Browsing by Subject "power system"
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Item Integration of Electric Energy Storage into Power Systems with Renewable Energy Resources(2012-10-26) Xu, Yixing 1985-This dissertation investigates the distribution and transmission systems reliability and economic impact of energy storage and renewable energy integration. The reliability and economy evaluation framework is presented. Novel operation strategies of energy storage and renewable energy are proposed. The method for optimizing the energy storage sizing and operation strategy in order to achieve optimal reliability and economy level is developed. The objectives of the movement towards the smart grid include making the power systems more reliable and economically efficient. The rapid development of the large scale energy storage technology makes it an excellent candidate in achieving these goals. A novel Model Predictive Control (MPC)-based operation strategy is proposed to optimally manage the charging and discharging operation of energy storage in order to minimize the energy purchasing cost for a distribution system load aggregator in power markets. Different operation strategies of energy storage have different reliability and economic impact on power systems. Simulation results illustrate the importance of the energy storage operation strategies. A hybrid operation strategy which combines the MPC-based operation strategy and the standby backup operation strategy is proposed to flexibly adjust the reliability and economic improvement brought by energy storage. A particle swarm optimization approach is developed to determine the optimal energy storage sizing and operation strategy while maximizing reliability and economic improvement. A reliability and economy assessment framework based on sequential Monte Carlo method integrated with the operation strategies is proposed. The impact on the transmission systems reliability brought by energy storage and renewable energy with the proposed operation strategies is investigated. Case studies are conducted to demonstrate the effectiveness of the proposed operation strategies, optimization approach, and the reliability and economy evaluation framework. Insights into how energy storage and renewable energy affect power system reliability and economy are obtained.Item Intelligent Economic Alarm Processor (IEAP)(2013-08-06) Guan, YufanThe advent of electricity market deregulation has placed great emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a competitive environment. This creates a need for better ways of correlating the market activity with the physical grid operating states in real time and sharing such information among market participants. Choices of command and control actions may result in different financial consequences for market participants and severely impact their profits. This work provides a solution, the Intelligent Economic Alarm Processor to be implemented in a control center to assist the grid operator in rapidly identifying the faulted sections and market operation management. The task of fault section estimation is difficult when multiple faults, failures of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets approach has been proposed to tackle the complexities. In this approach, the fuzzy reasoning starting from protection system status data and ending with estimation of faulted power system section is formulated by Petri-nets. The reasoning process is implemented by matrix operations. Next, in order to better feed the FRPN model with more accurate inputs, the failure rates of the protections devices are analyzed. A new approach to assess the circuit breaker?s life cycle or deterioration stages using its control circuit data is introduced. Unlike the traditional ?mean time? criteria, the deterioration stages have been mathematically defined by setting up the limits of various performance indices. The model can be automatically updated as the new real-time condition-based data become available to assess the CB?s operation performance using probability distributions. The economic alarm processor module is discussed in the end. This processor firstly analyzes the fault severity based on the information retrieved from the fault section estimation module, and gives the changes in the LMPs, total generation cost, congestion revenue etc. with electricity market schedules and trends. Then some suggested restorative actions are given to optimize the overall system benefit. When market participants receive such information in advance, they make estimation about the system operator's restorative action and their competitors' reaction to it.Item Long term voltage stability analysis for small disturbances(2009-05-15) Men, KunThis dissertation attempts to establish an analytical and comprehensive framework to deal with two critical challenges associated with voltage stability analysis: 1. To study the new competitive environment appropriately and give more incentive for reactive power supports, one has to evaluate the impacts of distributed market forces on voltage stability, which complicates the voltage stability analysis. 2. Accurately estimating voltage stability margin online is always the goal of the industry. Industry used to apply static analysis for its computation speed at the cost of losing accuracy. On the other hand, dynamic analysis can result in more accurate estimation, but generally has a huge computation cost. So a challenge is to estimate the voltage stability margin accurately and efficiently at a reasonable cost, especially for large system. Considering the first challenge, this dissertation applied eigenvalue based bifurcation analysis to allocate the contribution of voltage stability. We investigate how parameters of the system influence the bifurcations. Three bifurcations (singularity induced bifurcation, saddle-node and Hopf bifurcation) and their relationship to several commonly used controllers are analyzed. Their parameters? impact on these bifurcations have been investigated, from which we found a way to allocate the contribution by analyzing the relative positions of the bifurcations. For the second challenge, a new fast numerical scheme is developed to estimate voltage stability margin by intelligently adjusting the load increase ratio. A criterion, named EMD (Equilibrium Manifold Deviation) criterion, is proposed to gauge the accuracy of the estimation. And based on this criterion, a new computation scheme is proposed. The validity of our new approach is proven based on the well-known Runge-Kutta-Fehlberg method, and can be extended to other explicit single-step methods easily. Numerical tests demonstrate that the new approach is very practical and has great potential for industrial applications. This dissertation extends our new numerical scheme to stiff systems. When a system is ill-conditioned, the implicit method would be applied to achieve numerical stability. We further demonstrate the validity to combine the intelligent load adjustment technique with the implicit method to save the computation cost without loss of accuracy. This dissertation also delves into the auto detection of stiffness of the power system, and extends our new numerical scheme to general sytems.Item Measurement enhancement for state estimation(2009-05-15) Chen, JianAfter the deregulation of the power industry, power systems are required to be operated efficiently and economically in today?s strongly competitive environment. In order to achieve these objectives, it is crucial for power system control centers to accurately monitor the system operating state. State estimation is an essential tool in an energy management system (EMS). It is responsible for providing an accurate and correct estimate for the system operating state based on the available measurements in the power system. A robust state estimation should have the capability of keeping the system observable during different contingencies, as well as detecting and identifying the gross errors in measurement set and network topology. However, this capability relies directly on the system network configuration and measurement locations. In other words, a reliable and redundant measurement system is the primary condition for a robust state estimation. This dissertation is focused on the possible benefits to state estimation of using synchronized phasor measurements to improve the measurement system. The benefits are investigated with respect to the measurement redundancy, bad data and topology error processing functions in state estimation. This dissertation studies how to utilize the phasor measurements in the traditional state estimation. The optimal placement of measurement to realize the maximum benefit is also considered and practical algorithms are designed. It is shown that strategic placement of a few phasor measurement units (PMU) in the system can significantly increase measurement redundancy, which in turn can improve the capability of state estimation to detect and identify bad data, even during loss of measurements. Meanwhile, strategic placement of traditional and phasor measurements can also improve the state estimation?s topology error detection and identification capability, as well as its robustness against branch outages. The proposed procedures and algorithms are illustrated and demonstrated with different sizes of test systems. And numerical simulations verify the gained benefits of state estimation in bad data processing and topology error processing.Item Power System Online Stability Assessment using Synchrophasor Data Mining(2013-04-30) Zheng, CeTraditional power system stability assessment based on full model computation shows its drawbacks in real-time applications where fast variations are present at both demand side and supply side. This work presents the use of data mining techniques, in particular the Decision Trees (DTs), for fast evaluation of power system oscillatory stability and voltage stability from synchrophasor measurements. A regression tree-based approach is proposed to predict the stability margins. Modal analysis and continuation power flow are the tools used to build the knowledge base for off-line DT training. Corresponding metrics include the damping ratio of critical electromechanical oscillation mode and MW-distance to the voltage instability region. Classification trees are used to group an operating point into predefined stability state based on the value of corresponding stability indicator. A novel methodology for knowledge base creation has been elaborated to assure practical and sufficient training data. Encouraging results are obtained through performance examination. The robustness of the proposed predictor to measurement errors and system topological variations is analyzed. A scheme has been proposed to tackle the problem of when and how to update the data mining tool for seamless online stability monitoring. The optimal placement for the phasor measurement units (PMU) based on the importance of DT variables is suggested. A measurement-based voltage stability index is proposed and evaluated using field PMU measurements. It is later revised to evaluate the impact of wind generation on distribution system voltage stability. Next, a new data mining tool, the Probabilistic Collocation Method (PCM), is presented as a computationally efficient method to conduct the uncertainty analysis. As compared with the traditional Monte Carlo simulation method, the collocation method could provide a quite accurate approximation with fewer simulation runs. Finally, we show how to overcome the disadvantages of mode meters and ringdown analyzers by using DTs to directly map synchrophasor measurements to predefined oscillatory stability states. The proposed measurement-based approach is examined using synthetic data from simulations on IEEE test systems, and PMU measurements collected from field substations. Results indicate that the proposed method complements the traditional model-based approach, enhancing situational awareness of control center operators in real time stability monitoring and control.Item Prognostic Control and Load Survivability in Shipboard Power Systems(2011-02-22) Thomas, Laurence J.In shipboard power systems (SPS), it is important to provide continuous power to vital loads so that their desired missions can be completed successfully. Several components exist between the primary source and the vital load such as transformers, cables, or switching devices. These components can fail due to mechanical stresses, electrical stresses, and overloading which could lead to a system failure. If the normal path to a vital load cannot supply power to it, then it should be powered through its alternate path. The process of restoring, balancing, and minimizing power losses to loads is called network reconfiguration. Prognostics is the ability to predict precisely and accurately the remaining useful life of a failing component. In this work, the prognostic information of the power system components is used to determine if reconfiguration should be performed if the system is unable to accomplish its mission. Each component will be analyzed using the Weibull Distribution to compute the conditional reliability from present time to the end of the mission. To determine if reconfiguration is needed, all components to a given load will be utilized in structure functions to determine if a load will be able to survive during a time period. Structure functions are used to show how components are interconnected, and also provide a mathematical means for computing the total probability of a system. This work will provide a method to compute the conditional survivability to a given load, and the results indicate the top five loads that have the lowest conditional survivability during a mission in known configuration. The results show the computed conditional survivability of loads on an all electric navy ship. The loads conditional survivability is computed on high/medium voltage level and a low voltage level to show how loads are affected by failing components along their path.