Transmission line modeling for the purpose of analog power flow computation of large scale power systems

This thesis proposes methods for modeling electric power transmission lines for the purpose of analog power flow computation of power system networks. Theoretical and applicable circuit models for analog transmission lines are presented with a focus on power-flow studies which concentrates on the steady state or static behavior of electrical power transmission lines. With this approach the wave propagation and reflection is not as much of a concern as the steady state line voltages and current flows. Because of this lumped circuit equivalent line models are utilized. The primary goal is to develop a computational alternative for power system analysis that overcomes obstacles currently faced by traditional digital computation methods. Analog computation is proving to be a viable alternative and has notable advantages over digital computers. In order to contrive a practical analog emulator precise models for power system components are required. Specifically this thesis develops a realization of an electric power transmission line model for such a purpose.The transmission line model traditionally utilized in power-flow computation is a lumped parameter pi-model equivalent circuit. In digital computation the shunt elements and sometimes the series resistances are often times neglected in order to simplify the power flow equations and subsequently speed up the calculation times. Prior research in analog computation for power flow analysis also utilized these simplified line models. A fully reconfigurable pi-model is presented here for an analog computation approach. No components have been neglected resulting in a more accurate line model with fast computation times. The ability to remotely reconfigure each component on the line model makes this model universal. The design could easily be fabricated to an integrated circuit to represent a large scale network and configured to match a real world system. In addition, the model is easily expanded to form a distributed parameter line model by interconnecting multiple components in series. This allows for computational analysis of the power system states throughout the transmission line which is traditionally not done in digital power flow computation due to computational restraints.M.S., Electrical Engineering -- Drexel University, 200

Power system security assessment through analog computation

This dissertation proposes a methodology for power system security assessment through analog computation. By exploiting the strengths of analog computation a more robust security assessment can be performed as compared to traditional methods. Security assessment is currently performed by power system operators utilizing digital computers and determines the power system structure, states and level of security based on telemetered data and knowledge of the system. Ideally this process would occur in real time but due to the limitations of digital computers and telemetry systems the security assessment is currently conducted at periodic intervals of ten to fifteen minutes. This process requires a tremendous amount of computation for large systems. In order to provide updated assessment at such time intervals, not even in real time, numerous assumptions and simplifications of the power system models and analyses are required to simplify and speed up the digital computations. Due to its inherent speed and computational efficiency analog computation is proving to be a viable alternative.Analog computation by definition is continuous in time and embodies an entirely different paradigm to computing as compared to discrete time methods. Security assessment for digital computers consists of topology estimations, state estimation and contingency analysis. The theory and practical approaches to these tasks through digital, discrete time, computational methods are fairly mature at this point in time but do not translate directly to analog computation. A robust analog computation engine along with corresponding computational theory is required in order to make use of analog methods for power system security assessment. This dissertation provides the relevant theory, hardware realization and application of an analog computer for power system security assessment.Ph.D., Electrical Engineering -- Drexel University, 200

Static generator model for analog power flow computation

Paper presented at ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Island of Kos, Greece.Accurate analog models of power system components are required in order to realize an analog computation engine for power systems. Analog computation is an area of continued interest and has certain advantages over traditional digital computation. Among the advantages are physically realizable solutions and significantly faster computation times. This paper focuses on the development of an algebraic static generator model designed for a previously proposed method of analog power flow computation. Prior research in this field has focused on modeling generators dynamically without VAR limitations. The static model proposed here can yield steady state results faster than the prior dynamic models and provides added functionality by incorporating VAR limitations. The model is constructed and verified via analog behavior modeling in PSpice software

Simulation of Man in the Middle Attack On Smart Grid Testbed

Over the past decade, the frequency of cyber attacks against power grids has steadily increased, requiring researchers to find and patch vulnerabilities before they can be exploited. Our research introduces the prototype of a man-in-the-middle attack to be implemented on a microgrid emulator of a smart grid. We present a method of violating the integrity and authentication of packets that are using the IEEE Synchrophasor Protocol in a controlled environment, but this same approach could be used on any other protocol that lacks the proper overhead to ensure the integrity and authenticity of packets. In future research, we plan to implement and test the attack on the previously mentioned smart grid testbed in order to assess the attacks feasibility and tangible effects on Wide Area Monitoring and Control applications, as well as propose possible countermeasures. For this paper, we developed a working simulation of our intended attack using the software ModelSim 10.4. The attack will modify network packet data coming from a Schweitzer Engineering Labs (SEL) Phasor Measurement Unit (PMU) hardware sensor, which provides a stream of precise timing values associated with current and voltage values, as these measured values are en route to the Open Phasor Data Concentrator (OpenPDC) application running on a Windows server. Our simulation provides and validates all of the necessary code in order to program a Field Programmable Gate Array and execute our attack on the testbed in future research

Blockchain for Power Grids

Sharing information is an important part of regulating and maintaining efficient and safe power grids. This project’s goal is to develop a way of using blockchain technology to share transaction information among different power grids in a secure, controlled, monitored, and efficient manner. The biggest concern regarding the data is integrity. By leveraging blockchain technology, the data will be reliable and resilient to attacks, such as man-in-the-middle and data spoofing attacks. The Hyperledger Fabric implementation provides a permissioned network in which power grids will act as nodes that maintain ledger information. By using a distributed ledger to validate transactions through the process of consensus, the system can share information in a manner that is more secure and transparent than traditional information sharing systems in which data is less secure and takes longer to validate. The additional layers of security and speed that Hyperledger technology provides help to prevent issues, such as power grid failures, that could stem from the latency or integrity issues involved with traditional methods of validating, processing, and reacting to shared data

Demand response impacts on off-grid hybrid photovoltaic-diesel generator microgrids

Hybrid microgrids consisting of diesel generator set(s) and converter based power sources, such as solar photovoltaic or wind sources, offer an alternative to generator based off-grid power systems. The hybrid approach has been shown to be economical in many off-grid applications and can result in reduced generator operation, fuel requirements, and maintenance. However, the intermittent nature of demand and renewable energy sources typically require energy storage, such as batteries, to properly operate the hybrid microgrid. These batteries increase the system cost, require proper operation and maintenance, and have been shown to be unreliable in case studies on hybrid microgrids. This work examines the impacts of leveraging demand response in a hybrid microgrid in lieu of energy storage. The study is performed by simulating two different hybrid diesel generator—PV microgrid topologies, one with a single diesel generator and one with multiple paralleled diesel generators, for a small residential neighborhood with varying levels of demand response. Various system designs are considered and the optimal design, based on cost of energy, is presented for each level of demand response. The solar resources, performance of solar PV source, performance of diesel generators, costs of system components, maintenance, and operation are modeled and simulated at a time interval of ten minutes over a twenty-five year period for both microgrid topologies. Results are quantified through cost of energy, diesel fuel requirements, and utilization of the energy sources under varying levels of demand response. The results indicate that a moderate level of demand response can have significant positive impacts to the operation of hybrid microgrids through reduced energy cost, fuel consumption, and increased utilization of PV sources

Cyber-Physical Systems Approach for Wide Area Control Applications

This paper describes a cyber-physical system approach for wide area control applications in power grids. Specifically, it is proposed to use cyber-physical system modeling methodology, to include explicit physical and behavior-based models, to facilitate the application of traditional controller design and analysis to wide area control applications. Our proposed approach allows for modeling the physical elements of the power grid (e.g. transmission network, generation, loads and measurement devices), the cyber components (e.g. execution of reactive software algorithms in data processing and control software), and the concurrent and sequential interactions of cyber and physical components. The cyber-physical interactions are critical for wide area control applications due to the multiple spatial and temporal scales present in these systems. The modeling methodology is formulated into a classical closed loop controller which the plant and the controller contain cyber and physical elements. The proposed approach allows for studying the impacts of cyber-physical interactions, evaluating the effectiveness and resiliency of wide area controllers, and can be applied as a tool to benchmark and derive specifications for final designs. The methodology is applied to a phasor measurement unit based wide area control of a static VAR compensator in a MATLAB/Simulink environment

Leveraging MapReduce and Synchrophasors for Real-Time Anomaly Detection in the Smart Grid

The rapid detection of anomalous behavior in SCADA systems such as the U.S. power grid is critical for system resiliency and operator response in cases of power fluctuations due to hazardous weather conditions or other events. Phasor measurement units are time synchronized devices that provide accurate synchrophasor measurements in power grids. The rapid deployment of PMUs enable improved real-time situational awareness to grid operators through wide area measurement systems. However, the quantity and rate of measurements obtained from PMUs is significantly higher than traditional devices, and continues to grow as more are deployed. Efficient algorithms for processing large-scale PMU data and notifying operators of anomalies is critical for real-time system monitoring. In this paper, we propose a novel, two-step anomaly detection approach that processes raw PMU data using the MapReduce paradigm. We implement our approach on a multicore system to process a dataset derived from real PMUs containing 4; 500 PMUs ( 18 million measurements). Our experimental results indicate the proposed approach detects constraint and temporal anomalies in under three seconds on 8 cores. Our work demonstrates the applicability of MapReduce for designing anomaly detection algorithms for the smart grid, and motivates the creation of novel MapReduce approaches for other SCADA applications

Leveraging Single Board Computers for Anomaly Detection in the Smart Grid

Smart Grid Technology is becoming an integral part of ensuring reliable and resilient operation of the power grid. The high sample rate and time synchronization of Phasor Measurement Units (PMUs) can provide enhanced situational awareness and more detailed information on power system dynamics as compared to traditional SCADA systems. A smart grid system must be able to detect alarm events (such as sudden voltage fluctuations or drops in current) in close to real-time. However, the communication network and bandwidth requirements to transfer large amounts of PMU data for realtime analysis is problematic. In this paper, we propose the use of a decentralized architecture for rapidly analyzing PMU data using single board computers to provide energy efficient monitoring locally in the power grid. This approach reduces communication requirements and enables real-time analysis. We present a novel anomaly detection scheme and test our approach on a real dataset of 1.4 million measurements derived from 8 PMUs from a 1000:1 scale emulation of a working power grid. Our results show that a single Raspberry Pi is sufficient to analyze data from multiple PMUs at a rate suitable for real-time analysis