AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

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.

DOE's mission under the Distributed Energy and Electricity Reliability (DEER) Program is to strengthen America's electric energy infrastructure and provide utilities and consumers with a greater array of energy-efficient technology choices for generating, transmitting, distributing, storing, and managing demand for electric power and thermal energy. DOE recognizes that distributed energy technologies can help accomplish this mission. Distributed energy (DE) technologies have received much attention for the potential energy savings and electric power reliability assurances that may be achieved by their widespread adoption. Fueling the attention has been the desire to reduce greenhouse gas emissions and concern about easing power transmission and distribution system capacity limitations and congestion. However, these benefits may come at a cost to the electric utility companies in terms of lost revenue and other potential impacts on the distribution system. It is important to assess the costs and benefits of DE to consumers and distribution system companies. DOE commissioned this study to assess the costs and benefits of DE technologies to consumers and to better understand the effect of DE on the grid. Current central power generation units vent more waste heat (energy) than the entire transportation sector consumes and this wasted thermal energy is projected to grow by 45% within the next 20 years. Consumer investment in technologies that increase power generation efficiency is a key element of the DOE Energy Efficiency program. The program aims to increase overall cycle efficiency from 30% to 70% within 20 years as well. DOE wants to determine the impact of DE in several small areas within cities across the U.S. Ann Arbor, Michigan, was chosen as the city for this case study. Ann Arbor has electric and gas rates that can substantially affect the market penetration of DE. This case study analysis was intended to: (1) Determine what DE market penetration can realistically be expected, based on consumer investment in combined heat and power systems (CHP) and the effect of utility applied demand response (DR). (2) Evaluate and quantify the impact on the distribution utility feeder from the perspective of customer ownership of the DE equipment. (3) Determine the distribution feeder limits and the impact DE may have on future growth. For the case study, the Gas Technology Institute analyzed a single 16-megawatt grid feeder circuit in Ann Arbor, Michigan to determine whether there are economic incentives to use small distributed power generation systems that would offset the need to increase grid circuit capacity. Increasing circuit capacity would enable the circuit to meet consumer's energy demands at all times, but it would not improve the circuit's utilization factor. The analysis spans 12 years, to a planning horizon of 2015. By 2015, the demand for power is expected to exceed the grid circuit capacity for a significant portion of the year. The analysis was to determine whether economically acceptable implementation of customer-owned DE systems would reduce the peak power demands enough to forestall the need to upgrade the capacity of the grid circuit. The analysis was based on economics and gave no financial credit for improved power reliability or mitigation of environmental impacts. Before this study was completed, the utility expanded the capacity of the circuit to 22 MW. Although this expansion will enable the circuit to meet foreseeable increases in peak demand, it also will significantly decrease the circuit's overall utilization factor. The study revealed that DE penetration on the selected feeder is not expected to forestall the need to upgrade the grid circuit capacity unless interconnection barriers are removed. Currently, a variety of technical, business practice, and regulatory barriers discourage DE interconnection in the US market.

Distribution power grids are rapidly changing from a centralized and unidirectional distribution network to a decentralized, bidirectional network that supports the penetration of large amounts of observable/unobservable distributed energy (DERs). The additional variability, uncertainty and scale of control variables generated by DER integration greatly increase the complexity of power system operation. This paper presents a method to improve the resiliency of distribution systems using increasing distributed energy resources (DERs). DERs and loads are aggregated into a switch-level equivalent model while retaining controllability information for real-time power outage management analysis after a power outage. Pre-fault smart meter measurements serve as input to a machine learning integrated cold load pickup (CLPU) model to obtain short-term load predictions, while optimal recovery analysis is carried out to determine restored network topology and utility control loads and DERs set-points.

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.

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.

Emission of greenhouse gases and depletion of fossil fuel reserves are two key drivers, which are forcing the mankind to generate the future energy demand from the renewable energy resources. These resources are generally distributed in nature and are directly integrated at distribution levels. Increasing penetration of the distributed energy resources in distribution power networks creates additional operational and control issues. These are mostly regulatory, economical load dispatching, power quality and protection issues.Generally power distribution systems are protected with the help of dedicated over current based protection schemes. But increasing share of distributed energy resources penetration in electric utilities poses a serious threat to the existing protection coordination schemes of the distribution systems. Distributed energy resources connected distribution networks become interconnected in nature and protection coordination schemes, which are designed for unidirectional flow of fault currents become ineffective/non-functional.Therefore, new protection coordination schemes are required for providing the adequate protection coordination for distributed energy resources connected electric power networks. In the available literature, the protection coordination schemes for radial distribution systems and developments in the area of protection coordination are discussed in detail. A thorough review for all these protection coordination schemes for distribution systems with and without distributed energy resources is done in this review article. It includes the analytical and artificial intelligence based techniques application for coordination of protective relays in the distribution systems. The limitations and research gaps in the area of protection coordination schemes are also presented in this review article.The aim of this research paper is to bring all the available research in the area of relay coordination on one platform, so that it will help the emerging researcher to identify the future scope of relay coordination application for distributed energy resources connected distribution systems.

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 penetration of distributed energy resources (DERs) in distribution systems brings new challenges in protection of distribution systems. The bidirectional fault current flow caused by the presence of DERs and their characteristics of low fault current make the conventional relays deficient in protecting distribution systems with DERs. In this paper, we propose the use of Dynamic State Estimation-based protection(EBP) which is immune to bidirectional flows as well as low levels of fault currents to protect distribution systems with DERs. EBP identifies faults based on the goodness of fit between the measurements and the estimated state values from the protection zone, irrespecitively of fault current level and direction, or harmonic content that may be generated by DERs. Models of two real-world distribution systems with utility size PV arrays were built in WinIGS to test the performance of EBP. The results showed that EBP can effectively detect faults in distribution systems with substantial PV capacity and it is immune to the characteristics of active distribution systems.

ABSTRACTMedium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

Modern distribution systems are becoming more resilient against power outages thanks to the flexible generation capacity provided by the increasing integration of distributed energy resources (DERs). Compared to utility-scale DERs, which can be directly controlled by system operators, small-scale, behind-the-meter DERs are much more difficult to coordinate despite being the vast majority. Two major obstacles to the implementation of DERs for service restoration are the coordination of behind-the-meter DERs and the management of uncertainty. In this paper, a novel distribution system restoration strategy is proposed to overcome these two obstacles. The flexibility of be-hind-the-meter DERs is quantified and integrated into the restoration planning models within a hierarchical structure. The model predictive control technique is employed to enable adaptive restoration planning solution adjustments to accommodate fault scenarios and forecast errors. Besides, real-time power dispatch models are proposed to maintain power balance using available DER capability. Comprehensive integration of adaptive restoration planning schemes and real-time dispatch results are achieved through a collaborative restoration framework. Finally, the effectiveness of the proposed restoration strategy is verified through a modified IEEE 123-bus system and a real-world utility system.

This paper proposes a hierarchical look-ahead framework to conduct conservation voltage reduction (CVR) when distributed energy resources such as solar photovoltaic (PV) systems and energy storage systems (ESSs), and demand response programs are integrated into distribution systems. With the increasing deployment of PV systems in distribution systems, their frequently varying power output due to cloud movements could have a detrimental impact on the consumer’s voltage quality, consequently leading to degraded CVR performance. A two-level CVR framework for the coordination of an on-load tap changer (OLTC), capacitor banks (CBs), and the smart inverters of PV systems/ESSs is presented, in which these elements operate to reduce the voltage profile along the distribution feeder at different temporal scales. At the global level, the operations of the OLTC and the CBs are scheduled every hour to achieve the best CVR performance in an optimization problem using mixed-integer linear programming. When voltage violations occur rapidly, the smart inverters of PV systems and ESSs help to maintain a lower voltage profile every second based on the proposed piecewise droop control functions at the local level. A simulation study is carried out in an IEEE 33-bus distribution system with an OLTC, CBs, PV systems, and ESSs, and our results demonstrate the advantages of the proposed approach in terms of voltage level and energy savings. Furthermore, the impact of demand reduction on the proposed approach is quantified, and we verify that a higher demand reduction yields more energy savings in the proposed framework.

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.

There is a conflict developing, or already underway, pitting distributed energy resource (DER) technologies against the grid-based assets required to facilitate their expansion within the distribution system. The growing push for non-wires alternatives (NWAs), which are being promoted as a replacement for traditional substations, transformers, and circuits, is, at best, incorrectly evaluated and, at worst, misconceived. Advocates of NWAs are supporters of the rapid development of DERs, arguing that DERs' contribution to avoiding capital expenditures for additional-most often, distribution level grid-assets should be rewarded. Other NWAs advocates challenge the need for upgrades to the distribution system at all, pointing to slow or negative demand growth and the possibility of stranded assets.There are at least two economic forces at play in the interaction between advocates of NWAs and traditional distribution planning. Both forces focus on demand-level changes in the distribution sector of the power system. DERs require access to market information to value individual technologies at the time of the initial capital decision as well as to make operational decisions in real time concerning whether or not to produce as a function of the energy's market value. The EV operator (individual or fleet) requires much of the same information as the DER owner but with an eye to opposite incentives charging (buying) when the price is low and not consuming (not charging) when the price is high. Where there is full agreement is that knowledge about the physical distribution system is required both for production and sale and for consumption and purchase.

Efficient and effective management of the electric distribution system requires an integrated approach to allow various systems to work in harmony, including distribution management systems (DMS), distributed energy resources (DERs), distributed energy resources management systems, and microgrids. This study highlights some outcomes from a recent project sponsored by the US Department of Energy, Office of Electricity Delivery and Energy Reliability, including information about (i) the architecture of these integrated systems and (ii) expanded functions of two example DMS applications to accommodate DERs: volt-var optimisation and fault location, isolation, and service restoration. In addition, the relevant DER group functions necessary to support communications between the DMS and a microgrid controller in grid-tied mode are identified.

Federal Energy Regulatory Commission (FERC) Orders 841 and 2222 have recommended that distributed energy resources (DERs) should participate in energy and reserve markets; therefore, a mechanism needs to be developed to facilitate DERs' participation at the distribution level. Although the available reserve from a single distribution system may not be sufficient for tertiary frequency regulation, stacked and coordinated contributions from several distribution systems can enable them participate in tertiary frequency regulation at scale. This paper proposes a deep reinforcement learning (DRL)-based approach for optimization of requested aggregated reserves by system operators among the clusters of DERs. The co-optimization of cost of reserve, distribution network loss, and voltage regulation of the feeders are considered while optimizing the reserves among participating DERs. The proposed framework adopts deep deterministic policy gradient (DDPG), which is an algorithm based on an actor-critic method. The effectiveness of the proposed method for allocating reserves among DERs is demonstrated through case studies on a modified IEEE 34-node distribution system.