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  1. Optimal Coordinated EV Charging with Reactive Power Support in Constrained Distribution Grids

    Electric vehicle (EV) charging/discharging can take place in any P-Q quadrants, which means EVs could support reactive power to the grid while charging the battery. In controlled charging schemes, distribution system operator (DSO) coordinates with the charging of EV fleets to ensure grid’s operating constraints are not violated. In fact, this refers to DSO setting upper bounds on power limits for EV charging. In this work, we demonstrate that if EVs inject reactive power into the grid while charging, DSO could issue higher upper bounds on the active power limits for the EVs for the same set of grid constraints.more » We demonstrate the concept in an 33-node test feeder with 1,500 EVs. Case studies show that in constrained distribution grids in coordinated charging, average costs of EV charging could be reduced if the charging takes place in the fourth P-Q quadrant compared to charging with unity power factor.« less
  2. Photovoltaic Hosting Capacity of Feeders with Reactive Power Control and Tap Changers

    This paper proposes an algorithm to determine photovoltaic (PV) hosting capacity of power distribution networks as a function of number of PV injection nodes, reactive power support from the PVs, and the sub-station load tap changers (LTCs). In the proposed method, several minute by minute simulations are run based on randomly chosen PV injection nodes, daily PV output profiles, and daily load profiles from a pool of high-resolution realistic data set. The simulation setup is built using OpenDSS and MATLAB. The performance of the proposed method is investigated in the IEEE 123-node distribution feeder for multiple scenarios. The case studiesmore » are performed particularly for one, two, five and ten PV injection nodes, and looking at the maximum voltage deviations. Case studies show that the PV hosting capacity of the 123-node feeder greatly differs with the number of PV injection nodes. We have also observed that the PV hosting capacity increases with reactive power support and higher tap position of sub-station LTC.« less
  3. Reducing Demand Charges and Onsite Generation Variability Using Behind-the-Meter Energy Storage

    Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. This directive is bringing potential opportunities in deploying behindthe-meter energy storage (BMES) systems for various grid functionalities. This study quantifies techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with onsite distributed photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines costoptimal BMES configuration for reducing peak-demands and demand charges, and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of themore » proposed algorithm is evaluated through a 24 hours time sweep simulation performed using data from smart microgrid testbed at Idaho National Laboratory (INL). The simulation results demonstrated that this research provides a simple but effective solution for peak shaving, demand charge reductions, and smoothing onsite PV variability.« less
  4. Transmission Line Ampacity Improvements of AltaLink Wind Plant Overhead Tie-Lines Using Weather-Based Dynamic Line Rating

    Abstract—Overhead transmission lines (TLs) are conventionally given seasonal ratings based on conservative environmental assumptions. Such an approach often results in underutilization of the line ampacity as the worst conditions prevail only for a short period over a year/season. We presents dynamic line rating (DLR) as an enabling smart grid technology that adaptively computes ratings of TLs based on local weather conditions to utilize additional headroom of existing lines. In particular, general line ampacity state solver utilizes measured weather data for computing the real-time thermal rating of the TLs. The performance of the presented method is demonstrated from a field studymore » of DLR technology implementation on four TL segments at AltaLink, Canada. The performance is evaluated and quantified by comparing the existing static and proposed dynamic line ratings, and the potential benefits of DLR for enhanced transmission assets utilization. For the given line segments, the proposed DLR results in real-time ratings above the seasonal static ratings for most of the time; up to 95.1% of the time, with a mean increase of 72% over static rating.« less
  5. Improvement of Transmission Line Ampacity Utilization by Weather-Based Dynamic Line Rating

    Most of the existing overhead transmission lines (TLs) are assigned a static rating by considering the conservative environmental conditions (e.g., high ambient temperature and low wind speed). Such a conservative approach often results in underutilization of line ampacity because the worst conditions prevail only for a short period of time during the year. Dynamic line rating (DLR) utilizes local meteorological conditions and grid loadings to adaptively compute additional line ampacity headroom that may be available due to favorable local environmental conditions. This paper details Idaho National Laboratory-developed weather-based DLR, which utilizes a state-of-the-art general line ampacity state solver for real-timemore » computation of thermal ratings of TLs. Performance of the proposed DLR solution is demonstrated in existing TL segments at AltaLink, Canada, and the potential benefits of the proposed DLR for enhanced transmission ampacity utilization are quantified. Moreover, we investigated a hypothetical case for emulating the impact of an additional wind plant near the test grid. Furthermore, the results for the given system and data configurations demonstrated that real-time ratings were above the seasonal static ratings for at least 76.6% of the time, with a mean increase of 22% over the static rating, thereby demonstrating huge potential for improvement on ampacity utilization.« less
  6. Optimum aggregation of geographically distributed flexible resources in strategic smart-grid/microgrid locations

    This paper determines optimum aggregation areas for a given distribution network considering spatial distribution of loads and costs of aggregation. An elitist genetic algorithm combined with a hierarchical clustering and a Thevenin network reduction is implemented to compute strategic locations and aggregate demand within each area. The aggregation reduces large distribution networks having thousands of nodes to an equivalent network with few aggregated loads, thereby significantly reducing the computational burden. Furthermore, it not only helps distribution system operators in making faster operational decisions by understanding during which time of the day will be in need of flexibility, from which specificmore » area, and in which amount, but also enables the flexibilities stemming from small distributed resources to be traded in various power/energy markets. A combination of central and local aggregation scheme where a central aggregator enables market participation, while local aggregators materialize the accepted bids, is implemented to realize this concept. The effectiveness of the proposed method is evaluated by comparing network performances with and without aggregation. Finally, for a given network configuration, steady-state performance of aggregated network is significantly accurate (≈ ±1.5% error) compared to very high errors associated with forecast of individual consumer demand.« less
  7. Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid

    This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide themore » exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.« less
  8. Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination

    Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from themore » power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.« less
  9. A Comparison of Real-Time Thermal Rating Systems in the U.S. and the U.K.

    Real-time thermal rating is a smart-grid technology that allows the rating of electrical conductors to be increased based on local weather conditions. Overhead lines are conventionally given a conservative, constant seasonal rating based on seasonal and regional worst case scenarios rather than actual, say, local hourly weather predictions. This paper provides a report of two pioneering schemes-one in the U.S. and one in the U.K.-where real-time thermal ratings have been applied. Thereby, we demonstrate that observing the local weather conditions in real time leads to additional capacity and safer operation. Second, we critically compare both approaches and discuss their limitations.more » In doing so, we arrive at novel insights which will inform and improve future real-time thermal rating projects.« less
  10. Electrically powered hand tool

    An electrically powered hand tool is described and which includes a three phase electrical motor having a plurality of poles; an electrical motor drive electrically coupled with the three phase electrical motor; and a source of electrical power which is converted to greater than about 208 volts three-phase and which is electrically coupled with the electrical motor drive.

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"Myers, Kurt S."

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