Showing papers presented at "Clemson University Power Systems Conference in 2018"

An Energy Storage Cost Comparison: Li-ion Batteries vs Distributed Load Control

Abstract: In 2017, San Diego Gas & Electric installed a 30 MW, 120 MWh lithium-ion battery storage facility–the world’s largest at the time. But, recent work demonstrates that local control can enable flexible loads to provide equivalent battery-like services to the grid. Our cost comparison shows that it is much cheaper to acquire 30 MW, 120 MWh of capacity by retro-fitting 120,000 water heaters with control hardware and telecommunications. Surprisingly, it may even be cheaper to give away 120,000 ‘smart’ water heaters!

Artificial Neural Network Control of A Standalone DC Microgrid

Abstract: This paper proposes a novel artificial neural network (ANN) based control method, integrated with droop control, for control of an islanded DC microgrid. The ANN controller is trained based on ADP (approximate dynamic programming) using LM (Levenberg-Marquardt) algorithm. A FATT (Forward Accumulation Through Time) algorithm is applied to calculated Jacobian matrix. The ANN performance is evaluated by using switching models of power DC converters. Performance of ANN in DC microgrid shows that the proposed controller has the ability to maintain voltage stability of standalone DC microgrid and manage the power sharing among the parallel-connected distributed generation units. For different transient scenarios, the ANN controller in DC microgrids also performs very well to tolerate load disturbances and track voltage references rapidly.

Economic Planning for Remote Community Microgrid Containing Solar PV, Biomass Gasifier and Microhydro

Abstract: Remote and scattered population of Pakistan have no access to national grid, while grid extension to these areas is an uphill task. Most people in far flung areas live without electricity, where decentralized generation based on renewable sources is the only way for the provision of electricity. The renewable energies are site specific and climate dependent therefore; integrated renewable energy system are deployed which can play significant role in bringing prosperity to the poverty stricken people lives by meeting their energy demands. Due to the stochastic behavior of renewable energy sources hybrid energy systems are preferred because it is more reliable and efficient. This paper deals with the economic planning of hybrid energy system of such that in the absence of one source the other can take over for cost effective energy production. We have performed economic analysis of three renewable sources Solar PV, Biomass and microhydro in HOMER. A comparative analysis is made taking into account the pros and cons of each hybrid model and best possible hybrid energy system is selected for the proposed project site. It is evident from the simulation results that hybrid energy system is more reliable and prominent solution towards the worse energy crises of the nation.

Participation of a Smart Community of Consumers in Demand Response Programs

Abstract: The penetration of renewable energy resources and demand response programs causes several management issues, such as network instability. Several research projects are currently investigating and surveying several methods to enhance the network reliability. This paper represents a smart model of community grid that contains a central management unit and several consumers, producers and prosumers. In the proposed model, the community manager is able to control the consumption and generation of the resources by establishing contracts with its members. The community manager utilizes a single period optimization problem for minimizing its operation costs by applying different types of demand response programs and the use of renewable resources. In the case study, an internal low voltage distribution network of a real university campus is considered as the community grid, in order to test and validate the proposed model.

Comparison of μPMU and PMU

Abstract: Phasor Measurement Units (PMUs) have been used for several years to record information on power system, especially in transmission system. Their ability to synchronize to Global Positioning System (GPS) time, enables them to make accurate measurements of angle differences. However, due to their cost and the small angle differences they are rarely used in distribution system. The recently developed micro Phasor Measurement Unit (μPMU) claims a capability of micro-second resolution and milli-degree accuracy, which is 100 times the resolution of traditional transmission-type PMU. Therefore, μPMUs could be an extremely useful tool for distribution systems and microgrids. To better understand the advantages of μPMUs compared to traditional PMUs, this paper provides the experimental results of a comparative testing of these two devices based on the C37.118.1 standard for Synchrophasor [1].

Graph Theory and Critical Load-Based Distribution System Restoration using Optimal Microgrids Formation

Abstract: Customer survivability and well-being can be enhanced, after a natural disaster, by efficiently restoring critical loads in a distribution system. Microgrids with distributed generation can improve resilience in case of power outages caused by natural events. This paper presents a graph theory-based distribution system restoration strategy using optimal microgrids formation. The restoration focuses on critical loads powered by distributed generation sources installed in radial distribution system. Specifically, a Minimum Spanning Tree (MST) search algorithm has been developed that maximizes the amount of critical load restored based on priority information, while satisfying the operational constraints of radial distribution systems. The proposed method has been tested on the modified IEEE 37 and 123-bus test systems. The simulation results validate the effectiveness of the proposed algorithm.

Bad Data Injection Attack Propagation in Cyber-Physical Power Delivery Systems

Abstract: The coupling between information, communication and computing elements with the physical components of power systems introduces new cyber and cyber-physical security concerns. Addressing these concerns requires novel methods that complement the legacy and existing security solutions. Attacks such as bad data injection can cause disruptions that transcend the cyber realm and affect the physical world. This paper introduces a graph-based attack propagation model that simulates a bad data injection attack and executes a heuristic defense strategy using power system state estimation. We use the state estimator to identify maliciously injected data and adopt physical security metrics to decide attack mitigation actions. Visualization from analysis performed by this propagation simulation can guide the operator at the control center to take appropriate action to minimize disruption of the physical power system operation due to bad data injection attacks.

Intelligent Method for Online Adaptive Optimum Coordination of Overcurrent Relays

Abstract: In power distribution systems, various abnormal events like faults may happen sometimes, which requires a reliable protective system. Overcurrent relays are most commonly employed in distribution systems among other types of protection systems. For the overcurrent relays, the coordination between them is very important in protection system. Coordination is to find the most appropriate settings for each relay including time dial settings (TDS) and pick up current settings. Current optimal coordination methods are developed under assumption of constant load and fixed DG output, which is a static condition. Therefore, they may not provide most appropriate, optimal settings of each relay for coordination in distribution system. This paper presents an intelligent online adaptive optimum coordination method for overcurrent relays using genetic algorithm for distribution systems when there are variations of load and distributed generations outputs. We have presented evaluation studies to demonstrate the proposed method.

Modeling and Control of Battery Energy Storage System for Providing Grid Support Services

Abstract: Managing intermittency and uncertainty caused by large scale penetration of renewable energy is a challenge in maintaining the real-time operation of a power system. A Battery Energy Storage System (BESS) has shown promising results in maintaining the reliability and operation of a reduced inertia power system by providing grid support services. A BESS can be modeled to alleviate frequency-voltage variations which results due to imbalance between generation and demand in a power system. This paper demonstrates the modeling and control of a grid size BESS for providing primary and secondary frequency response and voltage support. A simple BESS model is developed while maintaining the detailed behavior of BESS in the power system. The model is developed as a user written model in a commercial transient stability program PSLF. A technical overview of BESS is illustrated along with the various modes of operation and operational constraints like State of Charge (SoC), charge and discharge rate. The proposed positive sequence transient stability BESS model results are validated with electromagnetic transient (EMT) based program like PSCAD/EMTDC.

Solar Power Forecasting with Model Selection Analysis

Abstract: Solar power has been growing at an exponential rate during the recent years. Due to the increasing share of solar energy in the grid and the associated uncertainties, the task of solar power forecasting is very crucial and challenging. In this study, a specific PV site in the state of Florida is considered. Various forecasting models are constructed with combinations of multiple training lengths and feature selections. Using the past instances of power output and selected features such as temperature and wind speed, the forecasting accuracy is compared for the linear regression model, gradient boosting model, and neural network model.

Maximizing the Revenue of Energy Storage Participants in Day-Ahead and Real-Time Markets

Abstract: Determining the expected revenues from services provided by energy storage in a market is very important for investment decisions. Arbitrage in day-ahead and real-time markets provides revenue streams that depend on the operational strategy, energy market prices, and uncertainty. This paper proposes optimization models to maximize the revenue of energy storage systems (ESS) that participate in both day-ahead and real-time energy markets. We proposed a strategy where the real-time market can increase the total revenue while keeping its risk decoupled from day-ahead market revenue. A quadratic programming model is used to determine the optimal day-ahead dispatch that maximizes the operator’s revenue of a price-maker ESS. The optimal dispatch is then modified by the results of a dynamic mixed integer optimization problem, which models the real-time market participation. Uncertainties in the day-ahead and real-time price forecasts are handled by back-casting and by normal error models, respectively. PJM market historical prices are used in this paper. Price sensitivities with respect to the energy storage operation are modeled as a part of the method. Results show that both day-ahead and real-time markets can provide significant arbitrage opportunities. The economic viability of four ESS technologies is assessed.

Controller Design of Voltage Source Converter Using Nyquist Array

Abstract: In this paper a controller is designed for voltage source converters (VSC) using Nyquist array. Real systems existing in industry are nonlinear systems with multiple inputs and multiple outputs (MIMO). Such systems are always affected by different undesired factors like noise and distortion. But multivariable control design for linear systems is based on theories which are robust against noise, disturbances and uncertainties. DC and AC part of VSC are affected with disturbances which should be controlled. Thus, a Nyquist array is applied to VSC to study design and analysis of multivariable control based on the presented theories. The proposed controller is illustrated by simulation.

Comparison and Simulation of the Level-Shifted and Phase-Shifted Modulation for a Five-Level Converter for Integration of Renewable Sources

Abstract: Two H-bridge converters are cascade-connected in order to extend the power rating of grid-connected converters. This structure is known as a Cascaded H-Bridge converter. A cascaded H-bridge multilevel converter is introduced in this paper with a detailed discussion about the PI controller based closed-loop control system for the Static Var Compensator (STATCOM) application. This research work incorporates both phase shifted and level shifted multi-carrier based Pulse Width Modulation (PWM) with comprehensive comparisons. Simulation results are presented accordingly to manifest the efficacy and productivity of the proposed model for grid-connected multilevel converters. The benefits of this model are the simplicity of the control, modulation techniques and the quick response to the reactive power adjustment by adjusting the DC bus voltage. The performance of the Cascaded H-Bridge Converter (CHB) model is tested in MATLAB Simulink.

Mapping and Modeling Interdependent Power, Water, and Gas Infrastructures

Abstract: Although various aspects of interdependencies among Power, Water, and Gas (PWG) infrastructures have been studied in the last couple of decades, there still exists void of modeling techniques capable of revealing the interdependencies among real-world infrastructures. This paper presents review of the state-of-the-art knowledge on interdependent critical infrastructure (ICI) modeling techniques along with delineation and discussion of interdependencies at transmission and distribution levels among PWG networks. The present study will also outline the suitability of various approaches to work with real-time infrastructure monitoring data that is becoming abundantly available in the recent years. The paper also highlights some directions on future research in interdependency modeling as well as suggestions on improving real-time interdependent models in operational and physical aspects.

Impacts of Distributed Energy Resources and Load Models on Conservation Voltage Reduction

Abstract: Several studies and field tests have shown the potential of conservation voltage reduction (CVR) to decrease peak demand, energy consumption, and system losses. Nonetheless, the energy savings achievable by CVR is dependent on the load model, which could be constant power, current, impedance, or any combination of these models. Also, the use of distributed energy resources (DERs) at the distribution level presents a challenge to successful CVR implementation as these resources could cause voltage fluctuations in the system. This paper studies the impact of load models on CVR implementation in a distribution system feeder interfaced with renewable DERs. Load flow analyses are carried out using constant power (PQ) and constant impedance (Z) load models, respectively, and the resulting effects on feeder losses and energy consumption are observed as CVR is implemented. In addition, the impacts of DERs and voltage regulation devices on the feeder voltage profile are analyzed. The feeder losses showed opposite trends with constant PQ and Z loads as CVR is implemented. Overall, the results showed varied impacts of load models and DER output on feeder losses, energy consumption, and bus voltages in the distribution network.

Lighting Consumption Optimization in an Office Building for Demand Response Participation

Abstract: Due to daily increment of electricity demand all around the world, the use of renewable energy resources and the methods of energy optimization are being important. Since the lighting systems have a pivotal role in the energy consumption of the buildings, the optimization of the lighting system should be effective. Hence, the focus of this paper is to minimize the lights consumption of an office building, while participating in demand response programs. The methodology of this work is proposed as a linear optimization problem that manages the generation of a renewable energy resource, which supplies a part of the energy consumption of the building. The lighting system of the building consists of the several laboratorial and commercial equipment, utilizing different communication interfaces. For the case studies, the amount of the renewable energy generation, total consumption of building, and the consumption of the lights in a real research building are considered.

Emulation of Anomalies for Wide-Area Monitoring, Protection and Control System Development

Abstract: For security and stability in smart grid development, identification and reactions to external factors are emphasized through Wide-Area Monitoring Protection and Control (WAMPAC) systems. Anomaly detection and identification are critical to establishing a responsive, controllable grid architecture. In testing anomaly-detection algorithms for WAMPAC applications, there should be a benchmarking process for detection of anomalies and evaluating WAMPAC performance in the presence of anomalies. The ability to create, or emulate, anomalies within a testing environment of WAMPAC systems is a step towards achieving this capability. In this paper, the development and implementation of a software-controlled Anomaly and Fault Generator (AFG) into a 1000:1 scale emulated smart grid testbed is presented. The testbed uses Phasor Measurement Units (PMUs) for high accuracy, fidelity, and time synchronization of measurements. The AFG induces controlled faults and anomalous events into the system to evaluate the performance of anomaly detection systems and WAMPAC applications. System events include stolen breakers, electrical faults with variable fault resistance, and hijacking of transducers. High sample-rate, time-synchronized, measurements are also logged by the AFG to compare to WAMPAC system results.

Modeling of PMU Data Using ARFIMA Models

Abstract: Installing Phasor Measurement Units (PMUs) in the smart grid has played an important role in having more reliable and secure grid. Due to the high sampling rate (50 samples/s), PMU generates massive amount of data compared to the conventional SCADA system. Understanding the mathematical and statistical characteristics of the PMU data is a very crucial step to perform accurate modeling and estimation of the power system variables (Voltage (V), frequency (f), and phase angle (θ)). In this paper, we show the non-stationarity of the PMU data by applying Augmented Dickey-Fuller and Kwiatkowski-Phillips-Schmidt-Shin tests on a large data set from the EPFL campus grid. Then, we study the fractality of the PMU data by estimating the differencing parameter (d) in the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model. Our results call for adoption of ARFIMA models to model the PMU data in the smart grid.

Adaptive Protection Scheme for a Microgrid with High Levels of Renewable Energy Generation

Abstract: Deployment of high renewable energy based penetration in a distribution network increases the fault current levels and therefore it becomes imperative to review the protective device coordination study. Traditional relaying schemes may fail to protect the distribution system with high penetration of distributed generators (DGs) such as grid-tied photovoltaic, diesel generators and wind energy based systems. This paper investigates the impact on protective device coordination under high DG deployment. IEEE 13 bus test feeder has been modeled in ETAP software to perform the device coordination study with and without (photovoltaic) PV/wind power sources. A novel adaptive protective scheme is proposed using numerical relays compatible with IEC 61850 standard. To implement the algorithm, a laboratory based microgrid test bed has been modeled with logical nodes based on the IEC 61850 communication protocols. The limitation of modern numerical relays to update the settings in real-time has been discussed.

Reduction in Total Harmonic Distortion of Cascaded H-Bridge Multilevel Inverter with Using Phase Method

Abstract: Multi-level inverter have gained the popularity over traditional inverters due to low total harmonic distortion. Multilevel inverter is used for high power as well as low power applications. This paper analyzes the total Harmonic distortion of 3, 5, 7 and 9 levels by using Equal phase method. Cascaded H-Bridge configuration is used for analysis. The total harmonic distortion analysis of three, five, seven and nine level are studied and then compared their outputs through fast Fourier transform. Cascaded H-Bridge Multi-level inverter is simulated by using MATLAB/Simulink and results are obtained. Simulation results indicates that total Harmonics Distortion reduces with increase of voltage levels. Total harmonic distortion for 3 level is 41.42%, for 5 level is 39.46%, for 7 level is 26.78% and for 9 level is 22.56%.

A Survey on Transient Stability Studies for Electrical Power Systems

Abstract: Electrical Energy is the most important form of energy in modern times and has found a distinguished place as electrical power system in the research domain. This giant has ever increased in its size requiring more attention towards its stability. Transient Stability Studies, have found particular attention in operation and control of power systems as failure due to its ignorance has led to cascade tripping and a total black out in the past. This paper attempts to summarize the most relevant work done in Transient Stability Studies over the past three decades. Applications of Transient Stability Studies are provided and work done in each category is accounted. The future scopes or suggested research options by various authors have been highlighted.

Wide-Area Situational Awareness based Power System Stabilizer Tuning with Utility Scale PV Integration

Abstract: Historically, poorly damped electromechanical oscillations exhibited by synchronous generators have caused power system blackouts. With variable generation sources such as PV power integrated in power systems, the high variability and lack of sufficiently accurate forecasts, triggers electromechanical oscillations. Optimally tuned power system stabilizers (PSSs) are expected to provide effective damping to these electromechanical oscillations. The effects of the variations of the PV power and system disturbances on the speed deviations of the generators are captured and used in the formulation of the cost function to be optimized. The IEEE 68 bus 16 generator benchmark New England–New York power system integrated with utility scale PV generation sources is studied.

A Survey on the Effects of False Data Injection Attack on Energy Market

Abstract: False Data Injection Attack (FDIA) is considered to be one of the major cyber threats of power systems in recent time. It can make arbitrary changes in the results of state estimation without being detected by the traditional bad data detector. Though it can cause some physical damages, the attacker can exploit some monetary benefits as well. The idea of implementing FDIA on energy market was first revealed in 2010, and since then, there had been a significant amount of work to date. This paper is intended to help those who want to work in this field. It summarizes the main aspects of those works which are published till the beginning of 2018. It also suggests some potential research directions based on state-of-the-art literature.

HEMS Operation via MILP

Abstract: Advanced technology in communication and control enables electric utility customers to provide assistance to the grid through demand side management (DSM) and home energy management systems (HEMSs). This capability may mitigate the variability from increased penetration of variable resources, such as wind and photovoltaics (PV) leading to grid operation flexibility. Home load, distributed generation, and storage can assist in meeting such flexibility if they are managed properly. In this paper, we present an optimization model for HEMS based on mixed integer linear programming (MILP). The model schedules the operation of several home appliances, local generation, and home energy storage depending on the electricity price signal. The considered objective is minimizing the incurred cost by the household. Further, feed-in tariff policy is considered allowing the home to export and sell any surplus energy to the grid. Case studies show the reduction in imported energy and cost achieved after applying the HEMS. Further, superior execution times were recorded in all case studies indicating the effectiveness of the proposed model in terms of computational speed.

System Dynamic Model Validation using Real-Time Models and PMU Data

Abstract: High-resolution synchrophasor data recorded during disturbances has made dynamic model validation more feasible. While several papers discuss the validation of individual components such as governors and exciters, few consider the validation of the system model as a whole. It is a challenging problem for larger systems due to the sheer number of dynamic models, and hence the states and parameters involved. This paper describes the process of validating the entire system model, up to an interconnect level using an actual disturbance event and the PMU data captured during it. We use the state estimator snapshot captured just before the inception of the disturbance, which is also known as the real-time model. The paper details the important steps of setting up dynamic model data in these real-time models, and addresses issues commonly encountered during validation such as correcting “bad data”. The methodology is illustrated using an actual large system model.

Root Cause Identification of Power System Faults using Waveform Analytics

Abstract: A methodology intended to automatically identify the underlying cause of fault in transmission lines is presented. Fault data recorded by different Intelligent Electronic Devices (IEDs) in Common format for Transient Data Exchange for power systems (COMTRADE) is replayed to extract statistically significant features. Time domain features of the recorded data have been investigated. A fault triggering algorithm based on voltage sag/swell is used for segmentation of pre-fault, fault and post-fault period in the recorded data. One-way Analysis of Variance (ANOVA) is used to find the required confidence interval to validate the statistical significance of the selected features. The proposed method uses machine learning approach to classify faults, as they occur in the system, into preselected fault root cause groups. The developed algorithm has been tested using real field dataset. The results show that the methodology is sound and covers a wide range of root causes of faults.

Efficient Grounding Method for DC Microgrid with Multiple Grounding Points

Abstract: DC microgrid (MG) is an important structure of future electrical power systems, with many advantages in off grid and application for grid connected operation. It is considered for its stability, safety, reliability, and optimum efficiency. Power produced with renewable energy sources or changes in different stages or for reliability issue is controlled by power electronic advices like converters and inverters. Although some researches could invent new methods for dealing with challenges in microgrid systems, some aspects are still under research. Meanwhile, grounding architectures impact on power electronic converters needed to investigate more. This research presents the grounding method acts as a high impedance grounding in normal condition to avoid DC stray currents flow, and for fault transients acts as solid grounding. Then ground fault current is limited through a limiter resistor, to the permissible value, resulted in protecting power electronic interfaces.

Optimal Placement of DG in Active Distribution System Incorporating Performance Based Rates

Abstract: This paper proposes a novel method to calculate reliability model of distribution system using a hybrid of Monte Carlo simulation and 2m point estimate method. The proposed reliability model is used to solve Distributed Generation placement considering service regulation implementing Performance Based Rates through reward and penalty schemes. This optimization problem aims to maximize profit by placing DG at vantage points.

Security Considerations in Transmission Planning for Creating Large Synthetic Power Grids

Abstract: Synthetic power grids are test cases designed to spur innovation, as they contain no confidential energy infrastructure information and thus can be freely published. For building large and complex synthetic grids, this paper proposes a methodology to address security considerations in the transmission planning stage. The two-stage approach runs contingencies and adds lines strategically to fix violations while meeting other validation criteria. Results are shown for 10,000 and 70,000 bus cases.

PhasorToolBox – A Python Package for Synchrophasor Application Prototyping

Abstract: Despite the rapid expansion of open source computer software applications, the development of synchrophasor applications has not kept pace. This paper presents a development package for quick prototyping of synchrophasor applications using Python programming language, specifically for the retrieval of data from any device that adopts the IEEE C37.118.2-2011 standard. The package provides a high-level interface for developers to quick prototyping for the rapid development of advanced synchrophasor applications. The asynchronous design pattern makes the packet robust to handle a high volume of I/O without compromising real-time performance.