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Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can

Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can be divided into two parts. The first part of this dissertation focuses on developing a more accurate network model for TEP study. First, a mixed-integer linear programming (MILP) based TEP model is proposed for solving multi-stage TEP problems. Compared with previous work, the proposed approach reduces the number of variables and constraints needed and improves the computational efficiency significantly. Second, the AC power flow model is applied to TEP models. Relaxations and reformulations are proposed to make the AC model based TEP problem solvable. Third, a convexified AC network model is proposed for TEP studies with reactive power and off-nominal bus voltage magnitudes included in the model. A MILP-based loss model and its relaxations are also investigated. The second part of this dissertation investigates the uncertainty modeling issues in the TEP problem. A two-stage stochastic TEP model is proposed and decomposition algorithms based on the L-shaped method and progressive hedging (PH) are developed to solve the stochastic model. Results indicate that the stochastic TEP model can give a more accurate estimation of the annual operating cost as compared to the deterministic TEP model which focuses only on the peak load.
ContributorsZhang, Hui (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Thesis advisor) / Mittelmann, Hans D (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog

The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In the deregulated power system, locational marginal prices are used in transmission engineering predominantly as near real-time pricing signals. This work extends this concept to distribution engineering so that a distribution class locational marginal price might be used for real-time pricing and control of advanced control systems in distribution circuits.

In the deregulated power system, locational marginal prices are used in transmission engineering predominantly as near real-time pricing signals. This work extends this concept to distribution engineering so that a distribution class locational marginal price might be used for real-time pricing and control of advanced control systems in distribution circuits. A formulation for the distribution locational marginal price signal is presented that is based on power flow sensitivities in a distribution system. A Jacobian-based sensitivity analysis has been developed for application in the distribution pricing method. Increasing deployment of distributed energy sources is being seen at the distribution level and this trend is expected to continue. To facilitate an optimal use of the distributed infrastructure, the control of the energy demand on a feeder node in the distribution system has been formulated as a multiobjective optimization problem and a solution algorithm has been developed. In multiobjective problems the Pareto optimality criterion is generally applied, and commonly used solution algorithms are decision-based and heuristic. In contrast, a mathematically-robust technique called normal boundary intersection has been modeled for use in this work, and the control variable is solved via separable programming. The Roy Billinton Test System (RBTS) has predominantly been used to demonstrate the application of the formulation in distribution system control. A parallel processing environment has been used to replicate the distributed nature of controls at many points in the distribution system. Interactions between the real-time prices in a distribution feeder and the nodal prices at the aggregated load bus have been investigated. The application of the formulations in an islanded operating condition has also been demonstrated. The DLMP formulation has been validated using the test bed systems and a practical framework for its application in distribution engineering has been presented. The multiobjective optimization yields excellent results and is found to be robust for finer time resolutions. The work shown in this report is applicable to, and has been researched under the aegis of the Future Renewable Electric Energy Delivery and Management (FREEDM) center, which is a generation III National Science Foundation engineering research center headquartered at North Carolina State University.
ContributorsRanganathan Sathyanarayana, Bharadwaj (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible

The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible and controllable loads, bidirectional communications using smart meters and other technologies. Sensory technology may be utilized as a tool that enhances operation including operation of the distribution system. Addressing this point, a distribution system state estimation algorithm is developed in this thesis. The state estimation algorithm developed here utilizes distribution system modeling techniques to calculate a vector of state variables for a given set of measurements. Measurements include active and reactive power flows, voltage and current magnitudes, phasor voltages with magnitude and angle information. The state estimator is envisioned as a tool embedded in distribution substation computers as part of distribution management systems (DMS); the estimator acts as a supervisory layer for a number of applications including automation (DA), energy management, control and switching. The distribution system state estimator is developed in full three-phase detail, and the effect of mutual coupling and single-phase laterals and loads on the solution is calculated. The network model comprises a full three-phase admittance matrix and a subset of equations that relates measurements to system states. Network equations and variables are represented in rectangular form. Thus a linear calculation procedure may be employed. When initialized to the vector of measured quantities and approximated non-metered load values, the calculation procedure is non-iterative. This dissertation presents background information used to develop the state estimation algorithm, considerations for distribution system modeling, and the formulation of the state estimator. Estimator performance for various power system test beds is investigated. Sample applications of the estimator to Smart Grid systems are presented. Applications include monitoring, enabling demand response (DR), voltage unbalance mitigation, and enhancing voltage control. Illustrations of these applications are shown. Also, examples of enhanced reliability and restoration using a sensory based automation infrastructure are shown.
ContributorsHaughton, Daniel Andrew (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Switching surges are a common type of phenomenon that occur on any sort of power system network. These are more pronounced on long transmission lines and in high voltage substations. The problem with switching surges is encountered when a lot of power is transmitted across a transmission line
etwork, typically from

Switching surges are a common type of phenomenon that occur on any sort of power system network. These are more pronounced on long transmission lines and in high voltage substations. The problem with switching surges is encountered when a lot of power is transmitted across a transmission line
etwork, typically from a concentrated generation node to a concentrated load. The problem becomes significantly worse when the transmission line is long and when the voltage levels are high, typically above 400 kV. These overvoltage transients occur following any type of switching action such as breaker operation, fault occurrence/clearance and energization, and they pose a very real danger to weakly interconnected systems. At EHV levels, the insulation coordination of such lines is mainly dictated by the peak level of switching surges, the most dangerous of which include three phase line energization and single-phase reclosing. Switching surges can depend on a number of independent and inter-dependent factors like voltage level, line length, tower construction, location along the line, and presence of other equipment like shunt/series reactors and capacitors.

This project discusses the approaches taken and methods applied to observe and tackle the problems associated with switching surges on a long transmission line. A detailed discussion pertaining to different aspects of switching surges and their effects is presented with results from various studies published in IEEE journals and conference papers. Then a series of simulations are presented to determine an arrangement of substation equipment with respect to incoming transmission lines; that correspond to the lowest surge levels at that substation.
ContributorsShaikh, Mohammed Mubashir (Author) / Qin, Jiangchao (Thesis advisor) / Heydt, Gerald T (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Shunt capacitors are often added in transmission networks at suitable locations to improve the voltage profile. In this thesis, the transmission system in Arizona is considered as a test bed. Many shunt capacitors already exist in the Arizona transmission system and more are planned to be added. Addition of

Shunt capacitors are often added in transmission networks at suitable locations to improve the voltage profile. In this thesis, the transmission system in Arizona is considered as a test bed. Many shunt capacitors already exist in the Arizona transmission system and more are planned to be added. Addition of these shunt capacitors may create resonance conditions in response to harmonic voltages and currents. Such resonance, if it occurs, may create problematic issues in the system. It is main objective of this thesis to identify potential problematic effects that could occur after placing new shunt capacitors at selected buses in the Arizona network. Part of the objective is to create a systematic plan for avoidance of resonance issues.

For this study, a method of capacitance scan is proposed. The bus admittance matrix is used as a model of the networked transmission system. The calculations on the admittance matrix were done using Matlab. The test bed is the actual transmission system in Arizona; however, for proprietary reasons, bus names are masked in the thesis copy in-tended for the public domain. The admittance matrix was obtained from data using the PowerWorld Simulator after equivalencing the 2016 summer peak load (planning case). The full Western Electricity Coordinating Council (WECC) system data were used. The equivalencing procedure retains only the Arizona portion of the WECC.

The capacitor scan results for single capacitor placement and multiple capacitor placement cases are presented. Problematic cases are identified in the form of ‘forbidden response. The harmonic voltage impact of known sources of harmonics, mainly large scale HVDC sources, is also presented.

Specific key results for the study indicated include:

• The forbidden zones obtained as per the IEEE 519 standard indicates the bus 10 to be the most problematic bus.

• The forbidden zones also indicate that switching values for the switched shunt capacitor (if used) at bus 3 should be should be considered carefully to avoid resonance condition from existing.

• The highest sensitivity of 0.0033 per unit for HVDC sources of harmonics was observed at bus 7 when all the HVDC sources were active at the same time.
ContributorsPatil, Hardik U (Author) / Heydt, Gerald T (Thesis advisor) / Karady, George G. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2015
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Description
With growing concern regarding environmental issues and the need for a more sustainable grid, power systems have seen a fast expansion of renewable resources in the last decade. The uncertainty and variability of renewable resources has posed new challenges on system operators. Due to its energy-shifting and fast-ramping capabilities, energy

With growing concern regarding environmental issues and the need for a more sustainable grid, power systems have seen a fast expansion of renewable resources in the last decade. The uncertainty and variability of renewable resources has posed new challenges on system operators. Due to its energy-shifting and fast-ramping capabilities, energy storage (ES) has been considered as an attractive solution to alleviate the increased renewable uncertainty and variability.

In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed to study the cost-effectiveness of energy storage. A two-step approach is developed to analyze the effectiveness of using energy storage to provide ancillary services. Results show that as renewable penetrations increase, energy storage can effectively compensate for the variability and uncertainty in renewable energy and has increasing benefits to the system.

With increased renewable penetrations, enhanced dispatch models are needed to efficiently operate energy storage. As existing approaches do not fully utilize the flexibility of energy storage, two approaches are developed in this dissertation to improve the operational strategy of energy storage. The first approach is developed using stochastic programming techniques. A stochastic unit commitment (UC) is solved to obtain schedules for energy storage with different renewable scenarios. Operating policies are then constructed using the solutions from the stochastic UC to efficiently operate energy storage across multiple time periods. The second approach is a policy function approach. By incorporating an offline analysis stage prior to the actual operating stage, the patterns between the system operating conditions and the optimal actions for energy storage are identified using a data mining model. The obtained data mining model is then used in real-time to provide enhancement to a deterministic economic dispatch model and improve the utilization of energy storage. Results show that the policy function approach outperforms a traditional approach where a schedule determined and fixed at a prior look-ahead stage is used. The policy function approach is also shown to have minimal added computational difficulty to the real-time market.
ContributorsLi, Nan (Author) / Hedman, Kory W (Thesis advisor) / Tylavksy, Daniel J (Committee member) / Heydt, Gerald T (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2016
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Description
The safety issue in an electrical power distribution system is of critical importance. In some circumstances, even the continuity of service has to be compromised for a situation that can cause a hazard to the public. A downed conductor that creates an electrical path between a current carrying conductor and

The safety issue in an electrical power distribution system is of critical importance. In some circumstances, even the continuity of service has to be compromised for a situation that can cause a hazard to the public. A downed conductor that creates an electrical path between a current carrying conductor and ground pose a potential lethal hazard to anyone in the near proximity. Electric utilities have yet to find a fully accepted and reliable method for detecting downed conductors even with decades of research.

With the entry of more automation and a smarter grid in the different layers of distribution power system supply, new doors are being opened and new feasible solutions are waiting to be explored. The 'big data' and the infrastructures that are readily accessible through the smart metering system is the base of the work and analysis performed in this thesis. In effect, the new technologies and new solutions are an artifact of the Smart Grid effort which has now reached worldwide dimensions. A solution to problems of overhead distribution conductor failures / faults that use simple methods and that are easy to implement using existing and future distribution management systems is presented.

A European type distribution system using three phase supply is utilized as the test bed for the concepts presented. Fault analysis is performed on the primary and the secondary distribution system using the free downloadable software OpenDSS. The outcome is a set of rules that can be implemented either locally or central using a voltage based method. Utilized in the distribution management systems the operators will be given a powerful tool to make the correct action when a situation occurs. The test bed itself is taken from an actual system in Norway.
ContributorsAbusdal, Geir Magne (Author) / Heydt, Gerald T (Thesis advisor) / Ayyanar, Raja (Committee member) / Heydt, George (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The objective of this thesis is to detect certain cyber attacks in a power distribution ener-gy management system in a Smart Grid infrastructure. In the Smart Grid, signals are sent be-tween the distribution operator and the customer on a real-time basis. Signals are used for auto-mated energy management, protection and

The objective of this thesis is to detect certain cyber attacks in a power distribution ener-gy management system in a Smart Grid infrastructure. In the Smart Grid, signals are sent be-tween the distribution operator and the customer on a real-time basis. Signals are used for auto-mated energy management, protection and energy metering. This thesis aims at making use of various signals in the system to detect cyber attacks. The focus of the thesis is on a cyber attack that changes the parameters of the energy management system. The attacks considered change the set points, thresholds for energy management decisions, signal multipliers, and other digitally stored parameters that ultimately determine the transfer functions of the components. Since the distribution energy management system is assumed to be in a Smart Grid infrastructure, customer demand is elastic to the price of energy. The energy pricing is represented by a distribution loca-tional marginal price. A closed loop control system is utilized as representative of the energy management system. Each element of the system is represented by a linear transfer function. Studies are done via simulations and these simulations are performed in Matlab SimuLink. The analytical calculations are done using Matlab.

Signals from the system are used to obtain the frequency response of the component transfer functions. The magnitude and phase angle of the transfer functions are obtained using the fast Fourier transform. The transfer function phase angles of base cases (no attack) are stored and are compared with the phase angles calculated at regular time intervals. If the difference in the phase characteristics is greater than a set threshold, an alarm is issued indicating the detection of a cyber attack.

The developed algorithm is designed for use in the envisioned Future Renewable Electric Energy Delivery and Management (FREEDM) system. Examples are shown for the noise free and noisy cases.
ContributorsRavi, Vaithinathan (Author) / Heydt, Gerald T (Thesis advisor) / Karady, George G. (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2014