Bryan Palmintier

A Power Hardware-in-the-Loop Platform With Remote Distribution Circuit Cosimulation

This paper demonstrates a novel cosimulation architecture that integrates hardware testing using power hardware-in-the-loop (PHIL) techniques with larger-scale electric grid models using off-the-shelf non-PHIL software tools. This test bed for distributed integration enables utilities to study the impacts of emerging energy technologies on their system and manufacturers to explore the interactions of new devices with existing and emerging devices on the power system, both without the need to convert existing grid models to a new platform or to conduct in-field trials. This paper describes an implementation of this architecture for testing two residential-scale advanced solar inverters at separate points of common coupling (PCCs). The same hardware setup is tested with two different distribution feeders (IEEE 123 and 8500 node test systems) modeled using GridLAB-D. In addition to simplifying testing with multiple feeders, the architecture demonstrates additional flexibility with hardware testing in one location linked via the Internet to software modeling in a remote location. In testing, the inverter current, real and reactive power, and PCC voltage are well captured by the cosimulation platform. Testing of the inverter advanced control features is currently somewhat limited by the software model time step (1 s) and tested communication latency (24 ms). These limitations could be overcome using faster modeling and communication within the same cosimulation architecture.

Flexibility in generation planning: Identifying key operating constraints

This paper utilizes the recent methodology of clustered integer unit commitment (UC) - which tractably captures operational flexibility within generation expansion planning - to explore which operating constraints are the most important for generation investment decisions. Flexibility has been previously shown to alter the optimal generation mix, particularly in scenarios with high flexibility required by significant renewables (>=20%) and/or decreased flexibility of some low-carbon technologies (e.g. traditional nuclear). This work explores the potential to relax some operating constraints to speed-up computation while controlling errors. It is found that operating reserves and maintenance are the most important constraints, while hour-to-hour ramping is least important. However, relaxing integers provides the best accuracy vs. performance trade-offs, but only when the linear program (LP) relaxation includes the full problem with UC constraints. This reduces computation time ~50× with the lowest errors across all metrics: cost (-1%), CO2 (-1%), capacity (-9%), and energy mix (-9%). Considerably high speed ups are possible using the LP relaxed formulation with selected subsets of UC constraints. For cost and CO2, the combination of grouped reserves, ramping, maintenance, and LP provides errors around 2% with ~1500× speedup. However, for capacity and energy mixes, only LP provides reasonable errors (<;25%).

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

This paper describes the integrated grid modeling system (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing platforms to offer unprecedented resolution from independent system operator (ISO) markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed ISO markets and automatic generator control-level reserve deployment. IGMS uses a new message passing interface-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate open-source tools for wholesale markets, bulk ac power flow, and full-featured distribution systems including physics-based end-use and distributed generation models (many instances of GridLAB-D). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar photovoltaic and price responsive load scenarios.

Bus.py: A GridLAB-D communication interface for Smart distribution Grid simulations

As more Smart Grid technologies (e.g., distributed photovoltaic, spatially distributed electric vehicle charging) are integrated into distribution grids, static distribution simulations are no longer sufficient for performing modeling and analysis. GridLAB-D is an agent-based distribution system simulation environment that allows fine-grained end-user models, including geospatial and network topology detail. A problem exists in that, without outside intervention, once the GridLAB-D simulation begins execution, it will run to completion without allowing the real-time interaction of Smart Grid controls, such as home energy management systems and aggregator control. We address this lack of runtime interaction by designing a flexible communication interface, Bus.py (pronounced bus-dot-pie), that uses Python to pass messages between one or more GridLAB-D instances and a Smart Grid simulator. This work describes the design and implementation of Bus.py, discusses its usefulness in terms of some Smart Grid scenarios, and provides an example of an aggregator-based residential demand response system interacting with GridLAB-D through Bus.py. The small scale example demonstrates the validity of the interface and shows that an aggregator using said interface is able to control residential loads in GridLAB-D during runtime to cause a reduction in the peak load on the distribution system in (a) peak reduction and (b) time-of-use pricing cases.

Experiences integrating transmission and distribution simulations for DERs with the Integrated Grid Modeling System (IGMS)

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactive power impacts of PV inverter voltage support on the bulk power system.

Clustering distribution feeders in the Arizona Public Service territory

This paper describes a methodology and approach used to perform clustering on distribution feeders within the service territory of Arizona Public Service (APS). This clustering process was performed in order for APS to characterize the types of feeders in their service territory and to provide a method of feeder classification to inform PV interconnection requirements in the future. The paper begins with a description of the history of clustering techniques for classifying distribution feeders. The method chosen for clustering APS feeders incorporates best practices for the clustering algorithm, stopping criteria, and variable selection. All routines were written in open-source scripting languages. Specific steps in the clustering process are described and applied to the feeders in the APS service territory showing results for each step. The paper concludes with a summary of the work.

Final Technical Report: Integrated Distribution-Transmission Analysis for Very High Penetration Solar PV

Transmission and distribution simulations have historically been conducted separately, echoing their division in grid operations and planning while avoiding inherent computational challenges. Today, however, rapid growth in distributed energy resources (DERs)--including distributed generation from solar photovoltaics (DGPV)--requires understanding the unprecedented interactions between distribution and transmission. To capture these interactions, especially for high-penetration DGPV scenarios, this research project developed a first-of-its-kind, high performance computer (HPC) based, integrated transmission-distribution tool, the Integrated Grid Modeling System (IGMS). The tool was then used in initial explorations of system-wide operational interactions of high-penetration DGPV.

Examining system-wide impacts of solar PV control systems with a power hardware-in-the-loop platform

High penetration levels of distributed solar PV power generation may lead to adverse power quality impacts. Advanced inverter control schemes have the potential to mitigate many power quality concerns. However, interactions between local closed-loop controls may lead to unintended behavior in deployed systems. To study the performance of advanced control schemes in a detailed distribution system environment, a test platform has been developed that integrates Power Hardware-in-the-Loop (PHIL) with concurrent time-series electric distribution system simulation. In the test platform, GridLAB-D, a distribution system simulation tool, runs a detailed simulation of a distribution feeder in real-time mode at the Pacific Northwest National Laboratory (PNNL) and supplies power system parameters at a point of common coupling. At the National Renewable Energy Laboratory (NREL), a hardware inverter interacts with grid and PV simulators emulating an operational distribution system. The platform is described and initial test cases are presented.

Design of the HELIGS high-performance transmission-distribution-communication-market go-simulation framework

This paper describes the design rationale for the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), a new open-source, cyber-physical-energy co-simulation framework for electric power systems. HELICS is designed to support very-large-scale (100,000+ federates) co-simulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross-platform operating system support, the integration of both event-driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step. After describing the requirements, we evaluate existing co-simulation frameworks, including High-Level Architecture (HLA) and Functional Mockup Interface (FMI), and we conclude that none provide the required features. Then we describe the design for the new, layered HELICS architecture.

Advanced inverter functions and communication protocols for distribution management

This paper aims at identifying the advanced features required by distribution management systems (DMS) service providers to bring inverter-connected distributed energy resources into use as an intelligent grid resource. This work explores the standard functions needed in the future DMS for enterprise integration of distributed energy resources (DER). The important DMS functionalities such as DER management in aggregate groups, including the discovery of capabilities, status monitoring, and dispatch of real and reactive power are addressed in this paper. It is intended to provide the industry with a point of reference for DER integration with other utility applications and to provide guidance to research and standards development organizations.