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Emmanuel, Michael

Publications and source records attributed to Emmanuel, Michael.

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗

Enhancing grid reliability and resilience through novel DER control, total situational awareness and integrated distribution-transmission representation

High penetration of distributed energy resources (DERs) can lead to overvoltage and thermal violations, miscoordination of protection devices and potential adverse control interactions. The challenges are exacerbated by a lack of operator situational awareness of behind-the-meter DERs, and T&D interactions. Furthermore, the large attack surface of a DER environment creates significant cyber security challenges. The motivation is to address these barriers. The main goal is to enable extreme levels of DERs in distribution systems while simultaneously enhancing their reliability and resiliency. This is achieved by a data-driven approach for operation, planning and control of distribution systems with total situational awareness and real-time DER control enabled by a network of edge intelligent devices, a cloud-based analytical platform, and secure communications.

14 SOLAR ENERGY↗

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning: Preprint

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Duke Energy Carbon-Free Resource Integration Study

Duke Energy has partnered with the National Renewable Energy Laboratory (NREL) to evaluate pathways to achieving their carbon-free targets and to assess the operational impacts of the resulting system. This report details findings from Phase II of the Duke Low Carbon Resource Integration study, which consisted of three separate but interrelated analyses: (1) a resource assessment exploring the technical and economic potential and characteristics of wind and solar resources in the Carolinas; (2) capacity expansion modeling identifying the least-cost investment pathways for achieving 70% CO 2 emissions reductions in North Carolina by 2030 and a net-zero electricity system by 2050; and (3) detailed production cost modeling of power system operations at the higher shares of low- and zero-carbon emitting generation sources, informed by the capacity expansion modeling portion of the analysis. The analysis finds that Duke Energy can approach the 2030 and 2050 emissions target in North Carolina through investment in a combination of solar, wind, and storage along with maintaining its existing nuclear fleet. The average cost of CO 2 abatement in the Carolinas through 2021-2050 is on the order of $\$27-33$ per metric ton (range of $\$9-34$ per metric ton across key sensitivities).Duke Energy can expected increased interchange with neighbors to help balance higher levels of solar, although the ability to do this will depend on whether neighboring regions also move to integrate more carbon-free resources. As Duke Energy moves toward both the 2030 and 2050 targets, addressing energy needs during the winter peak period becomes particularly important, and the system relies on the availability of resources such as renewable or hydrogen combustion turbines, seasonal storage, or other similar technologies that are dispatchable but able to operate at low capacity factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Grid Optimization with Solar (GO-Solar)

This presentation discusses the goal to accelerate industry adoption of ADMS to improve normal operations with high DERs and improve resilience and reliability.

GO-Solar↗

Distribution System Research Roadmap; Energy Efficiency and Renewable Energy

The scope of the U.S. Department of Energy's Energy Efficiency and Renewable Energy (EERE) office covers a number of distributed energy resource (DER) technologies, including distributed photovoltaics, smart buildings, wind, water, behind-the-meter-storage, and electric vehicles. The impact of these technologies on the distribution system is often assessed with an individual technology focus. Similarly, different technology offices often leverage different sets of tools, leading to analyses that are not comparable. EERE sought the ability to assess the impact of integrating multiple DER technologies, and to comprehensively address DER integration challenges across the portfolio of EERE technologies. This project built on existing work understanding technical challenges, mapped out the key research questions, assessed relevant capabilities across the national laboratory network, identified key gaps, and produced a research roadmap to inform EERE investment decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Estimating Spatial Distribution Impacts of Rooftops Solar PV on Dynamic Hosting Capacity Evaluation for a Real Distribution Feeder

This paper models the sensitivity of dynamic hosting capacity analysis to the spatial distribution of distributed PV scenarios, random, close and far from substation deployments, at various penetration levels on a real distribution feeder, in a quasi-static time series (QSTS) power flow simulation using high resolution time-aware metrics. These spatial distribution scenarios were chosen to capture a wide range of potential operation impacts of these deployments using a set of thermaland voltage-based metrics such as instantaneous violations and moving averages for both thermal and voltage constraints. This study uses actual load and PV data up-scaled from 1-hour time step to 1-minute resolution to fully characterize the interaction between the daily changes in load and PV output, and their impacts on distribution system operations.

distribution system↗