Large Interconnected Power Systems Research Articles

Hilbert‐Huangtransform based fault identification and classification technique forACpower transmission line protection

In the modern power system, the fault identification and classification is one of the challenging tasks during high fault impedance due to low change in the magnitude of fault current from steady-state to fault inception. In this paper, a high impedance fault detection technique is proposed based on Hilbert-Huang transform (HHT). The energy for each phase is computed from the intrinsic mode function (IMF) of three-phase voltage/current signals. An average relay energy index (AREI) is proposed to detect the transmission line fault in the large interconnected power system. Furthermore, a fault classification technique is also proposed based on relay energy index (REI) of each phase of the three-phase voltage/current signals. The proposed HHT based fault detection technique is validated on standard WSCC 9 bus and IEEE 14 bus test power systems using PSCAD and MATLAB software. The simulation results reveal that the proposed Hilbert-Huang transform based fault identification and classification technique can be best suitable for protection of transmission lines during high impedance faults in complex and large AC power transmission system.

Power System Security Assessment and Enhancement: A Bibliographical Survey

Power system security assessment and enhancement are two major crucial issues in a large interconnected power system. System security can be classified on the basis of major functions that are carried out in control centers, namely system monitoring, contingency analysis and security enhancement. The key element involved in security assessment is contingency analysis. In real-time, all contingencies may not cause same severity level. To eliminate non-violation cases and select only critical cases, called contingency analysis, the idea of severity/performance indices seems to fulfill this need. Security enhancement incorporates security constrained optimal power flow (SCOPF) which ensures that system is operating at normal state by taking preventive and corrective control actions so that no contingencies result in violations. SCOPF recommends controller actions to optimize specific objective function such as fuel cost, power losses, emission that subject to a set of power system operating constraints. This paper presents a literature review on two topics which are reviewed in chronological order of appearance; security assessment and enhancement. We explore both traditional and soft computing techniques for assessing system security and enhancement of the power system and also identify key areas for future research.

Rotor Angle and Voltage Stability Analysis with Fault Location Identification on the IEEE 9 Bus System

Transient stability is very imperative in multi-machine interconnected power systems in order to scrutinize and analyze the system’s performance and response. Rotor angle stability and voltage stability are studied in this paper. By applying three-phase symmetrical faults, the transient stability of the IEEE 9 bus system is studied. A characteristic double hump is analyzed in the response of the generator, which is nearer to the fault location. By analyzing the characteristic double hump, the fault location in a large interconnected power system can be determined. It is shown that, as the fault is cleared, the system takes some finite time to return to its prior state. IEEE 9 bus system is chosen as a test system, which standard parameters. MATLAB Simpower System toolbox is used for load flow and transient stability analysis.

Power flow model with flat frequency control and load characteristic for voltage stability indices

The growing of power systems with massive interconnection becomes more complicated for reliable and economical operation under dynamic as well as steady-state operating conditions. Therefore, it is desirable to develop techniques for evaluating the voltage stability condition with the implementation of the voltage stability index and the minimum singular value of the system. This paper proposes an approach a model of power flow incorporating the generator controls with considering load characteristics of flat frequency control (FFC) scheme in large interconnected power systems. Results on a 24-Bus EHV practical system is presented for illustration of power flow solution.

Improved DE Algorithm for Power System Stabilizer for Damping Low Frequency Osci llations

In the large interconnected power system, maintaining the Small signal stability of the system is of more concern, for the stable, secure and reliable operation. This paper proposes an Improved Differential Evolution (DE) Algorithm based Optimal Power system stabilizer (PSS) for damping the low frequency oscillations. Enhancing the damping of system is formulated as the optimization problem. DE/Best Mutation Operator is adopted for producing the mutation vector, to augment the convergence rate of DE algorithm. The effectiveness of the proposed approach has been tested in Single Machine Infinite Bus (SMIB) system under different operating conditions. The time response evaluations has justified the superiority of the proposed approach for damping the oscillations and thereby improving the Small signal stability of the system.

Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller.

Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller.

Online coherency identification and stability condition for large interconnected power systems using an unsupervised data mining technique

Identification of coherent generators and the determination of the stability system condition in large interconnected power system is one of the key steps to carry out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends, the larger amount data available and the non-linear dynamic behaviour of the frequency measurements often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. This paper presents a novel online unsupervised data mining technique to identify coherent groups, to detect the power system disturbance event and determine status stability condition of the system. The innovative part of the proposed approach resides on combining traditional plain algorithms such as singular value decomposition (SVD) and K-means for clustering together with new concept based on clustering slopes. The proposed combination provides an added value to other applications relying on similar algorithms available in the literature. To validate the effectiveness of the proposed method, two case studies are presented, where data is extracted from the large and comprehensive initial dynamic model of ENTSO-E and the results compared to other alternative methods available in the literature.

Important Issues and Results When Considering the Stochastic Representation of Wind Power Plants in a Generation Optimization Model: An Application to the Large Brazilian Interconnected Power System

Wind power has an increasing share of the Brazilian energy market and may represent 11.6% of total capacity by 2024. For large hydro-thermal systems having high-storage capacity, a complementarity between hydro and wind production could have important effects. The current optimization models are applied to dispatch power plants to meet the market demand and optimize the generation dispatches considering only hydroelectric and thermal power plants. The remaining sources, including wind power, small-hydroelectric plants and biomass plants, are excluded from the optimization model and are included deterministically. This work introduces a general methodology to represent the stochastic behavior of wind production aimed at the planning and operation of large interconnected power systems. In fact, considering the generation of the wind power source stochastically could show the complementarity between the hydro and wind power production, reducing the energy price in the spot market with the reduction of thermal power dispatches. In addition to that, with a reduction in wind power and a simultaneous dry-season occurrence, this model, is able to show the need of thermal power plants dispatches as well as the reduction of the risk of energy shortages.

A statistical jacobian application for power system optimization of voltage stability

<p>Despite a tremendous development in optimal power flow (OPF), owing to the obvious complexity, non-linearity and unwieldy size of the large interconnected power systems, several problems remain unanswered in the existing methods of OPF. Seizing specific topics for maximizing voltage stability margin and its implementation, a detailed literature survey discussing the existing methods of solution and their drawbacks is presented in this research. The phenomenon of voltage collapse in power systems, methods to investigate voltage collapse, and methods related to voltage stability are briefly surveyed. Finally, the study presents a statistical method for analyzing a power system through eigenvalue analysis in relation to the singular values of the load flow Jacobian. Future study may focus on changes in theories in conjunction with large power systems.</p>

A Dynamic State Estimator Based Control for Power System Damping

Interarea power oscillation damping enhancement in large interconnected power systems is often accomplished using supplementary controls at the synchronous machines involved and with the use of flexible ac transmission system devices. The power system literature has demonstrated that wide area signals could be more effective than the local signals for these controllers. In some cases where phasor measurement units are used, all the required control signals may not be available. To alleviate these cases, control signals are obtained using estimated signals from a “dynamic state estimator,” and a robust supplementary controller is deployed. In this paper, the cited strategy is illustrated using a static var compensator. The feasibility of the proposed method has been demonstrated on the IEEE 50-generator test system.

Interarea Oscillation Damping Control Using High-Voltage DC Transmission: A Survey

High-voltage direct current (HVDC) transmission lines are increasingly being installed in power systems around the world, and this trend is expected to continue with advancements in power electronics technology. These advancements are also bringing multiterminal direct current (MTDC) systems closer to practical application. In addition, the continued deployment of phasor measurement units makes dynamic information about a large power system readily available for highly controllable components, such as HVDC lines. All these trends have increased the appeal of modulating HVDC lines and MTDC systems to provide grid services in addition to bulk power transfers. This paper provides a literature survey of HVDC and MTDC damping controllers for interarea oscillations in large interconnected power systems. The literature shows a progression from theoretical research to practical applications. There are already practical implementations of HVDC modulation for lines in point-to-point configuration, although the modulation of MTDC systems is still in the research stage. As a conclusion, this paper identifies and summarizes open questions that remain to be tackled by researchers and engineers.

ALFC of hybrid multi-generation power system using UC and TCPS by ANFIS control technique

ABSTRACTThis paper reveals the impact of an ultra-capacitor (UC) and thyristor control phase shifter (TCPS) on frequency stability of large hybrid interconnected power system. The impact of UC and TCPS has been studied for general purpose hybrid generated multi areas power system. Further to this, an adaptive neuro fuzzy inference system (ANFIS) is is proposed for automatic load frequency control (ALFC). Thermal and reheat thermal plants are connected in Area-1 and area-2, whereas area-3 has hydro plant and area-4, 5, 6 consists of nuclear power plant, diesel power and gas turbine plant, respectively. A micro grid based on Solar Photovoltaic (PV) system and fleet of electric vehicle (EV) system is developed and integrated with load side of area-1 for load management in interconnected grid. Effect of Small load change and large load change are discussed in separate cases. The controllers are tuned by adding sliding surface to enhance the performance. A comparison between ANFIS and PI-based control approaches with and without UC and TCPS exhibits the superiority of ANFIS controller by integrating UC and TCPS. The results of the proposed control technique are compared with already published results.

New approach of automatic generation control based on absolute rotor angle droop control

It is being increasingly recognised that the decentralised secondary frequency regulation (SFR) is more suitable for the expanding power systems. Decentralised SFR can more rapidly restore system frequency and damp generator rotor oscillations, as well as relieve the information-exchange stress between the control centre and widespread generators. Compared to other previously proposed methods, rotor angle droop (RAD) control is simpler and more straightforward. Similar to primary frequency control, the RAD controllers mainly distribute load variance among generators based on their rated capacity. However, they can rapidly and autonomously restore the system frequency without the intervention of a dispatching centre, which makes it more convenient for distributed generation (such as photovoltaic) to participate in frequency regulation. This study shows that the unbalance value between load forecast and real demand can be calculated through absolute rotor angle deviation. This calculated amount can then be reallocated to achieve more economical results. By calculating the area control error and changing the generation in different areas, the tie-line power flow (PF) can be controlled similarly. However, the fluctuation on the tie-line PF can be decreased since generators near the loads bear slightly more burden. This is helpful for tie-line control in large interconnected power systems.

Hierarchical Interactive Risk Hedging of Multi-TSO Power Systems

For a large interconnected power system with multiple transmission system operators (TSOs), online inter-TSO synergistic interactions are increasingly being required to hedge against system-wide operating risk. To address this issue, a novel hierarchical interactive risk hedging (HIRH) method is proposed. Under the established framework, the upper level coordinator can interact with the lower level local TSOs through target and response variables. Decentralized and interdependent risk hedging models are formulated, including a system-wide coordination optimization model for the coordinator and a set of preventive-corrective combined risk-aware optimal power flow models for local TSOs. To tackle the computational complexity of the multiple problems, a two-level decomposition-coordination algorithm based on analytical target cascading and Benders decomposition is developed. A case study of a modified three-area RTS-96 system demonstrates the effectiveness of the proposed HIRH.

Damped Nyquist Plot for a pole placement design of power system stabilizers

This paper proposes a new frequency domain control design method through the use of a modified Nyquist diagram with an embedded partial pole-placement capability. The proposed Damped Nyquist Plot (DNP) method evaluates the open loop transfer function (OLTF) along a line of constant damping ratio to provide a graphical tool to design power system stabilizers (PSS). The graphical tool shows how the closed loop poles move around this damping ratio line for different choices of PSS parameters, all of them placing a selected pair of complex-conjugate poles at the same desired point in the complex plane. New formulas are developed to determine the exact PSS parameters that promote the several possibilities of partial pole placement considering the parameter ranges used in tuning practice. These formulas can also be used for phase compensation of conventional methods of PSS design, such as GEP or Residue Angle Compensation. Multiple PSSs can be tuned using the DNP method sequentially. The proposed method is applied to two stabilization examples, the first of tutorial nature and the second is the large actual Brazilian Interconnected Power System.

DECOMPOSITION METHOD FOR SOLUTION OF A MULTI-AREA POWER DISPATCH PROBLEM

Large interconnected power systems are decomposed into areas or zones based on the size of the electric power system, network topology and geographical location. Multi-area economic emission dispatch (MAEED) problem is an optimisation task in power system operation for allocating amount of generation to the committed units within these areas. Its objective is to minimise the fuel cost subject to the power balance, generators limits, transmission lines, and tie-line constraints. The solution of the MAEED problem in the conditions of deregulation is difficult, due to the model size, nonlinearity, and interconnections. It determines the amount of power that can be economically generated in the areas and transferred to other areas if it is needed without violating tie-line capacity constraints. High-performance computing (HPC) gives possibilities for reduction of the problem complexity and the time for calculation by the use of parallel processing for running advanced application programs efficiently, reliably and quickly.

A New Wide Area Intelligent Multi-agent Islanding Detection Method for Implementation in Designed WAMPAC Structure

In this paper, a new multi-agent distributed neural network based islanding detection algorithm is presented. The proposed algorithm is placed in the designed wide area monitoring, control, and protection system (WAMPAC) as one of its applications. Therefore, firstly, the proposed WAMPAC structure and its main parts including WAMS, WACS and WAPS are highlighted that are designed to have a situational awareness to perform both of control and protection actions. To have fast and accurate responses at different contingencies such as WAMS equipment failures or data transmission latency, the multi-agent concept, and neural network algorithm are used at some of the WAMPAC control and protection applications. To show the effectiveness of the designed algorithms, the islanding detection application and its algorithms are described in detail. The proposed method is applied to the IEEE-118 bus power system and its performance is demonstrated at various disturbances. It is shown that the islanding necessity is predicted correctly that helps to perform corrective actions such as controlled islanding execution to avoid wide area blackout. In addition, the algorithm response is increased significantly that contributes to overcome the possible drawbacks of WAMS in large interconnected power systems.

Coordination of directional overcurrent relays in the interconnected power systems using effective tuning of harmony search algorithm

In the optimum coordination of Directional Overcurrent Relays (DOCRs), the appropriate relay settings, namely, Plug Setting (PS) and Time Multiplier Setting (TMS), are selected to minimize the operating time of relays subject to various coordination and boundary constraints. In the large interconnected power systems, the key issue with DOCRs protection is to achieve correct relay coordination with satisfying all coordination constraints. In this paper, the parameters of Harmony Search Algorithm (HSA) are tuned to effectively solve the relay coordination problem on five different test cases. Also, the relay coordination problem is formulated as Linear Programming Problem (LPP), Non-linear Programming Problem (NLPP) and Mixed-Integer non-linear programming Problem (MINLPP). In addition, the superiority of proposed method is demonstrated by comparing the obtained results with those obtained by the Genetic Algorithm (GA), hybrid GA-Nonlinear Programming (GA-NLP), Firefly Algorithm (FFA), and Cuckoo Search Algorithm (CSA).

Fuzzy unscented transform for uncertainty quantification of correlated wind/PV microgrids: possibilistic–probabilistic power flow based on RBFNNs

The probabilistic power flow (PPF) of active distribution networks and microgrids based on the conventional power flow algorithms is almost impossible or at least cumbersome. Always, Mont Carlo simulation is a reliable solution. However, its computation time is relatively high that makes it unattractive to be a reliable solution for large interconnected power systems. This study presents a new method based on fuzzy unscented transform and radial basis function neural networks (RBFNN) for possibilistic-PPF in the microgrids including uncertain loads, correlated wind and solar distributed energy resources and plug-in hybrid electric vehicles. When sufficient historical data of the system variables is not available, a probability density function might not be defined, while they must be represented in another way namely possibilistically. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution methodology is needed. The proposed method exploits the ability of RBFNN and unscented transform in non-linear mapping with an acceptable level of accuracy, robustness and reliability. Simulation results for the proposed PPF algorithm and its comparison with the reported methods for different test power systems reveals its efficiency, accuracy, robustness and authenticity.