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At least 199 records · Page 11

Survey and Gap Prioritization of U.S. Electric Vehicle Charge Management Deployments

The goal of this study was to survey and characterize the scope of current technical and programmatic knowledge pertaining to EV charge management technologies and practices in the US and relevant international jurisdictions. This characterization of existing field demonstrations and knowledge derived were used to determine gaps in the SCM demonstration landscape. Addressing these gaps through research and demonstration could increase confidence in the U.S. that load management and EV charge control could achieve overarching societal benefits. A survey of charge management deployments and input from stakeholders was completed to determine the state-of-the-art of smart charge management (SCM) where SCM is defined as controlling the amount of power exchanged between chargers and EVs to meet customers' charging needs while also responding to external power demand or pricing signals to provide load management, resilience, or other benefits to the customer and electric grid. The survey was the basis of the gap analysis in this report and determines which areas are well understood, with high confidence, and which areas need further investigation. Existing examples of EV charge management are characterized here to determine aspects that are ready for widespread deployment and have been demonstrated in the field. These include demonstration studies, pilots, programs, and EV-specific tariffs. In all, 110 examples of charge management were characterized. The data sources were public literature and utility filings as well as targeted interviews. In addition, 43 interviews with stakeholders were conducted with a consistent set of questions used in each interview. This study prioritized gaps in demonstrated SCM capabilities based on 1) Urgency of the particular use-case to offset traditional grid assets, 2) Impact, extensibility, and scaling of results across the entire spectrum of 3000+ utility service territories including projected technical and market potential for a given grid service, and 3) Value of federal funding in addressing the gap, including potential to leverage and/or add scope to existing field demonstrations funded by other non-federal funding mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

Connected Thermostat Alternatives for Room Air Conditioners and Minisplit Heat Pumps

The availability of smart, connected thermostats has improved climate control, energy efficiency, and grid demand-response programs for central HVAC systems. However, a significant gap exists in addressing integrated control systems for point-source heating and cooling systems such as window air-conditioners (window ACs) and mini-split heat pumps (MSHPs). This report examines the emerging market of third-party connected thermostats tailored for these systems, focusing on their effectiveness, reliability, and potential barriers to adoption.This study evaluates several commercially available products designed for room ACs and MSHPs through a series of laboratory tests. While these infrared-based (IR-based) thermostats offer remote temperature control and scheduling via mobile apps, our findings reveal that none are seamless, with reliability of basic functions being a critical factor. Promising features include integration of indoor air quality metrics and time-of-use pricing, but the latter are not yet available in the U.S. Barriers to broad user acceptance include non-seamless setup processes, challenges in thermostat placement, and unclear product differentiation. There is a pressing need for research and development in enabling MSHPs and central thermostats to coordinate, enhancing energy savings and comfort in retrofit applications. This study underscores the importance of further innovation in connected thermostat technology to address the diverse needs of single-zone HVAC systems and promote efficient energy management in households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Real-Time Testbed for Smart Grid Recloser Controller

The growing need for a low voltage recloser has become apparent due to the rise in requirements for a smart grid. This includes more detailed management of power flow forward (towards load) and backward (towards generation), source synchronization in real time, more indepth fault responses, and the use of green energy. The SEL-651R-2 relay is a device that can manage these needs, especially in fault response and synchronization, and is commonly used in systems called microgrids. Microgrids are distribution level systems that are able to operate separated from the main grid, are typically installed much closer to the load(s), and are fed by distributed energy resources (DERs), such as wind, solar or diesel generators. The SEL-651R-2 is normally used in the field with presets operative settings, but the Western Michigan University (WMU) Center for Interdisciplinary Research on Secure, Efficient and Sustainable Energy Technology (WMU InterEnergy Center) wished to test this device in its range of capabilities for microgrid application. A Hardware-In-the-Loop (HIL) testbed was implemented and used through the Real Time Digital Simulator (RTDS) using the RSCAD software to test the SEL-651R-2's use cases and functions. The testbed includes a microgrid with interconnection to a larger main grid, and the relay is meant to control the recloser at the point of common coupling (PCC) between the main grid and microgrid. The testbed shows how basic protections, reclosing, and synchronization checks function when handling faults that affect both the microgrid and the main grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗

Electrical Fault and Power Quality Detection Algorithms and Customer-Owned DERs Monitoring with a Cyber Grid Guard System and DLT

In this study, the electrical fault and power quality detection algorithms and customer-owned DERs monitoring use cases were implemented, with a Cyber Grid Guard system and DLT. Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substations, and are associated with customer-owned distributed energy resources (DERs). Data from these IEDs, such as power meters and protection relays, must be kept confidential and of high integrity. Blockchain technology has the potential to increase microgrid resilience by enhancing data sharing security. The growing use of IEDs and customer-owned renewable energy sources (DERs) may make it necessary to connect Distributed Ledger Technology (DLT) with power system applications. We implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in the loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results showed the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, power system applications for the ESGT with DERs and the CGG system will be based on executing smart contracts between electrical utilities and customer-owned DERs.

Piesciorovsky, Emilio↗

Natural Gas Community of the Future (Final Report)

Nicor Gas, a subsidiary of Southern Company Gas and its parent company Southern Company, is developing the concept of the Carbon-neutral, Affordable, Resilient, and Equitable Community ("CARE Community") to address the challenges of accessibility and affordability of grid-interactive efficient buildings in historically disadvantaged communities. The CARE Community is a new construction net-zero energy and carbon neutral residential neighborhood consisting of 50 homes with electricity and natural gas services in South Suburban Chicago, built as low-income affordable housing. The National Renewable Energy Laboratory (NREL) is assisting Southern Company to explore how energy efficiency, renewable technologies, and the reliability and resilience of natural gas can be combined and optimized in an islandable energy system as part of a broader effort to understand the role natural gas plays in future communities integrated with renewable energy and improved energy efficiency. The CARE Community will demonstrate how energy efficiency, distributed energy resources (DERs), and advanced controls can be combined with existing natural gas infrastructure to serve historically disadvantaged communities in a cold climate with low energy cost for affordable housing programs and enhanced resilience to withstand extreme weather. Homes will be a part of an islandable energy system, integrating multiple DER technologies such as solar panels, natural gas fuel cells, reciprocating natural gas engines, and battery storage. The CARE Community will provide a replicable template that affordable housing developers and energy companies can adopt throughout the United States. In this report, we present the design and modeling of the community and potential approaches for integrating DERs. We analyze and discuss annual simulations under normal operating conditions and week-long simulations under electric power grid outage conditions.

03 NATURAL GAS↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Assessment of the Distributed Ledger Technology for Energy Sector Industrial and Operational Applications Using the MITRE ATT&CK® ICS Matrix

In recent times, Distributed Ledger Technology (DLT) has gained significant attention for its potential application in the energy sector. Utilizing blockchain and DLT has demonstrated the ability to enhance the resilience of the electric infrastructure, which will support a more flexible infrastructure and advance grid modernization. However, the deployment of these technologies increases the overall attack surface. The MITRE ATT&CK® matrices have been developed to document an adversary’s tactics and techniques based on real-world observations. The MITRE ATT&CK® matrices provide a common taxonomy for offense and defense and have become a valuable conceptual tool across multiple cybersecurity disciplines for conveying threat intelligence, performing testing through red teaming or adversary emulation, and enhancing network and system defenses against intrusions. The MITRE ATT&CK® for Industrial Control Systems (ICS) matrix was created to provide knowledge about adversary behavior in the ICS technology domain. This study analyzes the relevance of various tactics and techniques across a seven-layer DLT engineering and cybersecurity stack, known as the DLT stack, designed by the Cybersecurity Taskforce under IEEE P2418.5 - Standard for Blockchain in Energy working group sponsored by Power and Energy Systems - Smart Buildings, Loads and Customer Systems (PES/SBLC) Technical Committee. Additionally, this paper identifies specific mitigation strategies tailored to the energy ICS environment

42 ENGINEERING↗

A Commercial Building Plug Load Management System that Uses Internet of Things Technology to Automatically Identify Plugged-In Devices and Their Locations

Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC's dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS's primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Valuing Resilience Benefits of Microgrids for an Interconnected Island Distribution System

Extreme climate-driven events such as hurricanes, floods, and wildfires are becoming more intense in areas exposed to these threats, requiring approaches to improve the resilience of the electrical infrastructure serving these communities. Long-duration outages caused by such high impact events propagate to economic, health, and social consequences for communities. As essential service providers, electric utilities are mandated to provide safe, economical and reliable electricity to their customers. The public is becoming less tolerant to these more frequent disruptions, especially in view of technological advances that are intended to improve power quality, reliability and resilience. One promising solution is state-of-the-art microgrids and the advanced controls employed therein. This paper presents and demonstrates an approach to technoeconomic analysis that can be used to value the avoided economic consequences of grid resilience investments, as applied to the islands of Vieques and Culebra in Puerto Rico. This valuation methodology can support policies to incorporate resilience value into any investment decision-making process, especially those which serve the public interest.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Incorporating Residential Smart Electric Vehicle Charging in Home Energy Management Systems: Preprint

Electric vehicles are expected to drastically increase residential electricity consumption and provide a significant source of flexible demand. Aggregating smart EV charge controllers with other smart home devices through a home energy management system can lead to more optimal outcomes that benefit homeowners, utilities, and grid operators. Control strategies must account for occupant convenience by considering the need for fully charged EVs at any time of day. In this paper, we develop an EV charging framework that accounts for occupant convenience using OCHRE, a residential energy model, and foresee, a home energy management system. We simulate a community with high EV penetration and show that integrated, smart EV charging reduces peak demand and smooths night-time energy consumption. Simulation results show that the proposed control strategy nearly eliminates peak period EV charging and reduces the daily peak demand from EVs by 23%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Incorporating Residential Smart Electric Vehicle Charging in Home Energy Management Systems

Electric vehicles (EVs) are expected to drastically increase residential electricity consumption and could provide a significant source of flexible demand. Aggregating smart EV charge controllers with other smart home devices through a home energy management system can lead to more optimal outcomes that benefit homeowners, utilities, and grid operators. Control strategies should consider occupant convenience by accounting for the need for fully charged EVs near the EV departure time. In this paper, we develop an EV charging framework that accounts for occupant convenience using OCHRE, a residential energy model, and foresee, a home energy management system. We simulate a community with high EV penetration and show that integrated, smart EV charging reduces peak demand and smooths night-time energy consumption. Simulation results show that the proposed control strategy nearly eliminates peak period EV charging and reduces the daily peak demand from EVs by 23%.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Centralized and Decentralized Distributed Energy Resource Access Control Implementation Considerations.

A global transition to power grids with high penetrations of renewable energy generation is being driven in part by rapid installations of distributed energy resources (DER). New DER equipment includes standardized IEEE 1547-2018 communication interfaces and proprietary communications capabilities. Interoperable DER provides new monitoring and control capabilities. The existence of multiple entities with different roles and responsibilities within the DER ecosystem makes the Access Control (AC) mechanism necessary. In this paper, we introduce and compare two novel architectures, which provide a Role-Based Access Control (RBAC) service to the DER ecosystem’s entities. Selecting an appropriate RBAC technology is important for the RBAC administrator and users who request DER access authorization. The first architecture is centralized, based on the OpenLDAP, an open source implementation of the Lightweight Directory Access Protocol (LDAP). The second approach is decentralized, based on a private Ethereum blockchain test network, where the RBAC model is stored and efficiently retrieved via the utilization of a single Smart Contract. We have implemented two end-to-end Proofs-of-Concept (PoC), respectively, to offer the RBAC service to the DER entities as web applications. Finally, an evaluation of the two approaches is presented, highlighting the key speed, cost, usability, and security features.

42 ENGINEERING↗

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advancing Federal Infrastructure Through Innovation: Selecting Electric Vehicle Charging Infrastructure Wisely

The Biden Administration's issuance of Executive Orders directly addressing and accelerating Federal fleet electrification places an onus on both fleet and facility managers. This panel will help fleet and facility personnel understand how to select EVSE infrastructure in terms of implementation, energy management, and costs of procurement, installation/deployment, and electricity. The panel will cover technology aspects to include managed EVSE, bi-directional charging, implications on local electrical systems and storage needs in certain cases to buffer power demand. Discussion will include various considerations relevant to ensuring adequate EVSE, balancing infrastructure needs, and upgrades with fleet needs. The panelists will discuss how to provide sufficient infrastructure support, including which stakeholders to involve, procurement impediments, easement locations, and requirements that arise during the design and implementation process.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗

DLR Calculation Engine Interoperability Profile: A Project for the TOGETs Task Force

This document contains a detailed interoperability profile outlining how the components of the CIM can be used to implement DLR in support of the two use cases identified in the Use Case Document. An interoperability profile is defined by the Smart Electric Power Alliance (SEPA) as a document that “specifies standards-based requirements for interfaces or applications that are accepted by the user-community, testing authorities, and other stakeholders. It specifies configuration options within a standard’s requirements sufficient to deliver the desired level of interoperability and functionality.” To that end, this document is not in itself a standard, nor has it been approved by any formal body. Rather, it is an example of how to implement the CIM standard and has been reviewed by industry, including transmission operators and DLR vendors.

24 POWER TRANSMISSION AND DISTRIBUTION↗