Peak Load Management in Distribution Systems Using ADMS and DERMS
This presentation provides an overview of peak load management for distributed energy resources.
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This presentation provides an overview of peak load management for distributed energy resources.
Distributed energy resource (DER) management and control is disjointed, siloed, and at times conflicting. Behind-the-meter (BTM) assets can provide significant flexibility but are poorly integrated with the grid. Centralized control methods alone are not scalable. The objective is to develop and demonstrate an architecture that: provides reliable, resilient, and secure grid services; enables scalable, near-real-time management of utility- and small-scale DERs; supports transactive control, aggregation, and direct control of DERs; and incorporates existing utility management systems.
Develop algorithms for leveraging existing AMI infrastructure to provide a foundational, pervasive secondary voltage monitoring network solution.
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A conceptual numerical methodology derived from Grid Architecture principles is introduced for deconflicting setpoints issued by multiple advanced distribution management system applications. The methodology applies technical, economic, environmental, and social rules to eliminate non-viable combinations. The concept of temporal equipment controls budgets is introduced to preserve the health of physical assets and avoid equipment damage through repeated controls cycling. The rules are combined with a multi-criteria decision-making framework to select a near-optimal set of deconflicted setpoints using a set of qualitative and quantitative decision criteria selected by the distribution system operator. Numerical results are demonstrated on the IEEE 123-bus test feeder for three competing applications. Three alternative distributed schemes are used to decompose the problem: by topological area, by phase, and fully decentralized. The fully decentralized implementation is shown to yield near-optimal deconfliction results with significantly reduced computational time.
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This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. The first document previously defined the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem was decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. It was recommended that selection of the optimal number of decompositions of the deconfliction problem be made based on a tradeoff analysis between computational speed and global optimality. This second document defines an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.
This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.
This workbook presents a hypothetical project designed to facilitate discussion and the practical application of cyber-informed engineering principles.
This project will evaluate the impact of augmenting a utility situational awareness with additional supervisory sensors downstream of the substation to enhance the resiliency and reliability of the power delivery and management by improving the identification of a fault location.
A system for testing an optical surface includes a rangefinder configured to emit a light beam and a null assembly located between the rangefinder and the optical surface. The null assembly is configured to receive and to reflect the emitted light beam toward the optical surface. The light beam reflected from the null assembly is further reflected back from the optical surface toward the null assembly as a return light beam. The rangefinder is configured to measure a distance to the optical surface using the return light beam.
Advanced Distribution Management Systems not generally optimize over the entire feeder because there are few high-fidelity distribution circuit models and real-time distribution-connected sensors are rare. The limited observability at the distribution level makes it difficult to globally optimize distribution operations and issue control setpoints to power systems equipment or Distributed Energy Resources (DER) to perform grid-support services. For example, setpoints can be issued to DER based on results from an optimization module that incorporates a static or time-series feeder simulation. Feeder simulation initial conditions are populated with photovoltaic (PV) and load forecasts, state estimation results, and/or digital twin measurements or state output. The real-time (RT) digital twin runs a model of the feeder to generate state estimation pseudo-measurements since there are limited live feeder measurements.
Highlights: • 4-Hydroxybenzoic acid enhances the sensitivity of MCF-7/ADM to ADM-induced apoptosis. • 4-Hydroxybenzoic acid induces apoptosis in breast cancer cell lines. • 4-Hydroxybenzoic acid induces cell cycle arrest in G2/M phase. Breast cancer is reported a very complex disease along with heterogeneous morphological characteristics and unrelated clinical behavior, and is a leading cancer among female. Nevertheless, chemo-resistance is frequently observed. Adriamycin (ADM) is a always employed drug to treat clinical breast cancer. However, strong resistance to ADM limited its clinical efficacy. Deregulation of HDAC6 activity is linked to various diseases including cancer resulting in accumulating interest for developing HDAC6 inhibitors. In the present study, for the first time, we found that 4-Hydroxybenzoic acid (4-HBA), as histone deacetylase 6 (HDAC6) inhibitor, could successfully reverse ADM resistance in human breast cancer cells. 4-HBA significantly promoted the anticancer effect of ADM on apoptosis induction, as evidenced by the increased expressions of Caspase-3 and PARP cleavage, which was associated with the promotion p53 and homeodomain interacting protein kinase-2 (HIPK2) expressions in ADM-resistant breast cancer cells. Furthermore, the suppressive effect of ADM on drug-resistant breast cancer cells was accelerated by 4-HBA through increasing the number of cells distributed in G2/M phase of cell cycle arrest. Inhibiting HIPK2/p53 pathway could abolish 4-HBA/ADM co-treatment-induced apoptosis and G2/M cell cycle arrest. Importantly, HDAC6 expressions were also significantly down-regulated in ADM-resistance breast cancer cells co-treated with ADM and 4-HBA. Additionally, 4-HBA clearly potentiated the anticancer role of ADM in the MCF-7 breast cancer animal model with low toxicity. Therefore, 4-HBA could be applied as an effective HDAC6 inhibitor to reverse human breast cancer resistance. Herein, the 4-HBA and ADM combination might represent as a useful therapeutic strategy to prevent human breast cancer.
The next generation of Earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of POLarization and Directionality of the Earth's Reflectances (POLDER) 670 nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical Angular Distribution Models (ADMs) for estimating top-of-atmosphere (TOA) albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types: The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-tau approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-tau approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field. Albedos based on ADMs that assume cloud properties are unbiased (fixed-tau approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching approximately equals 12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60 deg and 70 deg. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-tau approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (less than 1% relative error). When the ADMs are applied separately to populations consisting of only liquid water and ice clouds, significant biases in albedo with viewing geometry are observed (particularly at low sun elevations), highlighting the need to account for cloud phase both in cloud optical depth retrievals and in defining ADM scene types. ADM-derived monthly mean albedos determined for all 5 deg x 5 deg latitude/longitude regions over ocean are in good agreement (regional RMS relative errors less than 2%) with those obtained by direct integration when ADM albedos inferred from specific angular bins are averaged together. Albedos inferred from near-nadir and oblique viewing zenith angles are the least accurate, with regional RMS errors reaching approximately 5-10% (relative). Compared to an earlier study involving ERBE ADMs, regional mean albedos based on the 19 scene types considered here show a factor of 4 reduction in bias error and a factor of 3 reduction in RMS error.