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Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies and the plethora of other resources and assets that are becoming part of modern electricity production, delivery and consumption systems. As a result, the US Department of Energy's Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D™ that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

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Recent work in the field of distribution system analysis has shown that the traditional method of peak load analysis is not adequate for the evaluation of emerging distribution system technologies. Voltage optimization, demand response, electric vehicle charging, and energy storage are examples of technologies with characteristics having daily, seasonal, and/or annual variations. In addition to the seasonal variations, emerging technologies such as demand response and plug-in electric vehicle charging have the potential to receive control signals that affects their energy consumption. To support time-series analysis over different time frames and to incorporate potential control signal inputs, detailed end-use load models that accurately represent loads under various conditions, and not just during the peak load period, are necessary. This paper will build on previous end-use load modeling work and outline the methods of general multi-state load models for distribution system analysis.

Volt/var control (VVC) of smart PV inverter is becoming one of the most popular solutions to address the voltage challenges associated with high PV penetration. This work focuses on the local droop VVC recommended by the grid integration standards IEEE1547, rule21 and addresses their major challenges i.e. appropriate parameters selection under changing conditions, and the control being vulnerable to instability (or voltage oscillations) and significant steady state error (SSE). This is achieved by proposing a two-layer local real-time adaptive VVC that has two major features i.e. a) it is able to ensure both low SSE and control stability simultaneously without compromising either; and b) it dynamically adapts its parameters to ensure good performance in a wide range of external disturbances such as sudden cloud cover, cloud intermittency, and substation voltage changes. A theoretical analysis and convergence proof of the proposed control is also discussed. The proposed control is implementation friendly as it fits well within the integration standard framework and depends only on the local bus information. The performance is compared with the existing droop VVC methods in several scenarios on a large unbalanced 3-phase feeder with detailed secondary side modeling.