community and energy stakeholders. Current conventional methods have continued to exhibit shortfalls in tackling these security issues. In order to address this security issue, this paper proposes a hybrid Support Vector Machine and Multilayer Perceptron Neural Network (SVMNN) algorithm that involves the combination of Support Vector Machine (SVM) and multilayer perceptron neural network (MPLNN) algorithms for predicting and detecting cyber intrusion attacks into power system networks. In this paper, a modified version of the IEEE Garver 6-bus test system and a 24-bus system were used as case studies. The IEEE Garver 6-bus test system was used to describe the attack scenarios, whereas load flow analysis was conducted on real time data of a modified Nigerian 24-bus system to generate the bus voltage dataset that considered several cyberattack events for the hybrid algorithm. Sising various performance metricion and load/generator injections, en included in the manuscriptmulation results showed the relevant influences of cyberattacks on power systems in terms of voltage, power, and current flows. To demonstrate the performance of the proposed hybrid SVMNN algorithm, the results are compared with other models in related studies. The results demonstrated that the hybrid algorithm achieved a detection accuracy of 99.6%, which is better than recently proposed schemes.

A Distributed Control Method Based on a Voltage Sensitivity Matrix in DC Microgrids With Low-Speed Communication

Abstract: A distributed control method is proposed to improve the power sharing performance of bidirectional distributed generators (BDGs) and the voltage regulation performance of a dc bus in a dc microgrid (MG). To analyze the structural characteristics of a dc MG, voltage sensitivity analysis based on power flow analysis is presented. Based on this, a distributed control method using a voltage sensitivity matrix is proposed. The proposed method uses information received through the communication line and performs the droop gain variation method and voltage shifting method without additional controllers. This approach achieves improved power sharing and voltage regulation performance without output transient states, even at slow communication speed. The proposed method is implemented through an experimental environment consisting of two BDGs, a load, and a non-dispatchable distributed generator in a four-bus ring type model. The experimental results demonstrate improved power sharing accuracy and voltage regulation performance.

Educational Applications of Large Synthetic Power Grids

Abstract: This paper describes the use of large electric grids in university electric power system courses. Since much actual power system information is not publicly available, the application of public domain synthetic grids developed by the authors is presented including a 2000-bus grid. Discussion of the educational applications utilized in a senior level class are given for power flow analysis and sensitivity, economic dispatch, contingency analysis, optimal power flow (OPF), security-constrained OPF, transient stability, and real-time dynamic operations. In each of these, the application of the large synthetic grids give students insights and experience with cases closer to actual power systems in complexity and size.

On the Properties of the Compound Nodal Admittance Matrix of Polyphase Power Systems

Abstract: Most techniques for power system analysis model the grid by exact electrical circuits. For instance, in power flow study, state estimation, and voltage stability assessment, the use of admittance parameters (i.e., the nodal admittance matrix) and hybrid parameters is common. Moreover, network reduction techniques (e.g., Kron reduction) are often applied to decrease the size of large grid models (i.e., with hundreds or thousands of state variables), thereby alleviating the computational burden. However, researchers normally disregard the fact that the applicability of these methods is not generally guaranteed. In reality, the nodal admittance must satisfy certain properties in order for hybrid parameters to exist and Kron reduction to be feasible. Recently, this problem was solved for particular cases of monophase and balanced triphase grids. This paper investigates the general case of unbalanced polyphase grids. First, conditions determining the rank of the so-called compound nodal admittance matrix and its diagonal subblocks are deduced from the characteristics of the electrical components and the network graph. Second, the implications of these findings concerning the feasibility of Kron reduction and the existence of hybrid parameters are discussed. In this regard, this paper provides a rigorous theoretical foundation for various applications in power system analysis.

Uncertainty-Aware Computational Tools for Power Distribution Networks Including Electrical Vehicle Charging and Load Profiles

Abstract: As new services and business models are being associated with the power distribution network, it becomes of great importance to include load uncertainty in predictive computational tools. In this paper, an efficient uncertainty-aware load flow analysis is described which relies on generalized polynomial chaos and stochastic testing methods. It is described how the method can be implemented in order to account for real data-based load profiles due to two different usage models: residential loads and electrical vehicle charging profiles. Hence, it is shown how some relevant information affecting the quality of service can be deduced by means of non-elementary post-processing computations. The proposed technique is tested by using a benchmark scenario for typical European low voltage networks, considering the variation of both residential loads and EV charging profiles. The results are compared with the same simulation done by means of the Monte Carlo methodology. The consideration done during the analysis will be useful to clarify the application of the methodology but also to understand the effect of load variations on the grid characteristic quantities.

Probabilistic Power Flow Analysis for Hybrid HVAC and LCC-VSC HVDC System

Abstract: Some innovative works have been done to probabilistic power flow (PPF) analysis for hybrid HVAC and LCC-VSC HVDC system in this paper. Firstly, a unified method considering precise model of converters is proposed to solve a general deterministic power flow (DPF) calculation including hybrid LCC (Line Current Converter) and VSC (Voltage Source Converter), the pure VSC-MTDC (Voltage Source Converter-Multiple Terminal Direct Current) and pure LCC system. Meanwhile, with a large amount of renewable energy sources integrated to the main grid through DC grids, it will impose a stochastic impact on the secure operation of such hybrid AC/DC grids. Therefore, it becomes necessary to model the probabilistic uncertainties and analyze their effects on the operation of hybrid AC/DC systems under different control modes. Nevertheless, most power flow analysis methods for hybrid AC/DC system are still deterministic in nature. Therefore, a probabilistic method based on the combination of Nataf transformation and Latin hypercube sampling (LHS) is developed and proposed to solve this complex PPF problem in an efficient manner, which considers correlated various probabilistic uncertainties, e.g. wind speeds, solar radiations and loads following different types of probability distribution. Finally, the effectiveness of the unified DPF method is validated in a modified IEEE 14-bus system, while the proposed PPF is verified in a modified IEEE 118-bus system and the effects of uncertainties on the diverse operation modes of hybrid AC/DC grids are discussed as well.

Weather-Dependent Power Flow Algorithm for Accurate Power System Analysis Under Variable Weather Conditions

Abstract: Accurate power flow analysis is essential to system operators for planning, design, analysis, and control of power networks. The accuracy of power flow analysis can be increased significantly by including the weather-dependent characteristics of the system. In this paper, a novel weather-dependent power flow algorithm is proposed and studied in comparison to the very well-known conventional power flow. The weather-dependent power flow algorithm is novel in the sense that it is explicitly parameterized in terms of typically available measured weather parameters (ambient temperature, solar irradiance, wind speed, and wind angle) to perform a fully coupled weather-dependent power flow analysis. Using this algorithm, the IEEE 30-bus power network was studied utilizing real weather data by performing three year-long steady-state time-series power flow analyses. The study demonstrates that the proposed weather-dependent power flow algorithm accurately estimates the branch resistances, the system states (current and voltages), the power losses, the branch flows, and the branch loadings. These are made possible because the proposed algorithm accurately estimates branch conductor temperature due to the coupling of power flow with the nonlinear heat balance model. An analysis of the computational complexity of the proposed algorithm is also presented.

Direct Active and Reactive Power Control of Three-Phase Inverter for AC Motor Drives With Small DC-Link Capacitors Fed by Single-Phase Diode Rectifier

Abstract: This paper proposes a power controller used for three-phase inverters with small dc-link capacitors fed by a single-phase diode rectifier. The effect of the reactive power was investigated based on a power flow analysis between a dc-link and three-phase inverter. These results enable the development of a direct active/reactive power controller in discrete time instead of adopting a classical proportional-integral (PI)-type current regulator, which directly leverages the total power flow of the system. A suitable reactive power selection method was presented to improve the overall system efficiency. The command voltage vector at each discrete time step can be simply and intuitively determined by an inverter power without requiring motor current-regulating PI gains and additional control functions. The proposed controller regulates an average motor velocity/airgap torque while simultaneously shaping a grid-side current with a high power factor and low harmonics to meet IEC61000-3-2 requirements. The proposed structure can be applied to three-phase inverters for a broad family of ac motors, such as induction and permanent magnet synchronous motors.

Nested backward/forward sweep algorithm for power flow analysis of droop regulated islanded microgrids

Abstract: In this study, nested backward/forward sweep (NBFS) algorithm, is proposed to solve the load flow problem of islanded microgrids. The proposed algorithm is designed in such a way that the voltage magnitude of the angle reference bus and the system frequency become additional variables in the power flow analysis. In the absence of the slack bus, new loops and equations are introduced in the proposed backward/forward sweep (BFS) method to fulfil the requirement of droop characteristics in the power flow analysis. In each loop of the proposed algorithm, modified equations of BFS are employed to update the voltages of every bus except angle reference bus (slack bus). The voltage of angle reference bus and the system frequency are updated at the end of each loop operation. The proposed NBFS method is applied on several test systems including IEEE 22-bus, 38-bus, 69-bus, and 160-bus and the obtained results are compared with the result obtained from other BFS-based algorithms including direct BFS and modified BFS, Jacobian-based algorithms including Newton trust region (NTR) algorithm and modified Newton -Raphson (MNR) algorithm, and time-domain simulation in PSCAD/EMTDC. The proposed algorithm for droop-regulated AC microgrid exhibits faster convergence with better accuracy as compare to other algorithms.

Distribution network reconfiguration using feasibility-preserving evolutionary optimization

Abstract: Distribution network reconfiguration (DNR) can significantly reduce power losses, improve the voltage profile, and increase the power quality. DNR studies require implementation of power flow analysis and complex optimization procedures capable of handling large combinatorial problems. The size of distribution network influences the type of the optimization method to be applied. Straightforward approaches can be computationally expensive or even prohibitive whereas heuristic or meta-heuristic approaches can yield acceptable results with less computation cost. In this paper, a customized evolutionary algorithm has been introduced and applied to power distribution network reconfiguration. The recombination operators of the algorithm are designed to preserve feasibility of solutions (radial structure of the network) thus considerably reducing the size of the search space. Consequently, improved repeatability of results as well as lower overall computational complexity of the optimization process have been achieved. The optimization process considers power losses and the system voltage profile, both aggregated into a scalar cost function. Power flow analysis is performed with the Open Distribution System Simulator, a simple and efficient simulation tool for electric distribution systems. Our approach is demonstrated using several networks of various sizes. Comprehensive benchmarking indicates superiority of the proposed technique over state-of-the-art methods from the literature.

Implicit Continuous Newton Method for Power Flow Analysis

Abstract: This letter proposes an implicit form of the continuous Newton method to solve the power flow problem. The implicit formulation prevents the need to factorize the inverse of the Jacobian matrix of the power flow equations and allows exploiting implicit integration solvers. The backward Euler method is utilized in this letter for its L-stability and numerical robustness, which is independent of the step size. A 21 177-bus model of the ENTSO-E transmission system serves to show the performance of the proposed technique and to compare it with conventional methods, considering both well-posed and ill-conditioned scenarios.

A Sequence-Component-Based Power-Flow Analysis for Unbalanced Droop-Controlled Hybrid AC/DC Microgrids

Abstract: This paper proposes a generalized and efficient power-flow algorithm for islanded hybrid ac/dc microgrids. The algorithm considers the microgrid operational aspects, i.e., absence of a slack bus, unbalanced ac subgrid, droop-controlled ac and dc voltages and ac frequency, and coupling between the ac frequency and dc voltage through interlinking converters. To attain high computational efficiency, the algorithm adopts three features. First, it models the ac subgrid elements in sequence components, thereby dividing the subgrid's set of equations into three smaller sets for faster parallel solution. This approach also accurately represents the different types of ac distributed generators. Second, the algorithm sequentially solves for the power-flow variables of the ac and dc subgrids, thus reducing the number of equations to be solved simultaneously, once again for further computational cost alleviation. Third, the algorithm implements the quadratically convergent Newton–Raphson technique to solve the decoupled sets of equations. The proposed algorithm is validated through comparisons with time-domain simulations, in MATLAB/Simulink, for test hybrid ac/dc microgrids of different configurations. Moreover, three case studies are introduced to examine the proposed algorithm's effectiveness in solving large-scale microgrids, to investigate its limits-enforcement capabilities, and to evaluate its performance as compared to conventional methods.

Optimal Power Flow for Transmission Power Networks Using a Novel Metaheuristic Algorithm

Abstract: In the paper, a modified coyote optimization algorithm (MCOA) is proposed for finding highly effective solutions for the optimal power flow (OPF) problem. In the OPF problem, total active power losses in all transmission lines and total electric generation cost of all available thermal units are considered to be reduced as much as possible meanwhile all constraints of transmission power systems such as generation and voltage limits of generators, generation limits of capacitors, secondary voltage limits of transformers, and limit of transmission lines are required to be exactly satisfied. MCOA is an improved version of the original coyote optimization algorithm (OCOA) with two modifications in two new solution generation techniques and one modification in the solution exchange technique. As compared to OCOA, the proposed MCOA has high contributions as follows: (i) finding more promising optimal solutions with a faster manner, (ii) shortening computation steps, and (iii) reaching higher success rate. Three IEEE transmission power networks are used for comparing MCOA with OCOA and other existing conventional methods, improved versions of these conventional methods, and hybrid methods. About the constraint handling ability, the success rate of MCOA is, respectively, 100%, 96%, and 52% meanwhile those of OCOA is, respectively, 88%, 74%, and 16%. About the obtained solutions, the improvement level of MCOA over OCOA can be up to 30.21% whereas the improvement level over other existing methods is up to 43.88%. Furthermore, these two methods are also executed for determining the best location of a photovoltaic system (PVS) with rated power of 2.0 MW in an IEEE 30-bus system. As a result, MCOA can reduce fuel cost and power loss by 0.5% and 24.36%. Therefore, MCOA can be recommended to be a powerful method for optimal power flow study on transmission power networks with considering the presence of renewable energies.

Current injection-based Newton–Raphson power-flow algorithm for droop-based islanded microgrids

Abstract: The power-flow analysis of droop-based islanded microgrid (DBIMG) is a growing research area. The conventional power-flow techniques have been difficult to employ in DBIMG due to the non-existence of reference bus (slack bus). To address this issue, a current injection Newton–Raphson based novel algorithm is proposed. The proposed algorithm chooses system frequency and voltage magnitude of the reference bus as additional variables in power-flow formulation. The proposed algorithm takes into account three operating modes of distributed generators viz. Droop control, PQ and PV . The linear equations cover the droop characteristics of the DGs, while non-linear equations cover power-flow equations of the system. The proposed algorithm has been executed on two test systems viz. 6-bus system and 38-bus system. To show the effectiveness and robustness of the proposed algorithm, the performance of the proposed algorithm is also examined for the different loading conditions and different R/X ratios of the line of the test systems. The obtained solutions have also been compared with the solutions obtained by other Newton–Raphson based algorithms reported in the literature and PSCAD. The comparative analysis shows better efficiency and superior convergence of the proposed algorithm.

Deployment of Distributed Generation with D-FACTS in Distribution System: A Comprehensive Analytical Review

Abstract: In this paper, a comprehensive review of the distribution system (DS) with Distributed Generation (DG) and Distribution Flexible AC Transmission System (D-FACTS) allocation for enhancement of volta...

Existence of Explicit and Unique Necessary Conditions for Power Flow Insolvability in Power Distribution Systems

Abstract: This paper proposes an explicit necessary condition which guarantees the existence and uniqueness of power flow insolvability in the active distribution networks. Compared to the existing methods, the proposed condition shows better result for the power flow solution space boundary limit. The solution space for each node voltage has been plotted into a closed contour region, where the power flow solution exists. Based on derived solution criteria, a new index is presented to analyze the sensitivity of the system with load change in case of power flow solution. As the proposed method depends only on the present set of data, hence it can be used as a tool for real-time power flow analysis with lesser computational burden. The proposed theoretical derivation has been confirmed with numerical experiments over IEEE 13, 123 bus benchmark distribution systems and a real Indian distribution grid system.