Program: 1st Session on Thursday (08:20-09:40)

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T1-1 – Renewables Integration & Optimization – Wind

08:20 A Dump Load-Less Standalone Wind Energy Conversion System Supplying a Generic Load

Zuher Alnasir (University of Waterloo, Canada); Mehrdad Kazerani (University of Waterloo, Canada)

A current-source inverter-based standalone wind energy conversion system has been recently proposed for low power applications. In this paper, the system is modified by removing the dump load and avoiding the surplus power generation by curtailment of wind power. The generator-side converter is used to control the shaft speed, allowing extraction of maximum available wind power in normal mode of operation, and to regulate DC-link current, allowing curtailment of wind power when it is not possible to absorb maximum available power by the storage system and the load. In order to verify successful operation of the system under a wide range of load types, a reduced-order generic load model, that is suitable for both balanced and unbalanced load conditions, is developed and tested with the system. The current-source inverter is used to control positive- and negative-sequence voltage components separately. The operation of the modified system is investigated and verified under variable wind and load conditions.

08:40 Dynamic Frequency Support with DFIG Wind Turbines – A System Study

Denis Mende (Fraunhofer IWES, Germany); Tobias Hennig (Fraunhofer IWES, Germany); Alev Akbulut (Fraunhofer IWES, Germany); Holger Becker (Fraunhofer IWES, Germany); Lutz Hofmann (Leibniz Universität Hannover, Germany)

Frequency control in interconnected electrical power systems is nowadays realized using the networks’ conventional power plants. With the ongoing changes in power systems worldwide the share of these conventional power plants is decreasing while renewable resources such as wind power and photovoltaics are increasing their share continuously. Up to now a contribution of renewable sources on primary frequency control is not realized in interconnected power systems. This paper describes possibilities to support the frequency of power systems using wind turbines with enhanced active power functionalities such as primary frequency control and synthetic inertia. The effects of these functionalities were analyzed in the IEEE 39 bus system. Different simulations with an implementation in a doubly fed induction generator wind turbine model show promising results. The frequency behavior of a 50 % penetrated system with standard wind power plants shows unfavorable frequency behavior compared to the original system, whereas a system with additional frequency supporting functionalities by wind power plants improves the frequency behavior significantly.

09:00 Inertia Support During Variable Wind Conditions

Mattias Persson (Chalmers University of Technology, Sweden); Peiyuan Chen (Chalmers University of Technology, Sweden); Ola Carlson (Chalmers University of Technology, Sweden)

Wind variations are important to consider while designing inertia support strategies. One model has been evaluated but the findings should reflect issues with several control strategies utilizing a fixed support pattern. Wind variability is shown to be at the worst around 0.5 m/s for second to second evaluations, drastic changes can occur in wind speed if considering longer durations of inertia support, such as 30~s. An improved inertia control algorithm has been presented allowing a stable delivery of inertia support from variable speed wind turbines (VSWT) realistic wind conditions. The controller improves the previously presented algorithm and is proving good performance when subjected to realistic wind data. The impact of the utilized wind speed filter is described and its impact on the simulation found to be of great importance.

09:20 Low Voltage Ride-Through Enhancement in DFIG-Based Wind Turbine

Ehsan Gatavi (Western Sydney University, Australia); Ali Hellany (Western Sydney University, Australia); Mahmood Nagrial (Western Sydney University, Australia); Jamal Rizk (Western Sydney University, Australia)

Wind farms are regarded as large-scale power plants with interconnected systems, where all systems interact with each other to improve the efficiency of the plant and thus enhance the quality of the output power. However, the conventional centralized controller is inappropriate for such plants. Accordingly, the plant-wise controller is an alternative solution to be plant-wise decentralized, by designing the separate local controller of each subsystem. Moreover, voltage stability plays a significant role to preserve the Doubly Fed Induction Generator (DFIG) based Wind Farms (WF) connected to the grid, which is known as Low-Voltage-Ride-Through (LVRT), in the period of fault appearance. This paper describes a critical review on the existing control methods of the DFIG-based WTs, and also presents the significance of the LVRT capacity improvement to enhance the power quality and guarantee the plant-wise stability during the grid faults.

T1-2 – Distribution Operation

08:20 Interaction of Demand Response and Voltage Stability in Smart Grids

Masoud Esmaili (West Tehran Branch, Islamic Azad University, Iran); Ali Vedadi (West Tehran Branch, Islamic Azad University, Iran)

Demand Response (DR) is one of efficient tools in smart grids to manage load profile. When loads alter their consumption to respond to price signals, the voltage dependency of load powers leads to a mismatch between scheduled and obtained power consumption levels; this is called Demand Response Mismatch (DRM). To mitigate DRM and voltage rise after DR, some voltage compensators are used in the inductive mode. However, since DR is implemented in load peak hours, introduction of inductive compensators can jeopardize voltage stability of the power system. In this paper, a method is proposed to manage DRM while enough Voltage Stability Margin (VSM) is retained. The proposed method is tested on a typical 34-bus test system to evaluate its performance.

08:40 Mitigating Overvoltage Scenarios Caused by Large Penetration of Distributed Energy Resources

Alexandre Nassif (ATCO Electric, Canada); Xun Long (FortisAlberta, Canada)

Distributed Generators (DGs) are continuously more prevalent in medium-voltage distribution systems. Steady-state voltage management for these systems has become a major obstacle to power utilities due to DGs’ control mode typically applied, i.e., constant power factor control. Voltage rises are becoming a norm that poses hurdles to accepting many DG connections. This paper addresses this issue and provides existing mitigation strategies utilities are adopting. It also explains the imperative need to develop better mitigation measures.

09:00 Grid Voltage Level Spanning Operational Strategies for Battery Energy Storage Systems in Distribution Grids

Lorenz Viernstein (Technical University of Munich, Germany); Rolf Witzmann (Technische Universität München, Germany); Joachim Przibylla (Technical University of Munich, Germany)

With rising renewable generation and battery storage prices decreasing, storage integration in electrical grids is increasingly discussed as an option to avoid conventional grid extension as well as an option for new business models for utilities and customers. While the majority of available literature focuses only on the low-voltage level, the impact distributed storages can have on the superimposed medium-voltage grid has to be considered. Especially in grids with high distributed renewable generation, battery storages can contribute to a grid operation conforming to standards. In this paper an operational strategy is presented that includes medium-voltage/low-voltage transformers as well as the high-voltage/medium-voltage transformer into the control algorithm. Results obtained by simulations show, that battery storage systems in low-voltage grids can efficiently relief the superimposed medium-voltage grid and the transformer connecting it to the high-voltage level.

09:20 Comparative Evaluations of Regenerative and Electro-dynamic Braking and Power Substations Along Graded Section of a Japanese Suburban Rail Line

Kosuke Kumagai (East Japan Railway Company, Japan); Tetsuo Fujita (East Japan Railway Company, Japan); Masashi Nakahira (East Japan Railway Company, Japan); Yoshiki Mizuguchi (East Japan Railway Company, Japan); Hideki Sonoda (East Japan Railway Company, Japan)

To reduce the environmental impact of the DC feeding system of the East Japan Railway Company (JR-EAST), it is important to have effective regenerative energy transfer from one train to another. Considering previous studies in simulation, we gathered information helpful for effective energy-saving measures. In this paper, such measures were adapted to the DC feeding system on a graded section of the Chuo Line, a rail line originating in the Tokyo metropolitan area. Simultaneous measurements were conducted on Chuo Line Series E257 trains and the adjacent substations.
In particular, from these measurements the relation between regenerative and electro-dynamic braking of trains and behavior of the adjacent substations was specifically confirmed in a track section with a falling gradient. Also, we studied estimation regarding regenerative power constriction, electro-dynamic braking and regenerative energy on trains using the data from substations to estimate the amount of energy-saving per train. This was by changing substation DC bus voltages for more effective regenerative energy transfer in the future.

T1-3 – Cyber-Security and Big Data

08:20 Comparison of Artificial Intelligence Techniques for Energy Consumption Estimation

Oludolapo Olanrewaju (University of Johannesburg, South Africa); Charles Mbohwa (University of Johannesburg, South Africa)

In this article, a comparison study of three artificial intelligence (AI) techniques for energy consumption estimation are presented. The models considered are: multilayer perceptron (MLP); radial basis function (RBF) and support vector machine (SVM). The energy consumption is modeled as a function of activity, structural and intensity changes. The models are applied to Canadian industrial manufacturing data from 1990 to 2000. Comparisons were based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), Root Relative Square Error (RRSE) as well as Simulation Time. The best results were obtained for the Multilayer Perceptron.

08:40 Parameter Selection of Multi-Class SVM with Evolutionary Optimization Methods for Static Security Evaluation in Power Systems

Samin Rastgoufard (University of New Orleans, USA)

Static Security Evaluation (SSE) is one of the most important real-time studies in power systems. Static security can be assessed by different machine learning methods. In this paper, one of the well-known classifiers, namely the Support Vector Machine (SVM), is used for solving the SSE problem. Proper operation of the SVM heavily depends on the appropriate choice of parameters. The optimization problem aims at determining these parameters. This work presents a study of several heuristic optimization methods for static security. In particular, Modified Particle Swarm Optimization (MPSO), Differential Evolution (DE), Ant Colony Optimization for continuous domain (ACOr), and Harmony Search (HS) are employed for determining the optimal SVM parameters. In addition to studying the performance of various optimization techniques, this work is concerned about viewing the SSE problem as a 2-class, a 3-class, and a 4-class classification problem, where each class is associated with a particular level of security. The performance of each method is presented in terms of classification accuracy and execution speed. It is shown that most optimization methods exhibit a similar performance. However, choosing the best optimization method seems to be dependent on the number of classes, and thus, on the number of security levels required by SSE. The New England 39-bus benchmark system is used for simulation.

09:00 Ensemble Regression Model-Based Anomaly Detection for Cyber-Physical Intrusion Detection in Smart Grids

Anna Kosek (Technical University of Denmark, Denmark); Oliver Gehrke (DTU Electrical Engineering, Denmark)

The shift from centralised large production to distributed energy production has several consequences on the current power system operation. The increasing number of the distributed energy resources (DERs) replacing large power plants influences the dependency of the power system on the small scale, distributed production. Many of these DERs can be accessed and controlled remotely, posing a cybersecurity risk. This paper investigates an intrusion detection system that evaluates the DER operation in order to discover unauthorized control actions. The proposed anomaly detection method is based on an ensemble of non-linear artificial neural network DER models that detects and evaluates anomalies in the DER operation. The proposed method is validated against real measurement data. Based on the obtained results the proposed ensemble anomaly detection method with normal model training data selection achieves 0.947 precision and 0.976 accuracy, which improves the precision and accuracy of a classic model-based anomaly detection by 75.7% and 9.2% respectively.

09:20 A Study of Resource-Constrained Cyber Security Planning for Smart Grid Networks

Md Hasan (University of Ottawa, Canada); Hussein Mouftah (University of Ottawa, Canada)

This paper studies cyber security planning issues in resource-constrained smart grid networks. In particular, it proposes a centrality-based trust system placement scheme for energy SCADA systems. It aims to utilize centrality measurements to improve cyber protection in resource-constrained scenarios. The role of centrality measurements is to rank nodes based on their importance in a network. Trust systems are specialized security devices that are capable of firewalling and network intrusion detection. They monitor both types of traffic, ingress and egress. They are mainly deployed to provide cyber protection to supervisory control and data acquisition (SCADA) systems. Due to budgetary constraints, only a selected number of nodes are equipped with trust systems. Those nodes are known as the trust nodes. The proposed scheme uses linear programming problem (LPP) formulations to select the trust nodes. Numerical results are obtained through case studies for the IEEE BUS 30 and BUS 57 test system topologies. The results reveal that the proposed scheme is capable of improving quality of cyber protection in resource-constrained scenarios.