Program: 4th Session on Friday (15:20-17:00)
- F4-1 – EV Growth, Impact & Integration
- 15:20 – A Novel Feature Fitting Simulation Algorithm for Estimating Electric Vehicle Demand
- 15:40 – Propagation of Electrical Disturbances to Automotive Batteries in Vehicle-to-Grid Context
- 16:00 – Funding an Electric Vehicle Charging Infrastructure From Associated Health Benefits
- 16:20 – The Effect of PEV Uncontrolled and Smart Charging on Distribution System Planning
- 16:40 – Integration of Electric Vehicles Into a Smart Power Grid: A Technical Review
- F4-2 – Transmission Apparatus
- 15:20 – Power Quality Improvement in Induction Furnace Using Eleven Level Cascaded Inverter Based DSTATCOM
- 15:40 – A Negative-Sequence Based Method for Fault Passage Identification
- 16:00 – Accelerating Renewable Connections Through Coupling Demand and Distributed Generation
- 16:20 – Multi-Objective Optimization for Voltage Regulation in Distribution Systems with Distributed Generators
- 16:40 – Research on Dynamic Frequency Bias Coefficient and Relevant Evaluation Criterion in the Setting of UHV
- IF4 – Industry Presentations
- Co-Located Affinity Group Events
- horizons@EPEC – 12:45-16:45
F4-1 – EV Growth, Impact & Integration
- 15:20 – A Novel Feature Fitting Simulation Algorithm for Estimating Electric Vehicle Demand
- 15:40 – Propagation of Electrical Disturbances to Automotive Batteries in Vehicle-to-Grid Context
- 16:00 – Funding an Electric Vehicle Charging Infrastructure From Associated Health Benefits
- 16:20 – The Effect of PEV Uncontrolled and Smart Charging on Distribution System Planning
- 16:40 – Integration of Electric Vehicles Into a Smart Power Grid: A Technical Review
15:20 A Novel Feature Fitting Simulation Algorithm for Estimating Electric Vehicle Demand
Electric vehicles will drive the future, therefore forecasting and simulating ‘transportation electrification’ demand over the coming years has become important for utilities. Ever since electricity was commercialized there has been a need for demand forecasting and simulation because electricity provider’s ability to produce energy far exceeds their ability to store energy. This is an industry worth billions of dollars and therefore even a marginal improvement in the way it’s predicted can have a great impact. Demand forecasting is critical for unit commitment and broadly effects the wholesale electricity market price. With the addition of transportation electrification this process has become even more challenging. Traditional ways are hard to model and computationally intensive, nowadays this type of problem is of great interest in the field of machine learning as well, because of the availability of large datasets from utilities. However datasets for transportation electrification still remain a huge challenge therefore more work needs to be done in forecasting electric vehicular loads. This paper tackles this new problem and presents a new method called Feature Fitting Simulation Algorithm to estimate electric vehicle charging demand profiles. The simulation was performed on MATLAB and Excel using various tools and functions to ensure the algorithms run on optimum efficiency. The novel feature of the algorithm is its hybrid structure of considering both historical and simulation data for temporal predication, secondly it introduces two key variables scaling and sensitivity to better control the time series output. FFSA is vetted against machine learning algorithms and the results indicate a better performance achieved by FFSA.
15:40 Propagation of Electrical Disturbances to Automotive Batteries in Vehicle-to-Grid Context
This paper investigates the effects of disturbances originating in the electric grid as well as residential appliance inrush currents on the integrity of battery packs in electric vehicles that are connected to the grid or a residence for the purpose of V2G or V2H service. Simulation results show that the effect on battery capacity loss was negligible. The large size of an automotive battery pack allows it to easily withstand the levels of current caused by typical grid based disturbances and appliance inrush currents. Thus, power grid disturbances as they exist, need not be considered a reason to refrain from employing an electric vehicle for V2G or V2H service.
16:00 Funding an Electric Vehicle Charging Infrastructure From Associated Health Benefits
This report looks at the health benefits associated with driving an electric vehicle, and determines the cost effectiveness of using these benefits to fund the expansion of electric vehicle charging infrastructure between 2016 and 2021. Damages related to poor air quality such as sick days and increased chronic illness were quantified, and reductions in instances of these issues resulted in a benefit that can be reaped by governments and municipalities. The result indicate that the benefits associated with improved air quality in general far exceed the costs of installing additional charging stations. The findings indicate that the overall outlook for future expansion of charging stations can be borne by the improved air quality provided by an increasing movement away from traditional internal combustion engine vehicles and towards electrified mobility options.
16:20 The Effect of PEV Uncontrolled and Smart Charging on Distribution System Planning
This paper presents a planning model for distribution systems considering various energy supply options such as distributed generation (DG), substations, and feeders. In addition, the impact of Plug-in-Electric Vehicle (PEV) uncontrolled and smart charging loads on the plan outcome is evaluated. A new optimal power flow (OPF) based optimization model is proposed to schedule PEV uncontrolled and smart charging loads. Test results are presented to demonstrate the effectiveness of the proposed model. The results show that PEV charging loads significantly affects the plan outcomes.
16:40 Integration of Electric Vehicles Into a Smart Power Grid: A Technical Review
Electrification of a transportation system is one of the most promising alternatives to mitigate the dependency of urban life to fossil fuels. However, introducing a large number of grid-connected vehicles reveals technical problems affecting the entire power system specially the low voltage distribution power grid. In this context, this paper presents a review of technical challenges associated with the integration of Vehicle-to-Grids (V2Gs). These challenges could be studied in several subsections of a power system such as the operation of power electronics equipment, supply-demand imbalance, and impacts on voltage and frequency. In addition, to clarify the concept of smart grid in a power system, a new definition of a smart power grid in the sector of power distribution is elaborated considering the effects of V2Gs. This developed definition specifies that the penetration of V2Gs, in fact, establishes an opportunity for implementing the smart power distribution through offering renewable energy storages, two-way communication, and reactive and active power injections to the grid. This review may be regarded as an important basis for the investigation of future challenges in the integration of V2Gs into a smart grid.
F4-2 – Transmission Apparatus
- 15:20 – Power Quality Improvement in Induction Furnace Using Eleven Level Cascaded Inverter Based DSTATCOM
- 15:40 – A Negative-Sequence Based Method for Fault Passage Identification
- 16:00 – Accelerating Renewable Connections Through Coupling Demand and Distributed Generation
- 16:20 – Multi-Objective Optimization for Voltage Regulation in Distribution Systems with Distributed Generators
- 16:20 – Research on Dynamic Frequency Bias Coefficient and Relevant Evaluation Criterion in the Setting of UHV
15:20 Power Quality Improvement in Induction Furnace Using Eleven Level Cascaded Inverter Based DSTATCOM
In power distribution networks, the use of non-linear loads is expanding day by day due to which the power quality of the system is being deteriorated. An induction furnace is one such typical example of a non-linear load which is indispensable component of the steel industries. It injects considerable amount of harmonics into the supply network and consequently the performance of other loads in its vicinity gets affected. In this paper, the application of an eleven level Cascaded Multilevel Inverter (CMLI) based Distribution Static Compensator (DSTATCOM) is presented to improve the power quality of an induction furnace in a steel industry. The experimental readings of the induction furnace are obtained using power quality analyser and then an equivalent model of this induction furnace has been developed in Matlab Simulink platform using real world industrial data. The solution methodology proposed by CMLI based DSTATCOM reveals the effectiveness of proposed control strategy for voltage sag mitigation and Total Harmonic Distortion (THD) improvement of both load current and voltage as per the IEEE standards.
15:40 A Negative-Sequence Based Method for Fault Passage Identification
Reliable fault indication is crucial in any distribution feeder management system. A distribution line protective device can use different algorithms to detect whether or not it is in the fault path. When the downstream fault involves all three phases, detection is typically easy to achieve and phase elements are sufficient. Single line to ground faults cannot always be treated in the same manner, as ground sources are prevalent throughout the grid. In these cases, directionality (achieved by voltage polarization) is required. However, the requirement of both current and voltage measurements could render the solution cost prohibitive. If voltage is not available, detection may fail. Hence, there is the need for a simple but reliable ground fault indicator which is based on current measurements solely. This paper proposes the use of negative-sequence current to achieve this purpose. It is inspired by the fact that there is only one source of negative-sequence currents in a radial system. The proposed settings were implemented in large scale in the city of Fort McMurray throughout ATCO Electric’s DSCADA devices. Such inputs are used by the feeder automation system to reconfigure the system automatically in case of permanent outages.
16:00 Accelerating Renewable Connections Through Coupling Demand and Distributed Generation
The objective of this paper is to investigate the options for using local demand to accelerate the connection of renewable Distributed Generation (DG) capacity. It presents a range of architectures for operating Distributed Energy Systems (DESs) that contain local demand and distributed generation. The concept of a DES is that demand is supplied by local DG either using privately owned distribution assets or a public distribution network owned by a Distribution Network Operator (DNO). Operation of a DES can help manage variability in DG output, reduce curtailment in Active Network Management (ANM) schemes, and assist the DNO in managing network constraints. They also provide a move towards local trading of electricity with potential financial and non-financial benefits to both distributed generators and local demand customers.
16:20 Multi-Objective Optimization for Voltage Regulation in Distribution Systems with Distributed Generators
In this study, in order to reduce the abnormal voltage drop or rise in the distribution systems with distributed generators, we consider a multi-objective function to be optimized in such a way that the voltage profile is enhanced while the total active power loss in the network is minimized under some operational constraints. Capacitors and static VAR compensator are also coordinated with the distributed generators in the network to acquire a better enhancement in the voltage profile. The purpose of this study is to obtain the optimum sizes and locations of these system components so that the active power losses and the deviations in bus voltages from their nominal values are minimized. The problem is formulated as a multi-objective optimization problem and solved by the goal attainment method. The studies are demonstrated on an IEEE 34-bus test system where the direct load flow method is utilized for load flow calculations.
16:40 Research on Dynamic Frequency Bias Coefficient and Relevant Evaluation Criterion in the Setting of UHV
After ultra-high voltage (UHV) tie lines are established, fluctuations of frequency and tie-line power become more obvious, which set a still higher demand on automatic generation control (AGC) performance. Frequency bias coefficient (K coefficient) plays the key role in improving control effect of AGC system. Based on operation characteristics of a domestic multi-area interconnected power system, this paper firstly proposes a calculation method of dynamic K coefficient in divided period. Furthermore, the evaluation criterion is first put forward to assess calculation results. Finally, an application example proves the validity of dynamic K coefficient in optimizing AGC operation.