OPTIMAL PLANNING AND OPERATION OF DISTRIBUTION SYSTEMS WITH MASSIVE ELECTRIC VEHICLES

The concern for global warming and the development of battery technology have promoted the adoption of electric vehicles (EVs) in recent years. The increasing penetration of EVs brings both challenges and opportunities to distribution systems. In the planning stage, system operators need to consider where to build public charging stations considering both economic and technology constraints. In the operation stage, system operators can take advantage of the EVs flexibility to mitigate operational issues and participate in markets. Therefore, it is of great importance to improve distribution system planning and operation with the trend of massive EV penetration.The objectives of my research are as follows: (1) to develop tools to generate synthetic distribution test feeders; (2) to develop methods to allocate public charging stations considering hosting capacity; (3) to develop methods solving voltage violations quickly and flexibility; and (4) to develop methods to evaluate the aggregate EVs flexibility.In this dissertation, we outline my contributions to the team effort to develop CP-SyNet, a tool to generate customizable cyber-physical synthetic distribution test feeders. CP-SyNet generates three-phase unbalanced test feeders according to users' requirements, while simultaneously considering both the cyber side and the physical side of the network for more advanced analysis.In the system planning stage, this dissertation proposes a comprehensive planning method for allocating charging stations considering realistic distribution and transportation operations. A new concept of extra load hosting capacity (ELHC) is proposed to evaluate the maximum extra load that the system can absorb without operational violations.In the system operation stage, this dissertation proposes a decentralized voltage control algorithm which considers the coordination of EVs and Photovoltaics (PV) inverters. The approach involves clustering of the distribution network that considers EV flexibility and prediction period and solving voltage problems in each cluster using the proposed model predictive control (MPC)-based algorithm.To evaluate the flexibility of massive EVs, this dissertation proposes a coordinated evaluation method, where distribution system operators (DSO) first evaluate EV aggregators' operational boundaries to exploit distribution level services and transmission system operators (TSO) then determine EV charging schedules and ancillary service capacity simultaneously, considering the requirement from DSO

Low-voltage distribution network reconfiguration considering high penetration of electric vehicles:a UK case study

Network reconfiguration is one of the electricity network optimization techniques for losses reduction and load balancing by changing the open-closed status of sectionalized switches. In this paper, an application of network reconfiguration in low-voltage (LV) domestic distribution network with high penetration of electric vehicles (EVs) is presented. Firstly, high resolution time-series domestic load profiles are generated and validated with measured data at substation. Electric vehicle charging profiles at both fast and slow charging modes are modelled and produced. Then the impact of increasing penetration of EVs on the network thermal and voltage constraints is quantified. To optimize the network topology, suitable locations of newly-installed switches and their operational time are identified by branch-exchange method and exhaustive search algorithm (ESA) due to the small size of network and less potential location. The proposed approach is applied to two practical 400V LV distribution networks interconnected by underground linkboxes which are used to provide back-feeds during routine maintenances or emergency conditions. By adding new sectionalized switches, the LV network will obtain more operational flexibility and could better explore its potential for further study under Smart Grid scenarios

Creating, Validating, and Using Synthetic Power Flow Cases: A Statistical Approach to Power System Analysis

abstract: Synthetic power system test cases offer a wealth of new data for research and development purposes, as well as an avenue through which new kinds of analyses and questions can be examined. This work provides both a methodology for creating and validating synthetic test cases, as well as a few use-cases for how access to synthetic data enables otherwise impossible analysis. First, the question of how synthetic cases may be generated in an automatic manner, and how synthetic samples should be validated to assess whether they are sufficiently ``real'' is considered. Transmission and distribution levels are treated separately, due to the different nature of the two systems. Distribution systems are constructed by sampling distributions observed in a dataset from the Netherlands. For transmission systems, only first-order statistics, such as generator limits or line ratings are sampled statistically. The task of constructing an optimal power flow case from the sample sets is left to an optimization problem built on top of the optimal power flow formulation. Secondly, attention is turned to some examples where synthetic models are used to inform analysis and modeling tasks. Co-simulation of transmission and multiple distribution systems is considered, where distribution feeders are allowed to couple transmission substations. Next, a distribution power flow method is parametrized to better account for losses. Numerical values for the parametrization can be statistically supported thanks to the ability to generate thousands of feeders on command.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification

Detecting faults in electrical power grids is of paramount importance, either from the electricity operator and consumer viewpoints. Modern electric power grids (smart grids) are equipped with smart sensors that allow to gather real-time information regarding the physical status of all the component elements belonging to the whole infrastructure (e.g., cables and related insulation, transformers, breakers and so on). In real-world smart grid systems, usually, additional information that are related to the operational status of the grid itself are collected such as meteorological information. Designing a suitable recognition (discrimination) model of faults in a real-world smart grid system is hence a challenging task. This follows from the heterogeneity of the information that actually determine a typical fault condition. The second point is that, for synthesizing a recognition model, in practice only the conditions of observed faults are usually meaningful. Therefore, a suitable recognition model should be synthesized by making use of the observed fault conditions only. In this paper, we deal with the problem of modeling and recognizing faults in a real-world smart grid system, which supplies the entire city of Rome, Italy. Recognition of faults is addressed by following a combined approach of multiple dissimilarity measures customization and one-class classification techniques. We provide here an in-depth study related to the available data and to the models synthesized by the proposed one-class classifier. We offer also a comprehensive analysis of the fault recognition results by exploiting a fuzzy set based reliability decision rule

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

The Creation, Validation, and Application of Synthetic Power Grids

Public test cases representing large electric power systems at a high level of fidelity and quality are few to non-existent, despite the potential value such cases would have to the power systems research community. Legitimate concern for the security of large, high-voltage power grids has led to tight restrictions on accessing actual critical infrastructure data. To encourage and support innovation, synthetic electric grids are fictional, designed systems that mimic the complexity of actual electric grids but contain no confidential information. Synthetic grid design is driven by the requirement to match wide variety of metrics derived from statistics of actual grids. The creation approach presented here is a four-stage process which mimics actual power system planning. First, substations are geo-located and internally configured from seed public data on generators and population. The substation placement uses a modified hierarchical clustering to match a realistic distribution of load and generation substations, and the same technique is also used to assign nominal voltage levels to the substations. With buses and transformers built, the next stage constructs a network of transmission lines at each nominal voltage level to connect the synthetic substations with a transmission grid. The transmission planning stage uses a heuristic inspired by simulated annealing to balance the objectives associated with both geographic constraints and contingency reliability, using a linearized dc power flow sensitivity. In order to scale these systems to tens of thousands of buses, robust reactive power planning is needed as a third stage, accounting for power flow convergence issues. The iterative algorithm presented here supplements a synthetic transmission network that has been validated by a dc power flow with a realistic set of voltage control devices to meet a specified voltage profile, even with the constraints of difficult power flow convergence for large systems. Validation of the created synthetic grids is crucial to establishing their legitimacy for engineering research. The statistical analysis presented in this dissertation is based on actual grid data obtained from the three major North American interconnects. Metrics are defined and examined for system proportions and structure, element parameters, and complex network graph theory properties. Several example synthetic grids are shown as examples in this dissertation, up to 100,000 buses. These datasets are available online. The final part of this dissertation discusses these specific grid examples and extensions associated with synthetic grids, in applying them to geomagnetic disturbances, visualization, and engineering education

Distribution Network Model Platform: A First Case Study

Decarbonisation policies have recently seen an uncontrolled increase in local electricity production from renewable energy sources (RES) at distribution level. As a consequence, bidirectional power flows might cause high voltage/ medium voltage (HV/MV) transformers to overload. Additionally, not-well-planned installation of electric vehicle (EV) charging stations could provoke voltage deviations and cables overloading during peak times. To ensure secure and reliable distribution network operations, technology integration requires careful analysis which is based on realistic distribution grid models (DGM). Currently, however, only not geo-referenced synthetic grids are available inliterature. This fact unfortunately represents a big limitation. In order to overcome this knowledge gap, we developed a distribution network model (DiNeMo) web-platform aiming at reproducing the DGM of a given area of interest. DiNeMo is based on metrics and indicators collected from 99 unbundled distribution system operators (DSOs) in Europe. In this work we firstly perform a validation exercise on two DGMs of the city of Varaždin in Croatia. To this aim, a set of indicators from the DGMs and from the real networks are compared. The DGMs are later used for a power flow analysis which focuses on voltage fluctuations, line losses, and lines loading considering different levels of EV charging stations penetration