Matching Items (4)
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- All Subjects: Distribution Systems
- Genre: Academic theses
- Genre: Masters Thesis
- Creators: Vittal, Vijay
Description
The past few decades have seen a consistent growth of distributed PV sources. Distributed PV, like other DG sources, can be located at or near load centers and provide benefits which traditional generation may lack. However, distribution systems were not designed to accommodate such power generation sources as these sources might lead to operational as well as power quality issues. A high penetration of distributed PV resources may lead to bi-directional power flow resulting in voltage swells, increased losses and overloading of conductors. Voltage unbalance is a concern in distribution systems and the effect of single-phase residential PV systems on voltage unbalance needs to be explored. Furthermore, the islanding of DGs presents a technical hurdle towards the seamless integration of DG sources with the electricity grid. The work done in this thesis explores two important aspects of grid inte-gration of distributed PV generation, namely, the impact on power quality and anti-islanding. A test distribution system, representing a realistic distribution feeder in Arizona is modeled to study both the aforementioned aspects. The im-pact of distributed PV on voltage profile, voltage unbalance and distribution sys-tem primary losses are studied using CYMDIST. Furthermore, a PSCAD model of the inverter with anti-island controls is developed and the efficacy of the anti-islanding techniques is studied. Based on the simulations, generalized conclusions are drawn and the problems/benefits are elucidated.
ContributorsMitra, Parag (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
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 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
Description
This research mainly focuses on improving the utilization of photovoltaic (PV) re-sources in distribution systems by reducing their variability and uncertainty through the integration of distributed energy storage (DES) devices, like batteries, and smart PV in-verters. The adopted theoretical tools include statistical analysis and convex optimization. Operational issues have been widely reported in distribution systems as the penetration of PV resources has increased. Decision-making processes for determining the optimal allo-cation and scheduling of DES, and the optimal placement of smart PV inverters are con-sidered. The alternating current (AC) power flow constraints are used in these optimiza-tion models. The first two optimization problems are formulated as quadratically-constrained quadratic programming (QCQP) problems while the third problem is formu-lated as a mixed-integer QCQP (MIQCQP) problem. In order to obtain a globally opti-mum solution to these non-convex optimization problems, convex relaxation techniques are introduced. Considering that the costs of the DES are still very high, a procedure for DES sizing based on OpenDSS is proposed in this research to avoid over-sizing.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
ContributorsLi, Qifeng (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Mittelmann, Hans D (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
Description
The past few years have witnessed a significant growth of distributed energy resources (DERs) in power systems at the customer level. Such growth challenges the traditional centralized model of conventional synchronous generation, making a transition to a decentralized network with a significant increase of DERs. This decentralized network requires a paradigm change in modeling distribution systems in more detail to maintain the reliability and efficiency while accommodating a high level of DERs. Accurate models of distribution feeders, including the secondary network, loads, and DER components must be developed and validated for system planning and operation and to examine the distribution system performance. In this work, a detailed model of an actual feeder with high penetration of DERs from an electrical utility in Arizona is developed. For the primary circuit, distribution transformers, and cables are modeled. For the secondary circuit, actual conductors to each house, as well as loads and photovoltaic (PV) units at each premise are represented. An automated tool for secondary network topology construction for load feeder topology assignation is developed. The automated tool provides a more accurate feeder topology for power flow calculation purposes. The input data for this tool consists of parcel geographic information system (GIS) delimitation data, and utility secondary feeder topology database. Additionally, a highly automated, novel method to enhance the accuracy of utility distribution feeder models to capture their performance by matching simulation results with corresponding field measurements is presented. The method proposed uses advanced metering infrastructure (AMI) voltage and derived active power measurements at the customer level, data acquisition systems (DAS) measurements at the feeder-head, in conjunction with an AC optimal power flow (ACOPF) to estimate customer active and reactive power consumption over a time horizon, while accounting for unmetered loads. The method proposed estimates both voltage magnitude and angle for each phase at the unbalanced distribution substation. The accuracy of the method developed by comparing the time-series power flow results obtained from the enhancement algorithm with OpenDSS results and with the field measurements available. The proposed approach seamlessly manages the data available from the optimization procedure through the final model verification.
ContributorsMontano-Martinez, Karen Vanessa (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Weng, Yang (Committee member) / Pal, Anamitra (Committee member) / Arizona State University (Publisher)
Created2022