Showing papers presented at "Clemson University Power Systems Conference in 2016"

On stability of islanded low-inertia microgrids

Abstract: As the number of distributed energy sources (DERs) increases in a microgrid (MG), the likelihood of frequency and voltage instabilities increases. In particular, the control of frequency and voltage becomes a challenge in an islanded mode due to the inherent low-inertia feature of DERs compared to a grid-tied mode where there is a grid support. This instability problem becomes worse for low or medium voltage low-inertia MGs, where the line impedance is dominantly resistive. The goal of this paper is to demonstrate the stability and power quality problems that can occur in islanded medium voltage MGs. PSCAD/EMTDC simulation results for an MG with a high share of low-inertia power generation units illustrate the importance of the frequency and voltage stability as power utilities adopting more DERs.

Analysis on central and distributed architectures of solar powered DC microgrids

Abstract: In this work, central and distributed architectures of DC microgrids for rural electrification are analyzed under various operating conditions In the proposed scheme, a single household consumer forms the atomic nanogrid unit which may integrate its resources in a scalable model with the community to form a microgrid, without dependence of the national grid The flow of power between houses and the microgrid is implemented through a bidirectional flyback converter The operation of proposed scheme for two different architectures, ie distributed generation distributed storage architecture (DGDSA) and centralized generation centralized storage architecture (CGCSA) is evaluated at various distribution voltage levels and conductor sizes Modified Newton Raphson Method based analysis is performed for both architectures which show that distributed architecture has significant advantages over central architecture due to higher efficiency, low voltage drop and lower line losses Further, the scalable nature with minimum installation cost for distributed architecture makes it more favorable for rural electrification applications in comparison to central architecture The simulated results are also verified using a scaled down version of hardware implementation

Navigating the challenges of Internet of Things (IoT) for power and energy systems

Abstract: Internet of Things (IoT) is the connection of the physical world to the Internet. It is fast emerging as the sustainable solution for providing access to affordable and clean energy all around the world. The utilities with IoT can have real-time feedback capabilities to better understand the customer needs and therefore make intelligent decisions to improve their service experience. With IoT, the electric power networks will be more secure, reliable, resilient and sustainable. IoT certainly opens the door to a lot of opportunities but it also has a few challenges associated with it. Some of these challenges include sensing, power management, cyber security, system complexity, and wireless and cloud connectivity. To grow and develop IoT, it becomes essential to have innovative sensing technology, a broad variety of wire and wireless standards, the lowest power solutions for any application, built-in hardware security technology, IoT solutions for everyone and not just experts, and an ecosystem of cloud partners to enable seamless integration. This paper presents the challenges and the recommended solutions associated with IoT.

Dissolved gas analysis to identify faults and improve reliability in transformers using support vector machines

Abstract: Dissolved gas analysis (DGA) and its key-gas ratios (C2H2/C2H4, CH4/H2, C2H4/C2H6) are the most widely used fault diagnostic tests for transformers This technique monitors the concentration of various gases in transformer oil and uses it to interpret the type of fault In this study, support vector machines (SVM) is proposed to classify and predict electrical faults in transformers depending on the key-gas ratios concentrations A dissolved gas analysis data obtained from published papers are used as a sample for the training and test set with a supervised machine learning from MATLAB software Results indicate that SVM method can achieve good accuracy under the circumstance of small training data

Model of a hybrid distributed generation system for a DC nano-grid

Abstract: A large segment of the world's population lives in rural areas that are geographically isolated, remote and sparsely populated. Nano grids employing hybrid energy systems (HES) based on photovoltaics (PV) and wind farms are considered to be an effective option to electrify remote and isolated areas which are far from conventional grids. This is applicable to areas that receive high averages of solar radiation and sufficient average wind speed annually. In this research investigation, a DC nano-grid was modelled, simulated and optimized for a hybrid solar-PV and wind, with energy storage and a back-up diesel generator for Umzinyathi district in KwaZulu-Natal Province, South Africa. A site survey was conducted, wind resource and solar radiation data obtained for the purpose of load forecasting and system modelling. HOMER software was used for system modelling. Minimum cost optimization of the system was carried out taking into consideration the costs of system components, hourly solar radiation and rating parameters as inputs into the simulation program. Sensitivity variables were specified to examine the effect of their uncertainties on system performance. Based on simulation results, the optimal system comprises of a 100kW PV array, thirteen 7.5kW wind turbines, 20kW diesel generator, and 96 Trojan T-105 deep cycle batteries. The net present cost (NPC), cost of energy (CoE) and payback period of the optimal system were found to be $459 545, $0.248/kWh and 4 years respectively. The economic and environmental analysis indicated that it is more advisable to electrify remote settlements using a DC nano-grid based on hybrid systems with multiple renewable sources as they have lower operating costs and more environmental friendly due to the reduced dependence on diesel generating units.

Review of Electric Spring: A new smart grid device for efficient demand dispatch and active and reactive power control

Abstract: This paper deals with theory, modeling, applications and limitations of an Electric Spring (ES) by reviewing the published literature in this area. An ES, a custom power device (power electronic converter), is gradually emerging as an eminent member of smart grid. It provides stability to the grid, by controlling real and reactive power so as to regulate voltage of the grid and is considered to be operating under the influence of intermittent and unpredictable renewable energy sources (RES). ES is connected in between grid and load and hence it can damp out the oscillations of the grid. Load is bifurcated into groups based on its tolerable voltage range. Critical load is required to have constant voltage profile with no tolerance to voltage variation and non-critical load can have this tolerance in a widely specified band so as to swing along the power pattern of RES. Optimally dispersed Electric Springs throughout the grid can provide stability while acting in unison. Operation of ES effectively caters the requirement of demand side management.

Comparative analysis of dynamic model reduction with application in power systems

Abstract: In this paper, three algorithms for dynamic model reduction of power systems are compared The significance and accuracy of approximate bi-simulation, balance truncation, and modal truncation technique are investigated While the bi-simulation method is applied to power systems for the first time, its detailed formulation is derived for a constrained linear system The full linearized dynamic model of a nonlinear system is determined and used as the input of the dynamic model reduction techniques The capability of each technique in keeping dominant oscillation modes after dynamic reduction is utilized as the comparison criterion As a result, this reduced model led to faster analysis and control of the power system All three reduction techniques are simulated over the dynamic 39-bus New England test system

Secure SCADA communication network for detecting and preventing cyber-attacks on power systems

Abstract: This paper presents a scaled model for supervisory control and data acquisition (SCADA) communication network, which monitors and controls power distribution in residential areas. We recommend to integrate advanced communication technologies into current SCADA system to improve its performance in monitoring and controlling the operations of the power systems. This paper further proposes to use ad hoc wireless sensor networks in the residential areas as a part of SCADA communication in power distribution network. Moreover, a trust-based intrusion detection and prevention (IDP) technology built on monitoring, detecting, and rehabilitation (MDR) approach is applied to the proposed network for cyber security analysis. To verify the performance of the proposed SCADA communication network using MDR, simulation is carried out for three different cases and results demonstrate that the proposed MDR approach helps in detecting and preventing the malicious nodes in the network effectively.

Probability of distribution network pole failures under extreme weather conditions

Abstract: Distribution poles support the overhead distribution equipment such as overhead line conductors, pole mounted transformers, pole mounted capacitors, switches, etc. Falling trees, wind, flying debris and fault current forces due to extreme weather cause electrical faults and can knock down distribution poles resulting in power outages, system damage and millions of dollars in replacement costs. The objective of this paper is to demonstrate a model for assessing the probability of failures of distribution poles versus weather parameters. The failure of a pole can be determined from two factors: (1) The stress on the pole and (2) the withstand capability (strength) of the pole. The stress depends on a very large set of parameters and it is a complex computational task. The challenge is to develop a model that will provide the stress on a pole as a function of all pertinent parameters that affect pole stress. The strength of the pole depends on the type of pole (material, size), installation type, and age/deterioration of pole. Through this model, the vulnerable areas and breakage points of the distribution network can be predicted by developing and quantifying an analytical model of the Distribution System. By doing so, the bottlenecks in Distribution Systems can be studied and reliability and resilience of the system can be analyzed. This analysis forms the foundation for developing Outage Prediction and Management Systems which is necessary for hardening the distribution network and increasing its resiliency during severe weather situations.

A study on the effect of distributed generation on short-circuit current

Abstract: In short-circuit studies, phase shifts in transformers (e.g., connected in wye-delta or vice versa) make difficult to calculate fault current flowing in sequence-component networks. Therefore, they are often ignored because the magnitude of fault current is much more of interest than phase angles from the protection point of view (e.g., overcurrent relays). As high-capacity distributed generation (DG) resources are being deployed into distribution networks, they may change the direction and the phase angle of fault current and cause abnormal operations of directional or distance relays. Thus, the objective of this paper is to develop a short-circuit analysis algorithm able to (a) calculate changes in phase shifts caused by transformers in sequence networks with high-capacity DG sources and (b) analyze the effect of not only various capacities (e.g., 10, 30, and 50 percent) of DG resources but also various locations of faults on current that flows during a short circuit. To verify the developed algorithm, using MATLAB, case studies that generate a single line-to-ground fault on (a) the high- and low-voltage sides and (b) a weakly meshed network are presented.

Smart AMI based demand-response management in a micro-grid environment

Abstract: Reliable operation of the electrical grid requires balancing between generation and energy demand at any time instant Increasing penetration of intermittent sources of alternative generation compromises reliability and introduces significant price volatility As a solution, demand response strategies have been studied to provide the necessary demand-side flexibility for utility to absorb some volatility In this paper, a demand-response management (DRM) system is proposed, where a service provider finds a mutual optimal solution for the utility and the customers in a microgrid setting This could be used by a service provider interacting with the respective customers and utility under the existence of some DRM agreements In this study, a micro-grid consisting of a smart neighbourhood of twelve customers is taken as experimental case study and an advanced metering infrastructure (AMI) is implemented Based on the formulation of an optimization problem which exploits price-responsive demand flexibility and the AMI infrastructure, a win-win-win strategy is presented By shaping load patterns according to market pricing, the proposed method led to higher cost savings for the flexible customers and the utility, with consistent profit margins achieved by the service provider Results for a range of typical scenarios are presented to demonstrate the effectiveness of the proposed demand-response management framework

Publishing real-time microgrid consumption data on the web of Linked Data

Abstract: Decentralising the power systems management brings clear advantages for the grid and for the stakeholders (consumers, generators, operational and management actors). The grid decentralisation can be achieved using microgrids. Some microgrids emerge worldwide, working as small energy islands. It is admitted that ontologies and open (Semantic) Web standards can form a basis for advanced communication architectures in smart grids. True, ontologies enable semantic interoperability and logical reasoning; the Linked Data principles enable the discovery of new information on the web. This paper reports on the use of these formalisms and principles to develop a new information system for a microgrid site already in place. More specifically, we developed a new ontology to represent time series of multiple observations, and made real-time consumption data available on the web as Linked Data. This enables consumption reporting, and enables other researchers to test their algorithms against real-time consumption data.

Real time digital simulation of voltage-based controller for electric vehicle charging

Abstract: Electric vehicle (EV) is a topic of increased interest due to the several advantages it can provide. However, adopting a large number of EVs can cause problems to the electric utilities. Therefore, proper management of EV charging is necessary. While several centralized methods were proposed to control the charging process, few autonomous methods were suggested. This work presents an autonomous controller that handles the charging rate of the EV adaptively. It does not require any kind of communication. The performance of the controller is demonstrated using a real time digital simulator (RTDS). The results show the effectiveness of the proposed controller in handling the charging process. The controller prevents line overloading and voltage violations in the system and achieves fair charging among the different EVs connected to the system.

Event based reduction of power fluctuation using cyber-physical control-communication network in smart grids

Abstract: Integration of Information and Communication (ICT) technologies with power flow management and control to support varying load demand is the hallmark of advanced power networks such as smart grids. Issues arising due to the complexity of these systems can be potentially solved by designing control-communication algorithms based on the information available at any instant of time. This paper presents a unique approach for optimized control of a smart grid considering its hybrid and complex nature. The developed technique uses a cyber-physical network controlling the system having different operating states under different operating conditions. This communication based hybrid control algorithm reduces the output power fluctuations in the events of changing dynamics. The information related to power quality is updated to the operator through a feedback mechanism in order to meet desirable efficiency, reliability and safety standards.

Voltage stability improvement of a multi-machine system using HVDC

Abstract: This paper presents a critical scenario of voltage stability study on a multi-machine system when subjected to different loading patterns. High Voltage Direct Current (HVDC) links control and the effects of its compensating devices' effects on voltage stability are also investigated. A static approach with the use of P-V (Power-Voltage) and Q-V (Reactive power-Voltage) curve was used in this study. The simulation results show that with the HVDC line, more power can be transmitted with lower line losses and improved voltage profile. The transformer tap changers and the switchable HVDC compensating devices also play a major role in stabilizing the voltage profile under different loading conditions. Simulations were run using DigSILENT PowerFactory, a software package for power systems simulation and analysis.

Solar farm hourly dispatching using super-capacitor and battery system

Abstract: Utilizing solar energy is essential to having a clean and healthy Earth for generations to come. However, because solar power is intermittent, caused by weather changes such as clouds or temperature fluctuations, power distributers cannot rely on solar farms as a consistent power source. The solution is the integration of an energy storage system capable of absorbing and producing the necessary power to maintain a constant power for a specific amount of time, known as dispatching. This paper demonstrates a successful dispatching scheme of solar energy using a hybrid energy storage system (HESS) consisting of a battery energy storage system (BESS) and a supercapacitor energy storage system (SESS). The HESS utilizes the high energy density property (the ability to charge and discharge large amounts of energy, preferably at low frequency) of lead acid batteries and the high power density property (the ability to rapidly charge or discharge energy, at high frequency) of supercapacitors together to invoke a synergy of low-frequency and high-frequency energy storage components. The HESS is designed to increase the longevity of the traditional BESS while enabling the capability to dispatch the solar energy.

Analysis of real-world power quality disturbances employing time-frequency distribution

Abstract: The traditional method for the analysis of power quality (PQ) disturbances is fast Fourier transform (FFT) which suffers from spectral leakage phenomenon, and results in erroneous assessment in the presence of nonstationary PQ disturbances Also, it cannot provide any time information as PQ indices are computed in the frequency domain only Regarding the limitations of the FFT, in this paper Page time-frequency distribution (TFD) method is utilized for the analysis of three-phase nonstationary, nonsinusoidal, and unbalanced PQ disturbances Utilizing the Page TFD technique, PQ indices such as effective rms voltage and current, apparent power, active power and power factor are redefined in the time-frequency domain, and the efficacy of the proposed method is evaluated by applying it to a synthetic and two real-world PQ disturbances provided by National Renewable Energy Laboratory (NREL) The analysis results show that the proposed method provides more accurate results than the FFT, and time-varying signature of the real-world PQ disturbances under nonstationary, nonsinusoidal, and unbalanced operating conditions

Ultra-low cost and solar storm secured local DC electricity to address climate change challenges for all economies

Abstract: Contrary to the outcome of the “history of war of currents”, the local generation of direct current (DC) power has the technical and economic advantages of emerging as the ultimate choice of power in the 21st century. Local DC power generated by photovoltaics (PV), batteries, electric vehicles (EVs), situational intelligence, intelligent loads, real-time monitoring of grid, cyber security, internet of things (IoT) and resiliency to space weather threats are the enabler of DC nanogrid and DC microgrid based ultra-low cost electricity infrastructure.

An artificial neural network-based peak demand and system loss forecasting system and its effect on demand response programs

Abstract: This paper describes a Neural Network application to reduce the computational complexities in a smart grid environment by predicting peak demand and losses for the next operating day Mitigating peak demands and losses could significantly reduce outage risks and increase costs savings, hence improving the reliability and efficiency of Electrical Service Providers (ESPs)

Dishonest Gauss Newton method based power system state estimation on a GPU

Abstract: To control a fast changing power system in real time, it is important to accelerate the computation processes related to it. Being one of the most time-consuming processes, state estimation needs to be made fast and scalable. Different methods were introduced in the literature over time to serve the purpose. It is high time to make the best out of them to find the fastest estimator with current parallel computation technology. In this study, the dishonest Gauss Newton method is implemented in a Graphics Processing Unit (GPU). As the method is not well explored in the literature, the performance of it is investigated first. Then different aspects of the parallel implementation is explained. It runs in hundreds of microseconds for IEEE 118-bus systems which is the fastest according to the authors findings. For very large systems, the required configuration of a GPU and the corresponding time are also estimated.

Calculation of relay currents in active weakly-meshed distribution systems

Abstract: This paper deals with short-circuit calculation, as one of the basic Distribution Management System (DMS) applications. It is common practice in short-circuit calculations to neglect loads, line and transformer shunt parameters as well as influence of the pre-fault state. This paper shows that some of these approximations could lead to incorrect results when calculating currents at relay locations (relay currents) in distribution systems. Consequently, an efficient short-circuit calculation procedure for active weakly-meshed distribution systems is proposed. Procedure is based on back/forward sweep with compensation for loops applied to faulted network models. The proposed procedure is robust and easy for programming and the results are significantly more accurate than those obtained by the oversimplified methods commonly used. Results show that errors made by listed approximations could be as high as 16% for a 20 KV test system, which can seriously affect the setting and coordination of protective equipment.

A smart PV inverter controller with PMU capability

Abstract: This paper introduces the control of a photovoltaic (PV) interface converter ready to offer auxiliary service - reactive power control - that also has Phasor Measurement Unit capability. A prototype of the controller is implemented using a National Instruments Compact RIO and tested using Hardware In the Loop techniques. Experimental results demonstrate the converter functionalities.

Distributed control of converters in a DC microgrid using agent technology

Abstract: The objective of this paper is to describe the implementation of an innovative agent-based architecture of controllers for stand-alone DC microgrids The controllers regulate voltage to the required level and balance load flow in all converters In addition, they maintain a deterministic time frame of a few 10's of milliseconds for a system with 10's of converters when there is no limitation in the number of events which might happen concurrently The paper proposes application of publish-subscribe agent-based controllers which are identified based on a numerical analysis as the most efficient technology for real-time coordination of power converters in the defined microgrid To test the design, a sample DC shipboard microgrid including four converters was used as a case study Results of implementing the agent-based publish-subscribe control system using Java Agent DEvelopment Framework (JADE) are illustrated in paper The results show that the upper-time limit for task management is consistent and independent of the number of converters

An information infrastructure framework for smart grids leveraging SDN and cloud

Abstract: Smart grids are recognized as the next-generation power grid that uses digital information and communications technology to create an advanced, automated, and efficient energy network among a wealth of electronic appliances, meters, and energy producing and distributing devices. As more complex and distributed interactions among these different components are envisioned, an open, scalable, and manageable framework is needed to support the communication and computing needs. This paper proposes an innovative method to derive scalable information infrastructure for smart grids. The framework well aligns with the emerging micro-grid operational model of the smart grid. A prototype framework is being developed consisting of CloudLab [1], GENI [2] wired and wireless networks, and real-time power system platform at the RTPIS Lab [3].

Medium voltage dynamic voltage restorer (DVR) based on DFCM converter for power quality improvement

Abstract: In the present electric power grids, power quality issues are recognized as a crucial concerns and a frequently occurring problem possessing significant costly consequence such as sensitive load tripping and production loss. Consequently, demand for high power quality and voltage stability becomes a pressing issue. Dynamic voltage restorer (DVR), as a custom power device, is one of the most effective solutions for “restoring” the quality of voltage at its load-side terminals when the quality of voltage at its source-side terminals is disturbed. In this paper, a new DVR topology based on double flying capacitor multicell (DFCM) converter for medium-voltage application has been proposed. The advantage of the proposed DVR is that it does not need any line-frequency step-up isolation transformer, which is bulky and costly, to be connected to medium-voltage power grid. The proposed DVR topology obtains the required active power from the energy storage feeding the dc link of the DFCM converter. The pre-sag compensation method, which is explained in detail, is used to restore amplitude and angle of the sensitive load voltage. Moreover, an approach based on d-q synchronous reference frame to determine DVR reference voltages is utilized. The proposed DVR topology is simulated and results to illustrate its performance under various conditions of voltage sag compensation are provided.

Dynamic loads and micro-generation method for a House Management System

Abstract: Several approaches have been proposed in the context of the smart grids and microgrids to validate the active participation of the end consumers in the energy management process The present paper focuses in a model with dynamic application of optimization algorithm to manage the active participation of the end consumers in the demand response events The method is performed using real and simulated loads and real micro-generation data from Polytechnic of Porto and from University of Sao Paulo The methodology includes the operation requirements for each resource, namely loads, micro-generation and electrical grid A case study with two scenarios is presented bearing in mind the difference between resources profiles of two countries The results of dynamic management model in domestic consumers are discussed for the participation in a 2 hours demand response event with same time characteristics In both scenarios, the power limit depends on the loads consumption and micro-generation

Flexible data acquisition, compression, and reconstruction in advanced metering infrastructure

Abstract: This paper will design a general, flexible, and efficient framework for data acquisition, data compression, and data reconstruction in advanced metering infrastructure (AMI). Compressed distributed sensing will be utilized to acquire load data from smart meters and transmit them to the central control unit. Different sparse binary measurement matrices will be exploited for different time instances when data acquisitions are performed. Each sparse binary measurement matrix corresponds to one data gathering scheme using compressed distributed sensing. This paper proposes to perform joint reconstruction of the two-dimensional load profile at the central control unit. Both spatial and temporal correlations will be explicitly employed to facilitate data reconstruction with high accuracy and fidelity. Meanwhile, the desirable data compression ratio can be achieved.

A stochastic approach to optimum placement of photovoltaic generation in distribution feeder

Abstract: Distribution systems are being challenged by voltage fluctuation due to the increasing penetration of distributed photovoltaic generation. In this paper, a stochastic approach based on kernel density estimation is proposed to identify the optimal location for the PV plant installation in distribution systems so that the voltage deviation and network losses are minimized. In order to demonstrate the effectiveness of the proposed method, the model of a real distribution feeder has been used. The feeder is located in Walterboro, SC, USA, which is composed of 38-bus and includes a photovoltaic plant. The simulation model has been validated against field measurement so that the simulation results of the proposed stochastic method are reliable and realistic.

Optimal demand response bidding and pricing mechanism with fuzzy optimization: Application for a virtual power plant

Abstract: In this paper, a virtual power plant (VPP) that consists of generation and controllable demand is enabled to participate in the wholesale market. VPP makes renewable energy sources (RES) and distributed generations (DGs) controllable and observable to the system operator. The main objective is to introduce a scheme that optimizes the bidding strategies and maximizes the VPP's profit on day-ahead basis. To achieve this goal, the VPP trades energy externally with a wholesale market, and trades energy and demand response (DR) internally with the consumers in its territory. That is, when generation exceeds demand, the VPP sells the excess energy to the market, and it buys energy from the market when the generation and reduction in demand due to DR scheme are less than the required demand in its territory. Fuzzy optimization is proposed in this work to consider the uncertainty in the RES.

Electrical power consumption monitoring in hotels using the n-Core Platform

Abstract: One of the problems that affects the management of large buildings is energy consumption. Wireless sensor networks are presented here as a great ally for the optimization of energy consumption. Thanks to the integration of temperature, lighting, humidity, air quality or gas sensors, combined with different actuators that can monitor and regulate the level of work of energy-consuming devices, and software management and analysis, energy consumption in large buildings is significantly reduced without decreasing the availability and effectiveness of resources. Hotels are a kind of ideal building to implement these systems. Nebusens has launched a pilot in a hotel, so energy consumption points can be monitored (HVAC, boilers, etc.), thanks to the implementation of the sensors that are integrated into its platform n-Core using its management software Polaris. Thus, the energy consumption has been reduced by up to 35% since the introduction of the pilot without any decrease in quality of service.