Browsing by Subject "Power system"
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Item Mixed-integer programming in power systems : the interdiction and unit commitment problems(2019-08) Huang, Bing, Ph. D.; Baldick, Ross; Bard, Jonathan; Hanasusanto, Grani; Santoso, Surya; Zhu, HaoMixed integer programming (MIP) maximizes (or minimizes) a linear objective subject to a set of constraints. In particular, one of the constraints for a MIP is that at least one of the variables can only take integer values. This technique has been widely studied in operations research and a MIP can be solved efficiently by commercial solvers. In this dissertation, two power system problems namely, an interdiction problem and a unit commitment problem, are formulated and solved with MIP techniques. The studies presented in this dissertation focus on extracting the special features embedded in the problems and formulating the problems such that they can be solved using the available MIP techniques. The objective of an interdiction problem in a power system is to find a set of the most critical or vulnerable components to secure and reliable operation. Before formulating the problem, we need to study the outages and their impacts in power systems in depth. Once a critical component of a power system fails, the outages including generator and load trips can sequentially spread and frequently lead to large blackouts. The efforts to develop a model to analyze cascading outages is first summarized. Reports about cyber attacks on the Ukraine power grid revealed that one or more malwares were deliberately developed to attack industrial facilities, with power systems as one of the major targets. Another potential cyber threat to secure operation of power transmission grids involves Internet of Things (IoT) demand attacks. Increasingly, Internet connections are available to devices with high energy consumption such as air conditioners and water heaters. However, these new connections expose the control of new electric loads to potential manipulation by attackers. To help assess the effects of cyber attacks, we develop numerical experiments and define different types of cyber attacks to simulate Ukraine-style cyber attacks and IoT demand attacks to study the system responses in a North American regional interconnection system. Based on the studies in cascading outage analysis and cyber attack simulations, an interaction problem between a defender (e.g. system operator) and an attacker (e.g. terrorist) in a power system is formulated as a MIP and a "short-term" impact of an attack is considered using a cascading outage anylsis (COA) tool. A demonstrative case study with an existing method is presented and numeric studies with "short-term" impacts with COA model are ongoing. The unit commitment (UC) problem in a power system is another MIP problem. UC determines the start-up and shut down schedules of generating units to meet forecast demand in a short term future (few hours to few days). It is critical to precisely represent the generating units in a UC problem to maximize the social welfare, which is the objective of the problem. The formulation of two types of unit namely, combined-cycle gas units and pumped-storage hydro units in a UC problem are presented in this dissertation. In recent years, combined-cycle units (CCUs) have been operated as providers of flexibility needed due to the increasing shares of renewables. Consequently, optimization models have been proposed to determine the configuration of CCUs. However, most of the existing models assume that any transition between configurations finishes in a single interval. This assumption is often violated in reality, as a transition might last up to a few hours during which the CCU has limited dispatchability. In this work, a mixed-integer programming formulation that represents the transition ramping of CCUs is summarized and the formulations of ramping constraints are discussed. Numerical studies are performed on an illustrative test system and a Mid-continent Independent System Operator (MISO) system. As one of the mature technologies for energy storage, pumped-storage hydro is able to provide services in a time range from minutes to days. Particularly, pumped storage hydro units are useful for enhancing the integration of renewable generations that are naturally intermittent. Optimization models have been proposed to determine strategies to dispatch a energy storage unit in the system. However, most of existing work assumes the output from a energy storage unit is continuous. This assumption is not true for a pumped storage hydro unit. Inspired by the work of modeling a combined cycle unit in the unit commitment problem, this work proposes a configuration based pumped storage hydro model that removes the invalid continuous outputs assumption in order to enhance the use of pumped storage hydro resources in the system. By introducing three "configurations," namely, pumping, generating and "alloff" or off-line, for a pumped storage hydro unit, the proposed model can more accurately reflect the practical operations of pumped storage hydro units in the day-ahead market. A comprehensive review of the existing pumped storage hydro models and industry practices is presented. The definition of configurations of a pumped storage hydro unit and the transitions between the configurations during operation are revealed and discussed in detail to describe the proposed model. A case study is presented to illustrate the proposed model.Item Optimization tools for emerging challenges in power systems(2022-05-06) Zhang, Nan; Leibowicz, Benjamin D.; Hanasusanto, Grani; Kutanoglu, Erhan; Carvallo, Juan PabloThe expansion and operation of electric power systems have always been viewed as a critical economic and social topic. With the rapid evolution of the electricity industry, a combination of factors, including the increasing renewable penetration, deployment of storage, customer preferences, and environmental regulations, bring challenges to traditional decision-making paradigms in power systems. Therefore, well-designed operations research applications in power system are becoming increasingly important to maintain and improve their performance. This dissertation aims to deploy novel optimization models and methods to address these emerging challenges and support the decision-making in modern power systems. The dissertation starts at the customer side in power system operations. In Chapter 2, we consider the problem of operating a battery storage unit in a home with a rooftop solar photovoltaic (PV) system so as to minimize expected long-run electricity costs under uncertain electricity usage, PV generation, and electricity prices. We implement a data-driven dynamic programming (DDP) algorithm that uses historical data observations to generate empirical conditional distributions and approximate the cost-to-go function, and formulate two robust data-driven dynamic programming (RDDP) algorithms to address the overfitting. Numerical results reveal that DDP and RDDP outperform common existing methods with acceptable computational effort. We also show that implementation of these superior operational algorithms significantly raises the break-even battery cost compared with existing feed-in tariff (FIT) or net energy metering (NEM) program. Following from Chapter 2, we move forward to the system-wide resource planning decision-making framework regarding distributed generation. In Chapter 3, we develop a sequential optimization framework that allows a utility to anticipate distributed energy resource (DER) adoption and choose its own generation, transmission, and distribution investments accordingly. Specifically, we adapt a capacity expansion model to represent both centralized and decentralized decision-making paradigms between the utility and customers under various electricity rate structures. By constructing a real-world case study of a utility in the Western U.S., we show that a centralized planning approach could save 7% to 37% of total system costs over a 15-year time horizon. We demonstrate that centralized decision-making deploys substantially more utility-scale solar and distributed storage compared to a decentralized decision-making paradigm. We also analyze the technological difference between the two paradigms and demonstrate how a utility could largely overcome the complications of decentralized distributed resource decision-making by incentivizing regulators to develop electricity rates that more closely reflect time- and location-specific, long-run marginal costs. Motivated from Chapter 3, we continue developing another complex decision-making framework in power system planning that includes more decision-makers on demand-side resources. In Chapter 4, we construct a novel bilevel programming model that co-optimizes a utility's capacity expansion and rate design decisions in the presence of multiple prosumers, including load-shifting customers, distributed PV adopters, and electric vehicle (EV) owners. We further develop a case study on a test power system and present several key findings. We show that co-optimized rate designs can more successfully incentivize behind-the-meter decisions and lead to substantial cost reduction in the whole power system compared to traditional, uncoordinated capacity planning. We also show that time-varying rates determined by the net load profile can both increase the utility's profit and decrease the total cost, and they enable the utility to design more effective locationally differentiated feed-in tariff policies. Finally, we find that providing smart EV charging outlets with their own electricity rates allows the utility to induce beneficial EV load shifting that reduces total system costs. In Chapter 5, we study another critical issue, resource adequacy, which refers to the ability of a power system to reliably satisfy electricity demands using its available resources. Monitoring and maintaining RA is becoming increasingly complex and challenging due to the drastic, ongoing changes in the electricity technologies, policies, and markets. In this chapter, We first diagnosis the with traditional RA assessments. We analyze the current RA assessment practices in integrated resource planning (IRP) by examining 11 plans from load serving entities over U.S., and show that LSEs could improve RA assessments in their IRPs by developing net load forecasts that capture load uncertainty and impacts of demand-side resources, or considering risks in market imports with its effect on reliability performance. In the second part, we develop a technical RA framework that applies a dispatch model to study the performances of RA assessments under different modeling assumptions. By constructing a case study, we distinguish operational details that are critical to include in any accurate RA assessment from details that are computationally burdensome but do not significantly affect the evaluation of RA. We show that the representations of detailed chronological operations of thermal generators and storage units are essential for accurate RA assessments. We also present the need of developing new metrics that beyond traditional expectation-based metrics in identifying the impact of modeling choices on RA assessments. Lastly, we show that non-economic dispatches without cost considerations can lead to fairly accurate RA assessments when coordinated with detailed operational strategies. The four core chapters of this dissertation improve the economic and reliability performance of power systems by leveraging novel optimization tools, and they yield high-level implications that can benefit to electricity decision-makers including regulators, utilities, and end-use customers. While each chapter looks at different components in power systems, they serve the common goal of applying operations research models and methods to address the emerging challenges and support the decision-making in modern power systems. The findings in this dissertation can be valuable in the ways to develop more economic, reliable, and sustainable electric power systems.Item Protection system lab experiments with overcurrent and differential relays(2020-05) Flint, Alison Ewing; Santoso, SuryaThis report presents the theory and application of two ubiquitous protection schemes, overcurrent protection and differential current protection, with the design of experiments and exercises for electrical engineering students. The objective of this undertaking is educational, so that students can learn, understand, and execute various operations pertaining to basic functions of relays. The result is a set of instructions for laboratory practices and exercises (lab manuals) which introduces relays in the context of the greater power system protection, and uses equipment modules to present relay functions.Item Strategic power dispatch methods for reducing cost and risk in energy generation(2021-08) Wu, Yutong; Nikolova, EvdokiaIn the United States, power generation is currently managed by Independent System Operators in a myopic way day by day. The widely adopted power dispatch method, Economic Dispatch, aims to clear the market with the cheapest available power generators while maintaining some level of grid stability. In this thesis, we show that the grid will bear an expensive long- term generation cost and high risk in grid resilience in the next thirty years if we continue to use the traditional Economic Dispatch. Meanwhile, we pro- pose a number of alternative dispatch methods, notably Balanced Dispatch and Two-Phase Risk Dispatch, that effectively reduce cost and risk for energy generation. Via extensive empirical experiments on the Texas grid, ERCOT, we show that our proposed methods could result in billions of savings in US dollars every year for ERCOT alone.Item Using fast-responding resources to control frequency in a power system(2016-12-13) Peydayesh, Mansoureh; Baldick, Ross; Santoso, Surya; Arapostathis, Aristotle; Bickel, Eric; Adib, ParvizFrequency control is one of the major concerns of power system operators. Frequency varies as the result of a supply-demand mismatch. Due to possible destructive outcomes of large frequency variations, several mechanisms are in operation to keep supply and demand in balance. Increasing penetration of non-dispatchable intermittent generation resources may increase power supply volatility, which makes frequency control more challenging. Emerging utility-scale storage technologies with reasonable cost have participated in electricity markets in recent years. Because of fast-ramping capabilities of these resources, one of their attractive applications is providing frequency regulation service. However, the amount of energy they can produce or consume is limited due to their restricted storage capabilities. Thus, in spite of their fast response to a deployment signal, their duration of response is bounded. In this thesis, we focus on using fast-responding resources to control frequency in power systems. In this research, the first question is if the participation of these resources in the regulation market have any adverse effect on the frequency control performance of the system. If the answer is yes, the next question is what is the best strategy to not only prevent the negative consequences but also improve the benefits of using fast-responding resources for frequency control. For this research, the system of Electric Reliability Council of Texas (ERCOT) is selected. All power system studies related to frequency control require an appropriate dynamic model. In this dissertation, a simplified model is constructed, which represents the ERCOT system frequency response during a short period of time after a contingency. The model is validated and tuned against system frequency measured by Phasor Measurement Units. Especially in situations of not having information about system individual units, this simplified model is highly advantageous. However, to study system frequency during normal conditions, a more comprehensive model is essential. Thus, we develop ERCOT Frequency Modeling and Analysis Tool (EFMAT), which has the required level of details and accuracy to simulate system frequency. All proposed approaches of modeling and parameter tuning in this research are also applicable to other power systems. In order to answer our research questions, we start with investigation of ERCOT Fast-Responding Regulation Service (FRRS). For selected historic days, conventional regulation providers are replaced by a storage system providing FRRS. For various capacities of the storage system, frequency is simulated using EFMAT and a system frequency control performance index is calculated. Comparing calculated index of different simulations can reveal the effect of FRRS capacity on the system performance. The simulations are repeated for several FRRS deployment strategies similar to the strategies of other North America power markets along with our proposed modifications. Three different storage systems are assumed in the simulations: one with unlimited stored energy, one with 6 minutes energy duration, and one with 15 minutes energy duration. Finally, FRRS optimal capacity and equivalency ratio between FRRS and conventional regulation are defined and calculated for the best deployment strategy.