This paper focuses on the impact of control system on small-signal stability of the Hybrid Multi-Infeed HVDC(H-MIDC) system, in which the Line-Commutated-Converter based HVDC (LCC-HVDC) and Voltage-Sourced-Converter based HVDC (VSC-HVDC) links feed into an AC system in close mutual proximity. A comprehensive linearized small-signal model is developed for an H-MIDC system. Based on the eigenvalue analysis and participation factor analysis, the inherent oscillatory modes of the H-MIDC system are revealed. Then, the impact of the most sensitive control system parameters on the least-damped modes are investigated. The studies show that (i) the proportional gains of PLL functions of LCC and VSC stations, and AC voltage outer loop controller of VSC station are highly coupled, and presents the most sensitivity to the least damped modes; (ii) parameters of PLL in LCC station, and outer loop of AC voltage control and PLL in VSC station can highly impact the damping of the oscillatory modes and even cause instability, and (iii) smaller PLL gains in LCC and VSC stations, and smaller proportional gain of AC voltage control of VSC station are preferable and can enhance damping of dominant modes.

This study investigates the viability and the associated operational implications of an all converter interfaced generation system operating at constant frequency using grid forming converters. Grid-forming converters set the frequency and voltage of the grid and enable its operation under constant frequency, thus creating a new paradigm for the frequency response of a power system. Power sharing between converters is addressed while assessing the implications of operating the bulk power system at a constant frequency. Case studies performed on a small 9-bus system as well as a large 2000-bus system, using a developed positive sequence as well as a detailed three-phase point on wave models of a grid forming converter are discussed.

This study examines a modal condition to cause inter-area, low-frequency, electromechanical power oscillations in an interconnected power system with two subsystems. The modal condition being examined is the closeness of two electromechanical oscillation modes from each subsystem on the complex plane, which is referred to as open-loop modal resonance. The analysis in this study indicates that under the condition of open-loop modal resonance, the electromechanical oscillation modes of the interconnected power system are located at approximately opposite positions on the complex plane with respect to the resonant electromechanical oscillation modes of the subsystems. Hence, when open-loop modal resonance occurs, one electromechanical oscillation mode of the interconnected power system must have reduced damping. In this study, the damping reduction in the inter-area, low-frequency power oscillations caused by open-loop modal resonance is demonstrated using example power systems. An incident of inter-area, low-frequency electromechanical power oscillations that occurred in an actual large-scale power system in China is examined. The examination results indicate that the poorly damped, inter-area, low-frequency power oscillation incident was caused by open-loop modal resonance.

Residential air conditioning loads with energy storage characteristics can quickly participate in the demand response, making it an important demand response resource. It can improve resource utilisation and the flexibility of power grid operation through the effective regulation. However, the degree of residential air conditioning to participate in demand response is affected by the outdoor temperature, users’ comfort settings, thermal storage and insulation properties of buildings. Moreover, the difficulty of assessing the demand response potential is further increased by the uncertainty of the influencing factors. To guide the residential air conditioners to participate in the power grid operation, the aggregated air conditioner model is established to describe the relationship among the total power, the external environment, and the indoor temperature. The demand response potential model is established from the amount and the duration of demand response. The effects of outdoor temperature, indoor temperature adjustment and the number of air conditioners participating in the response are quantitatively evaluated. Finally, the accuracy of the aggregated model and demand response potential model are verified by numerical simulation.

High level of delivered power quality (PQ) is becoming one of the key performance indicators for both contemporary and future power networks. The increased proliferation of converter connected generation and load in power networks, increased sensitivity to network disturbances of some of these new types of devices and requirements for more flexible operation of power networks led to the revision of some of PQ standards and introduction of modified or in some cases new requirements for PQ compliance. Although almost all PQ phenomena, with exception of voltage transients, are well defined and appropriate thresholds for individual phenomena are set in international standards, there is no standardised nor commonly accepted way to describe and evaluate the overall PQ performance at buses. This study presents an analytic hierarchy process (AHP) inspired methodology for assessing the overall PQ performance at a bus based on several different PQ phenomena considered simultaneously. Compound bus PQ index is defined using AHP to present the overall PQ performance at the bus with respect to voltage sag, harmonics and voltage unbalance. The application of the methodology is illustrated on a 295 bus generic distribution network.

The controllers are used to reduce fluctuations in frequency deviations and tie-line power flow exchange of an interconnected power system due to load and voltage disturbances. This study proposes a control strategy based on model predictive control (MPC) procedures with various design schemes for an unequal two-area interconnected power system. The study model comprises voltage excitation and frequency loops with necessary interactions between them. Flywheel as an energy storage system along with wind energy are engaged in the model under study. The tuning parameters of MPC-based controllers are obtained by quadratic problem solver. The validity of the proposed MPC-based controllers is extensively confirmed using the simulation results under different disturbance conditions such as different loadings and voltage changes. The effectiveness of the MPC based on controllers is compared to classical controllers and recent controllers based on optimisation techniques such as genetic algorithm. In addition, the quality specifications of the dynamic responses of the anticipated MPC-based controllers are reported to signify their values. The quality indices along with comparative performance point out the good performance of the demonstrated MPC-based controllers for various estimated novel scenarios.

This study develops a new multi-stage (dynamic) approach for the co-planning of power and gas systems to deal with variable renewable energy resources (VREs). The model is formulated using a stochastic programming framework to accurately capture the unfolding of both short and long-term uncertainties faced by power and gas systems. The effects of high renewable energy penetration and renewable energy uncertainty in both systems are assessed while determining the optimal investment and operation decisions in several stages of the planning horizon. To prove the benefits of the proposed approach, the authors compare the results of the authors’ framework with other methods used in the literature. The effectiveness of the framework is validated on a realistic case of Queensland, Australia, in which both networks are driven to capture the link between these systems and to accommodate the state's unique features of renewable availability. The results demonstrate that their dynamic approach provides more robust outcomes compared to other methods as it allows adapting the expansion plans to unexpected changes in the future. The analysis also shows that a transition towards renewable energy presents a higher cost, different investment strategies, and lower gas-fired consumption compared to the terminal renewable target.

Short-term voltage stability (SVS) is a serious issue in modern power systems. In China, the East China Power Network is especially vulnerable to short-term voltage instability due to its increasing dependence on electrical power from external through high-voltage direct current (HVDC) transmission lines. To study the SVS, a criterion/index is first required to evaluate the SVS of power systems. However, the currently used practical criteria cannot effectively evaluate the influence of controlling strategies (such as regulating dynamic VAR reservation) of power systems. Therefore, a practical and continuous SVS index (SVSI) based on voltage curves is proposed in this study. The proposed SVSI can quantify the extent of SVS in power systems, thus can be used in the optimisation target of preventive control for improving the SVS of power systems. Moreover, the SVSI consists of three components, and each component reflects a feature of the voltage curve in terms of SVS. The SVSI is essentially a model-free method for assessing the SVS of power systems, so it is robust. Three verifying cases and one application case are presented to show the validity of the SVSI and the feasibility of the SVSI in practical applications.

The power transformer is one of the vital and substantial elements of each country's power grid which not only require high investment, but they are also important in terms of economy, social, political, and strategy. Since this equipment is exposed to different electrical and mechanical winding faults during operation, they should be monitored continuously. One of the main monitoring methods is the use of frequency response analysis (FRA), which has a high sensitivity. The main challenge of the FRA is that the detecting task of the status of the transformer is done by a specialist and with a visual evaluation of the records. To overcome this problem, first, frequency responses in the healthy and present states are calculated through simulation of electrical and mechanical fault in the winding of the transformer and then, new statistical methods are used to interpret FRA results based on the obtained transfer function. In this study, for the first time, clustering analysis and cross-correlation methods are used to interpret FRA results for clustering and diagnosis of different short circuits turns, axial displacement, and radial deformation. Results and simulations verify ability and advantage of these methods in detection and determination of different faults.

This study examines the sub-synchronous oscillations (SSOs) caused by the control of a line commutated converter high-voltage, direct current (LCC HVDC) transmission line in a power system with a doubly fed induction generator for the wind power generation. The examination is based on a closed-loop interconnected model consisted of an open-loop HVDC subsystem and an open-loop subsystem of power generation. The open-loop modal coupling is the modal condition that an SSO mode of the open-loop HVDC subsystem is close to an open-loop SSO mode of the power generation subsystem on the complex plane. Analysis in the study indicates that under the condition of open-loop modal coupling, the LCC HVDC line may induce strong dynamic interactions which degrade the damping of power system SSOs. An SSO index is derived to assess the degree of damping degradation of the SSOs, which can be used to identify the SSO instability risk brought about by the control of LCC HVDC transmission line. Hence, the mechanism of why the control of LCC HVDC transmission line may cause power system SSOs is revealed from the perspective of open-loop modal coupling. Study cases are presented to demonstrate and validate the analysis and conclusions made in the study.

This study proposes a multi-stage restoration strategy to solve the service restoration problem in distribution systems considering the uncertainty of outage duration. Furthermore, it also proposes a restoration index defined in terms of (i) priority of the load restored, (ii) number of switching operations, and (iii) estimated likelihood of the restoration solution to assist the utility in enhanced decision-making. Service restoration is formulated as a single objective optimisation problem considering the maximising of the restoration index as the only objective. A decentralised multi-agent system method is developed to solve the service restoration problem considering controlled islanding of distributed generators. The uncertainty of outage duration is estimated using the maximum entropy principle-based on the cause of the fault. Exhaustive case studies are implemented on a small 38 bus and a large 119 bus test distribution system to demonstrate the effectiveness of the proposed multi-stage restoration strategy to restore the system under outage duration uncertainty.

The authors propose an intelligent real-time pricing (RTP)-based energy consumption scheduling model, which is especially applicable to more active and balanced demand management in a smart grid. Most previous research studies have not considered the incentive for subscribers who are more likely to move their consumption schedule to the off-peak period. Therefore, they considered the degree of the sacrifice made by each subscriber to determine an individualised price. As a result, the electricity unit price charged to each subscriber is different. An appropriate incentive coefficient is identified using a genetic algorithm and applied to the RTP model. This approach draws more active rescheduling of the energy consumption and enhances the fairness of a network. Compared with non-scheduling and day-ahead scheduling, the authors algorithm reduces the subscribers’ total cost by an average of 24.9 and 15.9%, and increases the corresponding average fairness of the network by 16.7 and 5.4%, respectively. Moreover, they achieved a significant reduction in the peak-to-average-ratio.

In this study, a novel accurate fault location algorithm is presented for two-terminal transmission lines. In contrast to conventional methods, the proposed algorithm not only utilises asynchronous samples recorded during the fault but also needs no line parameters and identification of fault type. In the presented fault-locating method, distributed parameter line model in the time domain and asynchronous data of the terminals collected during fault are applied. Fault locating as an optimisation problem has been solved by the heuristic algorithm of teaching–learning-based optimisation, and the decision variables of fault location, synchronisation time and line parameters are estimated simultaneously. The performance of the presented method was tested with different fault incidence angles, a variety of fault types, and under several system and fault conditions using the MATLAB/Simulink. These tests demonstrate the high accuracy of the presented method. Also, the proposed method did not show any dependence on the impedance of the Thevenin sources of the two sides of the line, the fault impedance and the fault incidence angle. Furthermore, it was not affected by the high resistance of the fault and the network structure.

Let-through energy (LTE) refers to the I ² t or Joule energy that a conductor is exposed to during a fault on the feeder. This energy is influenced by the magnitude of the fault current and time it takes for the protection system to clear the fault. If the LTE exceeds the conductor thermal energy limit, the conductor will get damaged. This concept of LTE evaluation is applied to the inverse definite minimum time (IDMT) current based back-up protection elements on a multisource high-voltage feeder in a hypothetical and actual network. Another method to calculate the relay operating time for IDMT relays was developed based on an average disk speed of electromechanical over-current relay and the proportionality of its speed to the magnitude of the fault current. This method was incorporated into a software application to generate results. These results allow the user to evaluate the conductor LTE exposure, total fault time exposure, the effect of instantaneous fault clearing and the application of auto-reclose cycles. An energy-area evaluation was applied to quantify and evaluate small protection settings changes. The conclusion is that LTE analysis on back-up protection should be considered for high-voltage feeders to ensure that the conductors are protected.

Wind and solar have major share among the growing renewable penetration, due to their extensive availability and improved technologies. Both wind and solar generation are highly uncertain and intermittent as compared to system load. The increased number of such uncertain and intermittent variables necessitates complex multivariate operational strategies for system operation. A compilation of different uncertain and intermittent variables such as load, wind and solar generation, to a single uncertain variable called net load, reduces system operational planning complexity. Net load is the difference between total load and renewable generation. Thus, conventional generation units have to be scheduled for net load. Prior knowledge about net load can help optimum operational planning such as generation scheduling and power system flexibility estimations. There have been significant advancement in load and renewable generation forecasting over the last decades. Still, there is little attention towards net load forecasting (NLF). This study proposes a novel NLF model using Gumbel copula based joint probability distribution for load, wind and solar generation forecasting error aggregation. Gumbel copula covers all extreme forecasting errors due to max-stable property. Proposed model uses modified Grey index models for forecasting. Results show that proposed model has strong potential in very short-term NLF.