Flexible Connections and Flexibility Services

The high penetration of distributed photovoltaic (PV) causes the rapid and dramatic fluctuation in the net load. As a result, flexible ramping ancillary services (FRAS) are needed to keep supply-demand balance and maintain frequency stability. For the FRAS provided by the distributed energy resources (DERs), utilizing only one type of resources has technical and economic limitations, so it is crucial to explore the DERs portfolio strategy. To this end, firstly, a technical and economic quantitative analysis method of FRAS provided by the portfolio of DERs including the incentive-based demand response (IBDR), right transfer demand response (RTDR), energy storage system (ESS) is proposed based on portfolio theory. Secondly, for different PV output scenarios that have corresponding FRAS demand, a risk-constrained and scenario-based portfolio model for aggregators is proposed using the conditional value at risk (CVaR). Extensive numerical results demonstrate that the proposed portfolio strategy enables DERs to provide FRAS and improves the aggregator’s profit.

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs).In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation(SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

In evolving distribution networks, Distribution Network Operators (DNOs) are turning to Distributed Energy Resource (DER) to acquire network flexibility services to actively manage network needs, reducing and/or deferring the need for traditional reinforcement. NIE Networks have undertaken the FLEX project which seeks to trial a network flexibility market in Northern Ireland. This paper reports the high-level methods employed by GB DNOs to procure and use flexibility, also drawing on relevant learnings from other sources such as flexibility procurement platforms. Using the information compiled, this paper presents pertinent decision points which will feed into a DNOs' business plan to procure flexibility services.

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

Incorporating flexibility options into distribution grid reinforcement planning: A techno-economic framework approach

We consider decentralized scheduling of Distributed Energy Resources (DERs) in a day-ahead market that clears energy and reserves offered by both centralized generators and DERs. Recognizing the difficulty of scheduling transmission network connected generators together with distribution feeder connected DERs that have complex intertemporal preferences and dynamics, we propose a tractable distributed algorithm where DERs self-schedule based on granular Distribution Locational Marginal Prices (DLMPs) derived from LMPs augmented by distribution network costs. For the resulting iterative DER self-scheduling process, we examine the opportunity of DERs to engage in strategic behavior depending on whether DERs do or do not have access to detailed distribution feeder information. Although the proposed distributed algorithm is tractable on detailed real-life network models, we utilize a simplified T&D network model to derive instructive analytical and numerical results on the impact of strategic DER behavior on social welfare loss, and the distribution of costs and benefits to various market participants.

The growth of distributed energy resources (DER) connected at distribution network level and the current legislation concerning the participation of DER to the energy and ancillary services markets, are a huge opportunity to get flexibility services from these resources but at the same time a great challenge from the technical point of view. According to the latest indications from EU Directives, demand response and generation flexibility are encouraged in order to meet network balancing needs, but a new actor is required: the aggregator. This new participant has the duty to aggregate consumption and generation in order to offer flexibility products in the ancillary services market, while ensuring the technical feasibility and assuring revenues for its clients and itself. This work focuses on the structure and the business model of aggregators and discusses the technical implication that such role has on the distribution network.

With the increasing deployment of Distributed Energy Resources (DERs) in the distribution system, DERs presents many challenges for smooth and stable operation of the grid. For the effective management of DERs extensive communication between different components of DER and distribution system is required. To standardize the communication methods and modeling of logical nodes required for Intelligent Electronic Devices (IEDs) in DERs, data modeling of DERs is issued in IEC 61850-7-420 standard. This paper has contributed communication modeling of Green Energy Resources (GERs) and other DERs, modeling of messages exchanged among different IEDs with regard to their optimum structure & size and a Substation Communication Network (SCN) topology. End to End (ETE) time delay performance of the designed communication configuration architecture is presented using OPtimized Network Engineering Tool (OPNET). The dynamic performance result in the SCN has demonstrated the successful communication configuration for integrating the DERs in distribution system.

Designing pricing strategies for coordination of networked distributed energy resources

Problem definition: The rapid expansion of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Examples of DERs include solar panels, electric storage, thermal storage, and combined heat and power plants. Because of the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper the question of how to integrate these DER supplies into the electricity market, with the objective of achieving full market efficiency. Methodology/results: We study four aggregation models, where there is an aggregator who, with the knowledge of DERs’ utility functions and generations, procures electricity from DERs, and sells them in the wholesale market. In the first aggregation model, a profit-maximizing aggregator announces a differential two-part pricing policy to the DER owners. We show that this model preserves full market efficiency, that is, the social welfare achieved by this model is the same as that when DERs participate directly in the wholesale market. In the second aggregation model, the profit-seeking aggregator is forced to impose a uniform two-part pricing policy to prosumers from the same location, and we numerically show that there can be large efficiency loss. In the third (fourth) aggregation model, a uniform (semiuniform) two-part pricing policy is applied to DER owners, whereas the aggregator becomes fully regulated but is guaranteed nonnegative (positive) profit. It is shown that these models again achieve full market efficiency. Furthermore, we show that DER aggregation also leads to a reduction in the market power of conventional generators. Managerial implications: DER aggregation via profit-seeking and/or regulated aggregators has been investigated by California Independent System Operator and New York Independent System Operator, among others, and the recent Federal Energy Regulatory Commission Order No. 2222 paved the way for aggregators to bid in the wholesale market. Our four aggregation models may shed light on how DERs should be included in the wholesale electricity market. Funding: This work was supported by the King Fahd University of Petroleum and Minerals [Grant INML2106] and the National Science Foundation [Grant 1832230]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2021.0539 .

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

The increasing deployment of distributed energy resources (DERs) and microgrids benefits power grids by improving system resilience. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. In this paper, algorithms are proposed for outage management and feeder restoration for distribution systems with multiple DERs. The Advanced Outage Management (AOM) identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The Advanced Feeder Restoration (AFR) is proposed to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs as well as the feeder configuration. By partitioning the system into islands, critical load will be served with the available generation resources within islands. When the utility systems become available, the optimal path will be determined to reconnect these islands back to substations and restore the remaining load. The proposed method has been validated with modified IEEE 123-Bus and 8500-Node Test Feeders. Simulation results demonstrate the capability of the integrated AOM and AFR to enhance distribution system resilience.

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

A virtual power plant (VPP) facilitates the integration of distributed energy resources (DERs) for transmission-level operations. A challenge in operating a VPP is to characterize the cost function over its feasible power transfer region under DERs' uncertainties. To address this challenge, a characterization method is proposed for the intraday operation of a VPP with nonanticipativity and robustness considerations to DERs' uncertainties. The characterization stems from designing operational requirements subject to nonanticipativity and robustness, by which a feasible power transfer region across all the time periods is constructed by boundary points at each time period and time-coupling constraints. Furthermore, a cost function over the feasible power transfer region is formulated as the combination of convex piecewise surfaces and a constant compensation cost. Finally, a perspective to analyze the impacts of DERs' uncertainties on feasible power transfer regions is studied. Numerical experiments in the IEEE 33-bus and 136-bus systems show that 1) our feasible power transfer region fulfills nonanticipativity and robustness to face DERs' uncertainties, 2) our cost function covers the true operational cost of a VPP, and 3) impacts of DERs' uncertainties on feasible power transfer regions can be measured by the product of their fluctuation intervals and system parameters.

The deployment of Distributed Energy Resources (DERs), small-scale electricity generation sources or controllable loads connected to the distribution system or a facility served by the distribution system, can have wide-ranging and positive impacts for the electricity grid. Interconnecting a DER in a high-value location on the grid can unlock benefits beyond those that accrue to the off-taker or asset owner. When DERs are deployed optimally, not only can the individual consumer benefit, but the local utility, the electricity system, and other ratepayers can benefit as well. By engaging in locational DER planning, states can help protect their communities and ratepayers and can help ensure the reliability and resilience of the electricity system. This report explores states' role in better integrating locational value into DER siting and development. It first outlines some of the benefits that can be achieved through the deployment of DERs in high-value locations. It then looks at state policy and regulatory roles and the tools states can use to influence the location of DER development. The report next examines the challenges of locational DER planning, with a particular focus on the challenges that states face in influencing the location of DER development. It highlights three case studies from states that engaged in locational DER planning through the Multistate Initiative to Develop Solar in Locations that Provide Benefits to the Grid and then presents several lessons learned from these efforts. The final section of this report summarizes some recent publications related to locational value of DERs in the form of an abbreviated literature review.