Abstract:Estimating the potential load curtailments as a result of hurricane is of great significance in improving the emergency response and recovery of power grid. This paper proposes a three-step sequential method in identifying such load curtailments prior to hurricane. In the first step, a twin support vector machine (TWSVM) model is trained on path/intensity information of previous hurricanes to enable a deterministic outage state assessment of the grid components in response to upcoming events. The TWSVM model is specifically used as it is suitable for handling imbalanced datasets. In the second step, a posterior probability sigmoid model is trained on the obtained results to convert the deterministic results into probabilistic outage states. These outage states enable the formation of probability-weighted contingency scenarios. Finally, the obtained component outages are integrated into a load curtailment estimation model to determine the expected potential load curtailments in the grid. The simulation results, tested on the standard IEEE 118-bus system and based on synthetic datasets, illustrate the high accuracy performance of the proposed method.

Abstract:Increasingly frequent natural disasters and man-made malicious attacks threaten the power systems. Improving the resilience has become an inevitable requirement for the development of power systems. The importance assessment of components is of significance for resilience improvement, since it plays a crucial role in strengthening grid structure, designing restoration strategy, and improving resource allocation efficiency for disaster prevention and mitigation. This paper proposes a component importance assessment approach of power systems for improving resilience under wind storms. Firstly, the component failure rate model under wind storms is established. According to the model, system states under wind storms can be sampled by the non-sequential Monte Carlo simulation method. For each system state, an optimal restoration model is then figured out by solving a component repair sequence optimization model considering crew dispatching. The distribution functions of component repair moment can be obtained after a sufficient system state sampling. And Copeland ranking method is adopted to rank the component importance. Finally, the feasibility of the proposed approach is validated by extensive case studies.

Abstract:The power and transportation systems are urban interdependent critical infrastructures (CIs). During the post-disaster restoration process, transportation mobility and power restoration process are interdependent, and their functionalities significantly affect other well-beings of other urban CIs. Therefore, to enhance the resilience of urban CIs, successful recovery strategies should promote CI function cooperatively and synergistically to distribute goods and services efficiently. This paper develops an integrative framework that addresses the challenges of enhancing the recovery efficiency of urban power and transportation systems in short-term recovery period. Specifically, the post-storm recovery process is considered as a scheduling problem under the constraints representing crew dispatch, equipment and fuel limit. We propose a new framework for co-optimizing the recovery scheduling of power and transportation systems, respecting precedency requirement and network constraints. The advantages and benefits of co-optimized recovery scheduling are validated in a testing system.

Abstract:The existing microgrid operation schemes do not consider the dynamic performance of frequency?in the islanded operation of microgrids. When an islanded microgrid encounters a disturbance, the sudden power mismatch could impose security risks or even a system collapse. To address such a challenge, this paper proposes the primary frequency response rescheduling (PFRR) approach. For a certain operation interval, the PFRR will optimally reschedule the distributed generators (DGs) with non-zero mechanical inertia and adjust the battery power. And the objective is to limit the rate-of-change-of-frequency (ROCOF) and to maintain the post-disturbance frequency nadir above a prescribed threshold. The effectiveness of the proposed strategy is verified by a case study on the IEEE 123-node test feeder system and the time-domain simulation in MATLAB Simulink.

Abstract:This paper deals with optimal scheduling of networked microgrids (NMGs) considering resilience constraints. The proposed scheme attempts to mitigate the damaging impacts of electricity interruptions by effectively exploiting NMG capabilities. A three-stage framework is proposed. In Stage 1, the optimal scheduling of NMGs is studied through determining the power transaction between the NMGs and upstream network, the output power of distributed energy resources (DERs), commitment status of conventional DERs as well as demand-side reserves. In Stage 2, the decisions made at Stage 1 are realized considering uncertainties pertaining to renewable generation, market price, power consumption of loads, and unintentional islanding of NMGs from the upstream network and resynchronization. Stage 3 deals with uncertainties of unintentional islanding of each MG from the rest of islanded NMGs and resynchronization. The problem is formulated as a mixed-integer linear programming problem and its effectiveness is assured by simulation studies.

Abstract:Modern power delivery systems are rapidly evolving with high proliferation of power-electronic (PE)-interfaced distributed energy resources (DERs). Compared to the conventional sources of generation, the PE-interfaced DERs, e.g., solar and wind resources, are attributed substantially different characteristics such as lower overload capability and limited frequency response patterns. This paper focuses on effective management and control mechanisms for PE-interfaced DERs in power distribution systems with high penetration of renewables, particularly under fault, voltage-sag, load variations, and other prevailing conditions in the grid. Aiming at the solutions to enhance the system performance resilience, we introduce an advanced model predictive control (MPC) based scheme to control the DER units, minimize the impact of transients and disruptions, speed up the response and recovery of particular metrics and parameters, and maintain an acceptable operation condition. The performance of the suggested control scheme is tested on a modified IEEE 34-bus test feeder, where the proposed solution demonstrates its effectiveness to minimize the system transient during faults, with an enhanced grid-edge and system-wide resilience characteristics in voltage profiles.

Abstract:This paper develops a comprehensive framework to analyze the impact of energy storage on improving the resilience of distribution systems against hurricanes. This paper first develops a spatio-temporal model of progressing hurricane when making landfall that can be used to anticipate outage scenarios caused by the gust-wind speed. An optimization model is then developed for optimizing the operation of distribution systems during hurricane that captures both pre-outage and post-outage network operation constraints. Numerical simulations are performed on the modified IEEE 33-bus distribution system with real hurricane data in Houston to demonstrate the effectiveness of the proposed model.

Abstract:Participation of distributed energy resources in the load restoration procedure, known as intentional islanding, can significantly improve the distribution system reliability. Distribution system reconfiguration can effectively alter islanding procedure and thus provide an opportunity to supply more demanded energy and reduce distribution system losses. In addition, high-impact events such as hurricanes and earthquake may complicate the procedure of load restoration, due to disconnection of the distribution system from the upstream grid or concurrent component outages. This paper presents a two-level method for intentional islanding of a reconfigurable distribution system, considering high impact events. In the first level, optimal islands are selected according to the graph model of the distribution system. In the second level, an optimal power flow (OPF) problem is solved to meet the operation constraints of the islands by reactive power control and demand side management. The proposed problem in the first level is solved by a combination of depth first search and particle swarm optimization methods. The OPF problem in the second level is solved in DIgSILENT software. The proposed method is implemented in the IEEE 69-bus test system, and the results show the validity and effectiveness of the proposed algorithm.

Abstract:Affected by the nonlinear time-varying factors due to fault scenarios, protection relaying, and control measures, the dynamic behaviors of a power system may be significantly different from the results of previous methods. In order to analyze the oscillation characteristics of complex power systems more accurately and suppress the low frequency oscillation more effectively, this paper improves the trajectory section eigenvalue method. Firstly, the time response of a system is obtained by numerical simulation in a given fault scenario. Secondly, the algebraic variables are substituted to the differential equations along the trajectory. Thus, the original time-varying differential-algebraic equations are approximated by a set of linear ordinary differential equations, which can be updated along the trajectory. On this basis, this paper proposes a method to extract instantaneous features of the oscillation from the micro perspective. The non-equilibrium points with strong nonlinearity or critical eigenmodes are identified by the proposed method. The simulation test results of the IEEE 3-machine 9-bus system and the New England system illustrate the validity of the proposed method.

Abstract:To guarantee the reliable power supply, the expected operation of all the components in the power system is critical. Distance protection system is primarily responsible of isolating the faulty section from the healthy part of the grid. Failure in protection devices can result in multiple conflicting alarms at the power grid operation center and complex events analysis to manually find the root cause of the observed system state. If not handled in time, it may lead to the propagation of the faults/failures to the adjacent transmission lines and components. With availability of the synchronized measurements from phasor measurement units (PMUs), real-time system monitoring and automated failure diagnosis is feasible. With multiple adverse events and possible data anomalies, the complexity of the problem will be escalated. In this paper, a PMU based algorithm is presented and discussed to detect the root cause of the failure in transmission protection system based on the observed state, e.g. multiple line tripping, breaker failures. The failure diagnosis algorithm is further enhanced to come up with the fully functional version of the failure diagnosis tool, which is tailored for the cases in which the PMU anomalies are present. In the developed algorithm the validity of the PMU data is critical; however, such causes as communication errors or cyber-attacks might lead to the PMU data anomalies. This issue is well-addressed in this paper and some major types of anomaly detection methods suitable for PMU data are discussed. Results show that the ensemble approach has some distinct advantages in data anomaly detection compared to the previously used standalone algorithms. Additionally, the enhanced failure diagnosis method is developed to clean the inaccurate data in case of the anomaly in measured voltage magnitudes. Finally, both original and enhanced versions of the tool are tested on 96-bus test system using the real-time OPAL-RT simulator. The results show the accuracy of the enhanced tool and its advantages over the primary version of the tool.

Abstract:A wavelet-based power management system is proposed in this paper with a combination of the battery and ultracapacitor (UC) hybrid energy storage system (HESS). The wavelet filter serves as a frequency-based filter for distributing the power between the battery and UC. In order to determine the optimal level of wavelet decomposition as well as the optimal activation power of the wavelet controller, an optimization procedure is established. The proposed frequency-based power management system moderates the usage of battery current, consequently improving its lifetime. Compared with the conventional threshold-based power management systems, the proposed system has the advantage of enhanced battery and UC power management. A LiFePO4?battery is considered and its life loss is modeled. As a case study, an electric motorcycle is evaluated in the federal test procedure (FTP) driving cycle. Compared with a conventional energy storage system (ESS) and a state of available power (SoP) management systems, the results show an improvement for the battery lifetime by 115% and 3%, respectively. The number of battery replacements is increased, and the energy recovery is improved. The 10-year overall costs of the proposed HESS strategy using wavelet are 1500 dollars lower, compared with the ESS.

Abstract:This paper proposes an adaptive segmentation method as a market clearing mechanism for peer-to-peer (P2P) energy trading scheme with large number of market players. In the proposed method, market players participate in the market by announcing their bids. In the first step, players are assigned to different segments based on their features, where the balanced?k-means clustering method is implemented to form segments. These segments are formed based on the similarity between players, where the amount of energy for trade and its corresponding price are considered as features of players. In the next step, a distributed method is employed to clear the market in each segment without any need to private information of players. The novelty of this paper relies on developing an adaptive algorithm for dividing large number of market players into multiple segments to enhance scalability of the P2P trading by reducing data exchange and communication overheads. The proposed approach can be used along with any distributed method for market clearing. In this paper, two different structures including community-based market and decentralized bilateral trading market are used to demonstrate the efficacy of the proposed method. Simulation results show the beneficial properties of the proposed segmentation method.

Abstract:Interval prediction of wind power, which features the upper and lower limits of wind power at a given confidence level, plays a significant role in accurate prediction and stability of the power grid integrated with wind power. However, the conventional methods of interval prediction are commonly based on a hypothetic probability distribution function, which neglects the correlations among various variables, leading to decreased prediction accuracy. Therefore, in this paper, we improve the multi-objective interval prediction based on the conditional copula function, through which we can fully utilize the correlations among variables to improve prediction accuracy without an assumed probability distribution function. We use the multi-objective optimization method of non-dominated sorting genetic algorithm-II (NSGA-II) to obtain the optimal solution set. The particular best solution is weighted by the prediction interval average width (PIAW) and prediction interval coverage probability (PICP) to pick the optimized solution in practical examples. Finally, we apply the proposed method to three wind power plants in different Chinese cities as examples for validation and obtain higher prediction accuracy compared with other methods, i.e., relevance vector machine (RVM), artificial neural network (ANN), and particle swarm optimization kernel extreme learning machine (PSO-KELM). These results demonstrate the superiority and practicability of this method in interval prediction of wind power.

Abstract:The increasing penetration of wind power brings great uncertainties into power systems, which poses challenges to system planning and operation. This paper proposes a novel probabilistic load flow (PLF) method based on clustering technique to handle large fluctuations from large-scale wind power integration. The traditional cumulant method (CM) for PLF is based on the linearization of load flow equations around the operating point, therefore resulting in significant errors when input random variables have large fluctuations. In the proposed method, the samples of wind power and loads are first generated by the inverse Nataf transformation and then clustered using an improved K-means algorithm to obtain input variable samples with small variances in each cluster. With such pre-processing, the cumulant method can be applied within each cluster to calculate cumulants of output random variables with improved accuracy. The results obtained in each cluster are combined according to the law of total probability to calculate the final cumulants of output random variables for the whole samples. The proposed method is validated on modified IEEE 9-bus and 118-bus test systems with additional wind farms. Compared with the traditional CM, 2m+1 point estimate method (PEM), Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS) based MCS, the proposed method can achieve a better performance with consideration of both computational efficiency and accuracy.

Abstract:A challenge faced by protection and planning engineers is the development and validation of accurate wind turbine generator (WTG) models to study the impact of increased wind integration on system protection. This paper is on the experimental validation of a generic electromagnetic transient-type (EMT-type) model of aggregated WTGs or wind parks suitable for transient studies. The phasor domain equivalent of the generic model, suitable for protection tools based on steady-state solvers, is also considered. The model has been validated using two sets of actual relay records for the fault response of two wind parks consisting of Type-III WTGs and connected to 115 kV and 230 kV transmission systems. The objective is to show that the generic model can reproduce the actual fault response in simulations, and protection engineers can obtain accurate models of wind parks using fault records. A distinctive characteristic of a WTG is its substantially different negative sequence fault current contribution compared to a synchronous generator. The paper shows that the generic model provides enough options to reproduce the negative sequence behavior and hence is suitable for fault studies involving negative sequence-based protection.

Abstract:To improve the controllability and utilization of distributed energy resources (DERs), distribution-level electricity markets based on consumers’ bids and offers have been proposed. However, the transaction costs will dramatically increase with the rapid development of DERs. Therefore, in this paper, we develop an energy sharing scheme that allows users to share DERs with neighbors, and design a novel incentive mechanism for benefit allocation without users’ bidding on electricity prices. In the energy sharing scheme, an aggregator organizes a number of electricity users, and trades with the connected power grid. The aggregator is aimed at minimizing the total costs by matching the surplus energy from DERs and electrical loads. A novel index, termed as sharing contribution rate (SCR), is presented to evaluate different users’ contributions to the energy sharing. Then, based on users’ SCRs, an efficient benefit allocation mechanism is implemented to determine the aggregator’s payments to users that incentivize their participation in energy sharing. To avoid users’ bidding, we propose a decentralized framework for the energy sharing and incentive mechanism. Case studies based on real-world datasets demonstrate that the aggregator and users can benefit from the energy sharing scheme, and the incentive mechanism allocates the benefits according to users’ contributions.

Abstract:The penetration level of distributed energy resources (DERs) is increasing and has significant impact on the voltage stability of distribution networks. Based on the various types of DERs with distinct reactive power characteristics (RPC), their different contributions to the system voltage stability require classification. Firstly, the features of DERs are reviewed and classified based on their RPC, to investigate different distributed generation technologies for reactive power support in distribution networks. Then, the concept of a relative available transmission capacity index (RATCI), which is based on power transfer margin of the power-voltage curve considering the non-negligible distribution network resistance, is proposed to quantify and evaluate the voltage stability by integrating DERs with the defined reactive power types. Case studies have been conducted for an IEEE 33-bus distribution network to calculate the system RATCI for the mixed integration of DERs. Results show that the multi-type and multi-locational integration of DERs can improve the voltage stability of a distribution network.

Abstract:Microgrids have presented themselves as an effective concept to guarantee a reliable, efficient and sustainable electricity delivery during the current transition era from passive to active distribution networks. Moreover, microgrids could offer effective ancillary services (AS) to the power utility, although this will not be possible before the traditional planning and operation methodologies are updated. Hence, a probabilistic multi-objective microgrid planning (POMMP) methodology is proposed in this paper to contemplate the large number of variables, multiple objectives, and different constraints and uncertainties involved in the microgrid planning. The planning methodology is based on the optimal size and location of energy distributed resources with the goal of minimizing the mismatch power in islanded mode, while the residual power for AS provision and the investment and operation costs of the microgrid in grid-connected mode are maximized and minimized, respectively. For that purpose, probabilistic models and a true multi-objective optimization problem are implemented in the methodology. The methodology is tested in an adapted PG&E 69-bus distribution system and the non-dominated sorting genetic algorithm II (NSGA-II) optimization method and an analytic hierarchy process for decision-making are used to solve the optimization problem.

Abstract:With the increasing interdependence of various energy carriers, the operation of power systems is found to correlate closely with the limitations on the other energy infrastructures. This paper presents a mixed-integer linear programming (MILP) model for the microgrid (MG) optimal scheduling considering technical and economic ties between electricity and natural gas (NG) systems. In the proposed methodology, different energy converters and storages, including combined heat and power (CHP) units, electricity/heat storage units, and distributed energy resources (DERs) are considered. The proposed model allows the MG operator to minimize the operation cost of the MG while different operational limitations on the energy hub are satisfied. The model is developed based on AC power flow constraints so as to respect reactive power and voltage security constraints. The efficiency and robustness of the proposed MILP formulation are successfully verified using a large-scale test MG.

Abstract:The concepts of microgrids (MGs) and smart grid represent the recent targeted revolution towards fully smart electrical network integrated with high penetration of renewable energy sources (RESs). The protection system of MGs becomes a challenge due to variable characteristics of its currents, bidirectional power flow and output power fluctuations of RES, causing selectivity and sensitivity issues for conventional protective devices (PDs) with fixed setting. In this paper, a smart protection scheme (SPS) is proposed using micro-phasor measurement units (μPMUs) to obtain the continuous rapid synchronized phasor measurement data. And it is communicated with a microgrid central controller (MGCC) through highly reliable communication architecture to carry out online smart adaptive protection scheme. Fault index coefficients and abnormality coefficients are calculated for each feeder to detect the fault location and the abnormality case. Detailed modeling of an MG including 10-bus connected distribution system with integrated distributed generation (DG) is simulated using ETAP software. The proposed protection algorithm is modeled and evaluated using MATLAB software. The proposed fault detector and abnormality detector can enable quick and accurate fault identification and isolation.

Abstract:An exponential-function-based droop control strategy for the distributed energy resources (DERs) is proposed to reduce the reactive power-sharing deviation, limit the minimum value of frequency/voltage, whilst improving the utilization rate of renewable energy. Both DERs and loads are interconnected to achieve a power exchange by converters, where the power management system should accurately share the active/reactive power demand. However, the proportional reactive power sharing often deteriorates due to its dependence on the line impedances. Thus, an exponential-function-based droop control is proposed to ① prevent voltage and frequency from falling to the lower restraint, ② achieve accurate reactive power sharing, ③ eliminate communication and improve the usage ratio of renewable energy. Furthermore, its stability is analyzed, and the application in islanded AC/DC hybrid microgrids is investigated to achieve the bidirectional power flow. The simulation and experimental results show that the reactive power sharing deviation can be reduced, and the utilization rate of renewable energy is improved by using the proposed method. Moreover, the simulation results illustrate that the system can maintain stable operation when the microgrid is switched from one supplied energy operation condition to another absorbed one.

Abstract:This paper proposes a novel system deployment principle for master/slave type islanded alternating current (AC) microgrids, with which decentralized control can be achieved without communications. The net power of a microgrid, including active and reactive power, is metered and compensated locally and independently by its units. This can benefit a microgrid regarding system expandability, flexibility, and plug-and-play. The proposed strategy is demonstrated in a typical islanded AC microgrid with diesel generators, renewable generation, and hybrid storage. A diesel generator set with constant speed governor and static exciter runs to build up and dominate the main AC bus. An ultra-capacitor unit suppresses fast-varying power fluctuations, and the battery shares part of the slow-varying power component. The diesel generator set only provides slow-varying power within a lower limit, which can avoid dramatic accelerations and decelerations and low load-rate operation. Finally, simulations on MATLAB/Simulink are carried out to verify the proposed strategy in typical scenarios.

Abstract:The large-scale construction of fast charging stations (FCSs) for electrical vehicles (EVs) is helpful in promoting the EV. It creates a significant challenge for the distribution system operator to determine the optimal planning, especially the siting and sizing of FCSs in the electrical distribution system. Inappropriate planning of fast EV charging stations (EVCSs) cause a negative impact on the distribution system. This paper presented a multi-objective optimization problem to obtain the simultaneous placement and sizing of FCSs and distributed generations (DGs) with the constraints such as the number of EVs in all zones and possible number of FCSs based on the road and electrical network in the proposed system. The problem is formulated as a mixed integer non-linear problem (MINLP) to optimize the loss of EV user, network power loss (NPL), FCS development cost and improve the voltage profile of the electrical distribution system. Non-dominated sorting genetic algorithm II (NSGA-II) is used for solving the MINLP. The performance of the proposed technique is evaluated by the 118-bus electrical distribution system.

Abstract:Vehicle-to-grid (V2G) is regarded as the effective way to reconcile contradictions between an electric power system and electric vehicles (EVs). A lot of research has been carried out to affect this, often based on different technical and trading model assumptions. The value of the research is dependent on how reasonable the assumptions it makes are. This paper presents a framework for analyzing V2G service development from a coevolutionary perspective in which the interactive relation between the diffusion of EVs and the upgrade of the distribution grid system is considered. A V2G service development logic and its management formulation are put forward. First, the motivations and contradictions of developing V2G services are analyzed. Then a development phase division of the V2G services is proposed in view of the coevolution relation between the grid upgrade and the development of the EV. Next, taking into account the characteristics of each phase, the physical trade structures and corresponding management hierarchies, management relations as well as management measures, are proposed. This paper provides a new perspective of V2G service development, answers the core question on how to make the V2G vision come true in synergy with the development of EVs, and gives some advice on future V2G management paradigms.

Abstract:Tampering, forgery and theft of the measurement and control messages in a smart grid could cause one breakdown in the power system. However, no security measures are employed for communications in intelligent substations. Communication services in an intelligent substation have high demands for real-time performance, which must be considered when deploying security measures. This paper studies the security requirements of communication services in intelligent substations, analyzes the security capabilities and shortages of IEC 62351, and proposes a novel security scheme for intelligent substation communications. This security scheme covers internal and telecontrol communications, in which the real-time performance of each security measure is considered. In this scheme, certificateless public key cryptography (CLPKC) is used to avoid the latency of certificate exchange in certificate-based cryptosystem and the problem of key escrow in identity-based cryptosystem; the security measures of generic object-oriented substation event, sampled measure value and manufacturing message specification in IEC 62351 are improved to meet the real-time requirements of the messages as well as to provide new security features to resist repudiation and replay attacks; and the security at transport layer is modified to fit CLPKC, which implements mutual authentication by exchanging signatures. Furthermore, a deployment of CLPKC in an intelligent substation is presented. We also evaluate the security properties of the scheme and analyze the end-to-end delays of secured services by combining theoretical calculation and simulation in this paper. The results indicate that the proposed scheme meets the requirements of security and real-time performance of communications in intelligent substations.

Abstract:The share of voltage source converter (VSC) technology is increasing in conventional power systems, and it is penetrating into specific transportation systems such as electric vehicles, railways, and ships. Researchers are identifying feasible methods to improve the performance of railway electrification systems (RESs) by utilizing VSC-based medium-voltage direct current (MVDC) railways. The continuous motion of electric trains makes the catenary resistance a variable quantity, as compared to the traction substation (TSS), and affects the current-sharing behavior of the system. A modified droop control technique is proposed in this paper for VSC-based MVDC RES to provide more effective current-sharing while maintaining catenary voltages above the minimum allowable limit. The droop coefficient is selected through an exponential function based on the ratio between the concerned TSS current and the system average current. This enables small adjustments of droop values in less concerning marginal current deviations, and provides higher droop adjustments for large current deviations. Meanwhile, the catenary voltages are regulated by considering the voltage data at the midpoint between two TSSs, which experiences the lowest voltages owing to the larger distance from the TSSs. The proposed techniques are validated via simulations and experiments.