Zhaoyu Wang

Presentations:

Big Data Analytics in Distribution Grids: Conservation Voltage Reduction Assessment, Data-Driven Resilience Quantification, and Model-Free Hosting Capacity Analysis

Recent years have seen a dramatic growth of smart sensors in power distribution grids. The new sensing capabilities, offered by smart meters, micro-phasor measurement units, and SCADA, have extended utilities’ visibility to grid edges. However, the power industry faces new challenges in managing the massive amount of data and extracting useful and actionable information from the measurements. This talk will present a few use cases of distribution grid data. The first one is using SCADA data for measurement and verification (M&V) of the energy saving effect of conservation voltage reduction (CVR). The work is based on a recently published IEEE Standard P3102 CVR Data Collection and Management Procedures. The second one is using various outage records to quantify grid resilience and provide metrics to guide planning and operation. The third one is using smart meter data to develop a model-free framework for dynamic solar hosting capacity analysis.

Blackstart Power Distribution Grids using Distributed Energy Resources and Dynamically Formed Microgrids

Extreme weather events may lead to prolonged outages in distribution systems, highlighting the need for innovative blackstart and restoration approaches. The increasing penetration of distributed energy resources (DERs) provides an opportunity to blackstart distribution systems without relying on transmission systems, thus, significantly accelerating load restoration and boosting grid resilience. This talk will present a holistic bottom-up blackstart and load restoration framework leveraging battery energy storage-based grid-forming inverters (GFMIs) and solar energy-based grid-following inverters (GFLIs). The proposed framework initiates blackstart with multiple GFMIs to form microgrids, sequentially expands the boundaries of islanded microgrids while establishing cranking paths to GFLIs, synchronizes microgrids to form larger islands, and finally synchronizes the distribution system with the transmission grid to complete the restoration process. The proposed framework is validated using the IEEE-123-bus system, with different numbers of GFMIs and under various transmission grid recovery times. Additionally, this talk will briefly introduce our project to convert the City of Montezuma to be Iowa’s first renewable microgrid with blackstart and self-healing capabilities.

Distribution Grid Modeling using Smart Meter Data

Missing or incorrect network models pose a significant challenge in distribution system planning and operation with high penetration of renewables. Although distribution grid modeling has been studied by many researchers using high-resolution and synchronized phasor data, the required high-quality sensors are costly and may not be available in practice. The increasing deployment of smart meters extends monitoring capability to grid edges and provides unprecedented amounts of data. However, most utilities use smart meters for billing purposes only without exploring insights or gaining actionable information from them because these data are limited to low-resolution power and voltage magnitude measurements. This talk will introduce robust, data-driven optimization methods that enable using only smart meter measurements for real-time identification of topology and line parameters with minimum prior information. For topology identification, the new method is to design a Laplacian-like matrix that can capture the physical network feature and leverage its inherent sparse structure to discover nodal connectivity even from low-quality smart meter data. For online parameter identification, the talk will introduce a bottom-up optimization algorithm that uses only smart meter data and conductor types in the network.

Power System Resilience: Fundamentals, Analytical and Planning Tools, and Industry Practices

Recent extreme weather events have highlighted the importance and urgency of enhancing power grid resilience. Although resilience is generally recognized as the capability to anticipate, absorb, adapt to, and rapidly recover from disruptive events, there is not much consensus on the precise definition and quantitative measures for resilience. This tutorial attempts to offer audience the fundamentals and some key ingredients in grid resilience by bringing perspectives from academia, research labs, industry, and governmental agencies. In this four-hour tutorial, we hope to help our audience take the first crack at answering the following questions: What does grid resilience mean exactly? What are the metrics to evaluate resilience? What are the resilience enhancement strategies and how optimization and data analytics can help? and what are industry practices and policies and initiatives from governmental agencies? This tutorial will prepare audience with basic concepts such as probabilistic and optimization modeling and simulation. Commonly used tools for resilience analysis and planning will be introduced. Industry practice and activities will be employed to materialize concepts and strategies for resilience enhancement.