Program: 4th Session on Thursday (15:20-17:00)

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T4-1 – Distribution Operation

15:20 Automatic Restoration in Distribution Systems Considering DG Transfer and Islanded Microgrids

Mohamed El-sharafy (York University, Canada); Hany Farag (YorkU, Canada)

This paper proposes a new centralized control scheme for automatic back-feed service restoration in distribution systems with high penetration of distributed generation (DG). The proposed restoration algorithm introduces three types of power transfer between the tied adjacent feeders during the restoration process: load transfer, DG transfer and a combination of load/DG transfer. Another feature of the proposed scheme is the ability of forming islanded microgrids (IMGs) in the post-restoration network by utilizing the available DGs. The objectives of the proposed algorithm are to 1) maximize the restored loads, and 2) minimize the switching operations taking into consideration the load variability during the fault occurrence and the system operational constraints. Several case studies have been carried out on a typical distribution system with multiple feeders to show the effectiveness and robustness of the proposed algorithm.

15:40 Optimal Power Flow with Demand Participation of RESs

Mutlu Yilmaz (Dalhousie University, Canada)

The paper is concerned with a semidefinite program (SDP) to solve the optimal power flow (OPF) problem for integrating renewable energy sources (RESs) with demand participation in electric grids. The electric generation from renewables as a supplier is randomly realized using an algorithm which is intended to demand participation. The demand participation is provided by demand-side resources with renewables to curtail the native loads, which means that the penetration of renewable generation is raised. Thus, a balance between supply and demand response of the grid is maintained. The optimization problem, accommodating the excess of the renewable generation, is introduced as a convex problem. The convex problem is represented in the form of the semidefinite program. Due to the nonconvexity of the optimal power flow problem, the convex semidefinite relaxation has been proposed to solve the optimization problem. We also perform contingency scenarios and test these scenarios by solving the semidefinite relaxation to obtain feasible solutions.

16:00 Applying Machine Learning Techniques for Forecasting Flexibility of Virtual Power Plants

Pamela MacDougall (TNO, The Netherlands); Anna Kosek (Technical University of Denmark, Denmark); Henrik Bindner (Technical University of Denmark, Denmark); Geert Deconinck (KU Leuven, Belgium)

Previous and existing evaluations of available flexibility using small device demand response have typically been done with detailed information of end-user systems. With these large numbers, having lower level information has both privacy and computational limitations. We propose a black box approach to investigating the longevity of aggregated response of a virtual power plant using historic bidding and aggregated behaviour with machine learning techniques. The two supervised machine learning techniques investigated and compared in this paper are, multivariate linear regression and single hidden layer artificial neural network (ANN). Both techniques are used to model a relationship between the aggregator portfolio state and requested ramp power to the longevity of the delivered flexibility. Using validated individual household models, a smart controlled aggregated virtual power plant is simulated. A hierarchical marketbased supply-demand matching control mechanism is used to steer the heating devices in the virtual power plant. For both the training and validation set of clusters, a random number of households, between 200 and 2000, is generated with day ahead profile scaled accordingly. Further, a ramp power (power deviation) is assigned at various hours of the day and requested to hold for the remainder of the day. Using only the bidding functions and the requested ramp powers, the ramp longevity is estimated for a number of different cluster setups for both the artificial neural network as well as the multi-variant linear regression. It is found that it is possible to estimate the longevity of flexibility with machine learning. The linear regression algorithm is, on average, able to estimate the longevity with a 15% error. However, there was a significant improvement with the ANN algorithm achieving, on average, a 5.3% error. This is lowered 2.4% when learning for the same virtual power plant. With this information it would be possible to accurately offer residential VPP flexibility for market operations to safely avoid causing further imbalances and financial penalties.

16:20 Calculation of Line Loss in Low-Voltage Transformer District Based on BP Network Model Optimized by LM Algorithm

Liu Li-ping (Chinese Socite for Electrical Engineering, P.R. China)

A novel method of calculating line loss rate in transformer district is presented and realized by programming, which is BP network model based on LM algorithm. Establish the characteristic index system according to electric characteristics parameters of samples. The classification of samples by K-Means clustering algorithm solves the numerical dispersion of line loss rate in transformer district. On this basis, each class is learnt and trained by BP network optimized by LM algorithm. BP network is adopted to map complex non-linear relation between line loss rate and electric characteristic parameters. Variation of transformer district line loss rate is obtained under different grid structures and load characteristic parameters. The transformer districts in the real system as an example, simulation and calculation are performed to verify the accuracy of the proposed method. This method has the advantages of fast convergence and high accuracy.

16:40 Current Modulated Messages Generated by PFC Circuits for Allocating Appliances with Management Systems in Smart Grid Applications

Christoph Aldejohann (TU Dortmund University, Germany); Thomas Wohlfahrt (TU Dortmund University, Germany); Christian Rehtanz (University of Dortmund, Germany); Johanna Myrzik (Technische Universität Dortmund, Germany)

This paper shows a technical solution to locate and to identify an electrical load and to allocate it with controllers for interchanging clearing and control information e.g. in smart grid applications. It is a solution where the controller can be easily integrated in smart meters, substations and in external control devices. The appliance uses its integrated switching power supply for establishing a communication link. Therefore the control of the integrated power factor correction (PFC) is modified. Thus plugging to a normal socket-outlet is sufficient for allocating the device with controllers in a way like a Plug’n’Play system. The technique does not need new lines and can be installed in existing electrical installations with minimal effort. The allocating technique uses two different communication channels. The first one is a unidirectional channel with a very low frequency which uses the electrical current as a carrier, and the second one is a bidirectional channel. The management system detects, if an appliance is connected to the pathway behind the controller and it establishes an individual communication link. The controller can check its responsibility because grid’s impedance for low frequencies is much lower than the impedance of the connected loads so that the current flows only on the pathway to the transformer station. The method has some more features such as setting up a hierarchized system with several management units for different tasks such as power management, clearing services or congestion management.

T4-2 – Energy Efficiency, Demand Response, & Energy Markets

15:20 New Approach on Energy Conservation Measures Types Applied in Mining Industry

Constantin Pitis (Powertech Labs Inc., Canada)

Some Energy Efficiency Programs (EEP) considers Energy Use Intensity (EUI) as an unreliable indicator due to its variation, i.e. the EUI values are dropping when production increases. Currently used Energy Conservation Measures – ECMs (supported by governmental and utility programs) are proven by energy savings (ES) recorded at revenue meter (or system boundary meter) considering energy use or energy recorded at revenue meter as a whole. The author proposed a novel concept of splitting the energy in 2 (two) specific components: Productive Energy and Non-Productive Energy followed by definition of new EUI type: Productive Energy Use Intensity (PEUI). The concept, applied to metal mines, made a breakthrough in EEP, enabling new ECM types applicable in Mining Industry. Case studies with verification & validation activities are provided.

15:40 The Impact of Intermittent Renewables on the Resource Adequacy in Electricity Markets

Hamid Aghaie (AIT Austrian Institute of Technology, Austria)

This paper analyzes the impact of renewables on the resource adequacy in German electricity market. A system dynamic model is proposed to model the electricity market by considering the uncertainty of renewable generation. The aim is to investigate the impact of the increasing renewables generation and its intermittency on the profitability of new installed capacity and long term investment decisions in an electricity market with a very tight reserve margin. It is assumed that the share of renewables generation will increase up to 60% in 2050. The results show that the investment in new conventional capacity will be profitable if the share of intermittent generation by solar and wind is at least 12% of total renewable generation in each year. The reason is that higher intermittency of renewables leads to more frequent scarcity situation and more profit for new capacity. The results prove that higher share of renewables leads to higher mean and variance of loss of load. Also, increasing share of renewables could result either ascending or descending average prices and it depends on the intermittency percentage of renewables’ generation. Increasing share of renewables leads to a higher price variance and higher intermittency results a steeper increase of price variance.

16:00 Economic Dispatch At Peak Load Using Load Reduction for Smart Grid

Zakareya Hasan (Dalhousie University, Canada); Mohamed El-Hawary (Dalhousie University, Canada)

This paper proposes a future economic dispatch problem for smart grid network (SGED) at peak time using demand side management (DSM) methods. The aim is to model the SGED problem at peak hours and solve it by finding an economic and reliable method of allocating the load on available generation units and choose the least expensive area or consumers to apply the DSM measures while satisfying the problem different constraints. Differential evolution is used to solve the SGED problem for two Test systems: three generation units with valve point effect and six generation units with prohibited operation zone and ramp rate limits.

16:20 A Review of Demand Response Techniques in Smart Grids

Anam Malik (University of New South Wales, Australia); Jayashri Ravishankar (University of New South Wales, Australia)

The worldwide installation of renewable energy generators has rendered the conventional frequency regulation techniques insufficient. However, smart grid in the recent years has shown great potential in regulating frequency by changing end-user demand so as to match supply. A large and growing body of literature in the past has investigated load scheduling and frequency deviation as two separate problems and proposed centralized or decentralized control techniques for eliminating power mismatch, that result in complex computational tasks and huge economic burden. Much of the research thus far fails to account for factors such as random customer demand, storage devices and various load groups in a single control model. The paper reviews previously presented demand scheduling and frequency regulation techniques as well as gives future directions for introducing a new, improved demand control system.

16:40 Residential Energy Management in Smart Grid Considering Renewable Energy Sources and Vehicle-to-Grid Integration

Fady Melhem (Université de Technologie de Belfort-Montbéliard (UTBM) / Institut de Recherche Industrielle (IRI), Lebanon); Nazih Moubayed (CRSI, Faculty of Engineering, Lebanese University, Lebanon); Olivier Grunder (Université de Technologie de Belfort-Montbéliard (UTBM), France)

The Smart Grids, which refers to the next generation of electrical power systems, are very complex systems with few theoretical researches. It needs to consider all sides of power grid, making it more intelligent and flexible. This notion is presented as an answer to changes in the electricity market, aiming to manage the increased demand while ensuring a better quality of service and more safety. This paper presents an integration of the distributed energy resources in the smart gird in an urban context. The analysis takes into account the integration of renewable energy production such as photovoltaic systems and micro-wind turbine systems, battery storage and gridable vehicles that can provide power to the grid by discharging the battery. Consequently, a mixed integer linear programming is proposed to optimize the energy production and consumption systems as well as the charging and discharging time of electric vehicle among a residential consumer. Besides, several case studies are presented by varying significant factors through design of experiments with Taguchi method to find the optimal solution and to illustrate their influence in the complexity of the system.

T4-3 – Power Electronics

15:20 Comparison of Si AND GaN-FETs in a VAR Compensation Application

Tanya Gachovska (Solantro Semiconductor Corp., Canada); Chris Gerolami (Solantro Semiconductor Corp, Canada)

VAR compensators (VARComps) are devices that produce reactive power in AC electrical systems. Electronic inverter circuits can supply currents that are at 90° to the grid voltage to supply reactive power Q. Since no active power P is delivered to the grid, these devices appear as a two terminal device similar to a capacitor or inductor. A VARComp was developed for this purpose. In this research, Si and GaN_HFETs were characterized in a full bridge VARComp. The Si devices have approximately twice the drain to source resistance and capacitance as compared with the GaN devices. The test results show ten times greater driver losses with Si devices as compared with GaN devices. Due to soft switching, no switching losses were observed for GaN devices. Since a GaN device does not have a body diode, diode reverse recovery losses were observed only for the Si VARComp. The transition switching time was approximately four times greater for Si FETs as compared with GAN-HFETs. The VARComp with GaN-HFETs required lower current and less time to resonate as compared with the VARComp with Si FETs and therefore had low losses. Due to the more linear transfer function of the GaN devices, as compared to Si devices, THD when operating open loop was 8% smaller. Higher total power losses were observed for the Si VARComp than the GaN VARComp.

15:40 Research on Optimal Allocation of Reactive Power Compensators in Substation

Zhichang Yuan (Tsinghua University, P.R. China)

An optimal method on allocation of reactive power compensators in substations is proposed in this paper. Equivalent circuit of 110kV substation is built up, which can model load capacity, short circuit capacity, transformer, motor in load, and power factor. Power load is modeled with composite load containing motor and constant Z load. Firstly the capacity of shunt capacitor is determined by the demand to make power factors of entirely substation equal to 1. Secondly the capacity of dynamic var source such as STATCOM or SVC is determined by the demand to prevent transient voltage collapse under faults. The capacities of reactive power compensators on different system conditions are analyzed which can be referred by power system planners and operators.

16:00 Virtual DC Machine Control Strategy of Energy Storage Converter in DC Microgrid

Shucheng Tan (Xi’an University of Technology, P.R. China); Ge Dong (School of Aerospace Engineering, Tsinghua University, Beijing, P.R. China); Hui Zhang (Xi’an University of Technology, P.R. China); Na Zhi (Xi’an University of Technology, P.R. China); Xi Xiao (Tsinghua University, P.R. China)

The bus voltage of DC microgrid is the key indicator of the stable operation of the system. The energy storage device plays an important role in maintaining the stability of the DC bus voltage of DC microgrid. In this paper, a virtual DC machine (VDCM) control strategy of energy storage converter in DC microgrid is adopted, aiming to solve the problem that the DC bus voltage is easy to be disturbed and cannot be well maintained. This control method simulates the characteristics of the DC machine and is a robust and flexible DC/DC converter control method, which can make the converter and the DC bus flexible connection, effectively restrain the DC bus voltage disturbance impact so as to enhance the stability of DC microgrid. A simulation model of DC microgrid with photovoltaic, energy storage device and load is established in MATLAB/Simulink. Simulation results show the feasibility and validity of the adopted control method.

16:20 Stray Capacitance of HVDC Key Devices and Its Impact on Harmonic Distribution

Yunchao Wang (Tsinghua University, P.R. China); Zhanqing Yu (Tsinghua University, P.R. China); Xiao Zhang (Tsinghua University, P.R. China); Jun Hu (Tsinghua, P.R. China); Jinliang He (Tsinghua University, P.R. China); Shuiming Chen (Tsinghua University, P.R. China)

This paper focuses on the stray capacitance of HVDC key devices and its impact on the harmonic distribution and the problem of obtaining wide band models for electrical power system transient simulation purposes for EMTP with linear components. Smoothing reactor, converter transformer and the valve hall can be modeled with stray parameters by segmented wide-band model with skin effect resistance. The simulation curve of the model can already be consistent with measured curves, and it can reflect the resonance characteristics under 100 kHz and fit the stray capacitance well in high frequency. The analysis of overvoltage fault proves that the stray capacitance played an important role in fault analysis with respect to harmonics distribution of HVDC system and the model with stray parameters has significant value of application.