Hardware-in-the-loop Testing of Direct Transfer Trip for Network Protector Units in the Presence of Distributed Energy Resources
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Joshi, Milan↗
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Techno-Economic Assessment of Data Center Load Demand Powered by Small Modular Reactors and Distributed Energy Resources
The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.
14 - SOLAR ENERGY↗
Robust Dynamic Watermarking for Cyber-Physical Security of Inverter-Based Resources in Power Distribution Systems
Not provided.
Automation & Control Systems↗
Valuation of Distributed Wind in an Isolated System
Remote communities are increasingly adopting renewable energy, such as wind, as they transition away from diesel energy generation. It is important to understand the benefits and costs of wind energy to isolated systems so that decision-makers can optimize their choices in these communities. There are few examples of valuation of wind energy as a distributed resource and numerous differences in valuation approaches, especially in the inclusion of environmental and economic impacts. We apply a distributed wind valuation framework to calculate the benefits and costs of wind in St. Mary’s, Alaska, to the local electric cooperative and to society, finding that the project does not have a favorable benefit-to-cost ratio unless societal benefits are included, in which case the benefit-to-cost ratio is nearly double. Government funding is important to reducing the initial capital expenditures of this wind project and will likely be the case for projects with similar characteristics. Additional fuel savings benefits are potentially possible for this project through technological additions such as energy storage and advanced controls.
17 WIND ENERGY↗
Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks
With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility
In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.
advanced metering infrastructure↗
Distributed Optimization in Distribution Systems: Use Cases, Limitations, and Research Needs
We report electric distribution grid operations typically rely on both centralized optimization and local non-optimal control techniques. As an alternative, distribution system operational practices can consider distributed optimization techniques that leverage communications among various neighboring agents to achieve optimal operation. With the rapidly increasing integration of distributed energy resources (DERs), distributed optimization algorithms are growing in importance due to their potential advantages in scalability, flexibility, privacy, and robustness relative to centralized optimization. Implementation of distributed optimization offers multiple challenges and also opportunities. This paper provides a comprehensive review of the recent advancements in distributed optimization for electric distribution systems and classifications using key attributes. Problem formulations and distributed optimization algorithms are provided for example use cases, including volt/var control, market clearing process, loss minimization, and conservation voltage reduction. Finally, this paper also presents future research needs for the applicability of distributed optimization algorithms in the distribution system.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Cybersecurity Methods for Grid-Connected Power Electronics
The present work shows a secure-by-design process, defense-in-depth method, and security techniques for a secure distributed energy resource. The distributed energy resource is a cybersecure, solar inverter and battery energy storage system prototype, collectively called the Cybersecure Power Router. Consideration is given to the use of the Smart Green Power Node for a foundation of the present work. Metrics for controller security are investigated to evaluate firmware security techniques. The prototype's ability to mitigate, respond to, and recover from firmware integrity degradation is examined. The prototype shows many working security techniques within the context of a grid-connected, distributed energy resource. Further work is expected in the Cybersecure Power Router project. Consideration is also provided for the migration of the present research and the Smart Green Power Node to realize a pre-production prototype.
Moquin, Stephen Joe↗
A mission planning concept and mission planning system for future manned space missions
The international character of future manned space missions will compel the involvement of several international space agencies in mission planning tasks. Additionally, the community of users requires a higher degree of freedom for experiment planning. Both of these problems can be solved by a decentralized mission planning concept using the so-called 'envelope method,' by which resources are allocated to users by distributing resource profiles ('envelopes') which define resource availabilities at specified times. The users are essentially free to plan their activities independently of each other, provided that they stay within their envelopes. The new developments were aimed at refining the existing vague envelope concept into a practical method for decentralized planning. Selected critical functions were exercised by planning an example, founded on experience acquired by the MSCC during the Spacelab missions D-1 and D-2. The main activity regarding future mission planning tasks was to improve the existing MSCC mission planning system, using new techniques. An electronic interface was developed to collect all formalized user inputs more effectively, along with an 'envelope generator' for generation and manipulation of the resource envelopes. The existing scheduler and its data base were successfully replaced by an artificial intelligence scheduler. This scheduler is not only capable of handling resource envelopes, but also uses a new technology based on neuronal networks. Therefore, it is very well suited to solve the future scheduling problems more efficiently. This prototype mission planning system was used to gain new practical experience with decentralized mission planning, using the envelope method. In future steps, software tools will be optimized, and all data management planning activities will be embedded into the scheduler.
Wickler, Martin↗
Resource Management for Distributed Parallel Systems
Multiprocessor systems should exist in the the larger context of distributed systems, allowing multiprocessor resources to be shared by those that need them. Unfortunately, typical multiprocessor resource management techniques do not scale to large networks. The Prospero Resource Manager (PRM) is a scalable resource allocation system that supports the allocation of processing resources in large networks and multiprocessor systems. To manage resources in such distributed parallel systems, PRM employs three types of managers: system managers, job managers, and node managers. There exist multiple independent instances of each type of manager, reducing bottlenecks. The complexity of each manager is further reduced because each is designed to utilize information at an appropriate level of abstraction.
Neuman, B. Clifford↗
Integrating System to Edge-of-Network Architecture and Management for SHINES (SEAMS) Technologies of High Penetration Grids
Consistent with the U.S. DOE’s EERE SHINES FOA objectives, the goal of this project was to enable integration from EMS to variable DER in a way that delivered visibility and opportunities for managing and controlling distributed resources using SEAMS technologies. This project implemented several SHINES technologies, which included: (1) three Stem battery systems; (2) six ConnectDER PV collars; (3) two E-Gear PV/Battery storage interfaces; and (4) eight Kitu smart inverter emulators. A Siemens Energy IP DEMS was deployed in a development environment and integrated with the SHINES technologies via OpenADR and IEEE 2030.5 protocols with documented architecture. In the case of IEEE 2030.5, a suite of technologies including a gateway, an API, software and a server from Kitu Systems (the Citadel, Convoy, Kitu Crosslink API, and Kitu Spark) were used to demonstrate that the utility could achieve visibility of distributed energy resources (DER) and control of single and multiple DER systems with a single command. The project also included a LCOE analysis of SHINES technologies compared to traditional system and circuit mitigation measures.
14 SOLAR ENERGY↗
Application of DLT cybersecurity stack to TES applications for a scalable, cybersecure, and interoperable future
Transactive Energy Systems (TES) are expected to improve upon existing grid operations and capabilities by enabling the integration of traditional grid resources with distributed energy resources (DER). Distributed Ledger Technology or DLT (e.g., blockchain) presents itself as a viable instrument to support decentralized, autonomous, and tamper-evident applications, which can be leveraged within TES's ecosystem. DLTs can provide pertinent security controls including access controls, data immutability, and traceability in addition to other well-known advantages such as decentralization and scalability. This work demonstrates the DLT Cybersecurity stack and its applicability to TES-based use-cases/applications. The seven-layer DLT cybersecurity stack is a DLT-agnostic framework that can quickly be used to classify and group the individual needs of an application into the different processing and cybersecurity layers offered by a DLT using a common taxonomy and an architectural mapping framework. This enables application engineers to demystify and strengthen the overall security aspects of their systems while maintaining an open perspective towards features and drawbacks that may hinder their performance in real-world scenarios. The paper leverages the work performed by the IEEE P2418.5 - Blockchain for Energy Standards working group.
Blockchain, blockchain interoperability, Cybersecu↗
An innovative approach for distributed and integrated resources planning for the Space Station Freedom
This paper presents a planning approach to the Space Station Freedom program which takes into account the widely distributed nature of that program. The program management structure is organized into three major levels: a strategic level, a tactical level, and an execution level. For each level, resource availabilities are determined, the resources are distributed, schedules are built independently within the resource limits, the schedules are integrated into a single schedule, and conflicts are resolved by negotiating requirements and/or relaxing contraints. This approach distributes resources to multiple planning entities in such a way that when the multiple plans are collected, they fit together with minimal modification. The up-front distribution is planned in such a way and to a sufficient degree that a fit is virtually assured.
Hornstein, Rhoda S.↗
Optimal dynamic control of resources in a distributed system
The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.
Shin, Kang G.↗
Surfer: An Extensible Pull-Based Framework for Resource Selection and Ranking
Grid computing aims to connect large numbers of geographically and organizationally distributed resources to increase computational power; resource utilization, and resource accessibility. In order to effectively utilize grids, users need to be connected to the best available resources at any given time. As grids are in constant flux, users cannot be expected to keep up with the configuration and status of the grid, thus they must be provided with automatic resource brokering for selecting and ranking resources meeting constraints and preferences they specify. This paper presents a new OGSI-compliant resource selection and ranking framework called Surfer that has been implemented as part of NASA's Information Power Grid (IPG) project. Surfer is highly extensible and may be integrated into any grid environment by adding information providers knowledgeable about that environment.
Zolano, Paul Z.↗
Elastic distributed training with fast convergence and efficient resource utilization
Distributed learning is now routinely conducted on cloud as well as dedicated clusters. Training with elastic resources brings new challenges and design choices. Prior studies focus on runtime performance and assume a static algorithmic behavior. In this work, by analyzing the impact of of resource scaling on convergence, we introduce schedules for synchronous stochastic gradient descent that proactively adapt the number of learners to reduce training time and improve convergence. Our approach no longer assumes a constant number of processors throughout training. In our experiment, distributed stochastic gradient descent with dynamic schedules and reduction momentum achieves better convergence and significant speedups over prior static ones. Numerous distributed training jobs running on cloud may benefit from our approach.
Cong, Guojing↗
Coordinated voltage control and reactive power regulation between transmission and distribution systems
Systems and methods are described for coordinating volt-var control between sub-transmission and distribution systems. Distributed energy resources of a distribution system are aggregated into virtual power plants from which reactive power can optimally be dispatched to the sub-transmission system. A sub-transmission controller executes a volt-var AC optimal power flow optimisation function to minimize voltage fluctuations that might otherwise occur when coordinating with a distribution system having distributed energy resources. The distribution system can use a sensitivity matrix for regulating voltage at distribution feeders while fulfilling a transmission or sub-transmission system's demand requests.
Samaan, Nader A.↗
FERC Order No. 2222 and Considerations for Distributed Wind
The Federal Energy Regulatory Commission (FERC) issued Order No. 2222 in October 2020. The rule directs Regional Transmission Organizations and Independent System Operators (ISOs) to amend their tariffs and participation models to accommodate heterogeneous distributed energy resource (DER) aggregations in the wholesale energy markets that they operate, including capacity, energy, and ancillary service markets. The Commission issued the rule to better capture the benefits provided by DERs deployed in the United States, whose use has been expanding rapidly. The Commission defines DERs as “any resource located on the distribution system, any subsystem thereof or behind a customer meter,” including but not limited to “electric storage resources, distributed generation, demand response, energy efficiency, thermal storage, and electric vehicles and their supply equipment.” The rule aims to increase DER participation in wholesale markets by allowing the creation of DER aggregations, in which multiple DERs that are too small to meet minimum capacity requirements for wholesale markets individually would be able to participate in markets as a single unit. As of June 20, 2023, all ISOs have filed initial compliance plans and a number have begun implementation. Compliance dates range from 2024 to 2029, with Midcontinent ISO having the latest date of compliance proposed for 2029. Southwest Power Pool still has an outstanding date, having no final order yet from FERC, but a target date of the third quarter of calendar year 2025. The rule, which is technology agnostic and requires ISOs to create participation plans that accommodate different DERs, provides an opportunity for distributed wind market expansion. In addition, distributed wind can bring benefits to heterogenous DER aggregations. These benefits include resource diversity (i.e., a complementary generation profile to other types of distributed generation), its small footprint and ability to be co-located with load, and its potential to provide frequency response, voltage support, and black start services, among other ancillary services. This report provides a status update on FERC Order No. 2222, the current state of ISO compliance, and information relevant to the distributed wind industry as DER aggregators and other stakeholders expand their participation to wholesale energy markets.
17 WIND ENERGY↗