Open source interface for distribution system modeling in power system co-simulation applications and two algorithms for populating feeder models, An

2017 Spring.Includes bibliographical references.The aging electric infrastructure power system infrastructure is undergoing a transformative change mainly triggered by the large-scale integration of distributed resources such as distributed generation, hybrid loads, and home energy management systems at the end-use level. The future electric grid, also referred to as the Smart Grid, will make use of these distributed resources to intelligently manage the day to day power system operations with minimum human intervention. The proliferation of these advanced Smart Grid resources may lead to coordination problems to maintain the generation-demand balance at all times. To ensure their safe integration with the grid, extensive simulation studies need to be performed using distributed resources. Simulation studies serve as an economically viable alternative to avoid expensive failures. They also serve as an invaluable platform to study energy consumption behavior, demand response, power system stability, and power system state estimation. Traditionally, power system analysis has been performed in isolated domains using simulation tools for the transmission and distribution systems. Moreover, modeling all the power system assets using a single power system tool is difficult and inconclusive. From the Smart Grid perspective, a common simulation platform for different power systems analysis tools is essential. A co-simulation framework enables the interaction of multiple power system tools, each modeling a single domain in detail, to run simultaneously and provide a holistic power system overview. To enable the co-simulation framework, a data exchange platform between the transmission and distribution system simulators is proposed to model transmission and distribution assets on different simulation testbeds. A graphical user interface (GUI) is developed as a frontend tool for the data exchange platform and makes use of two developed algorithms that simplifies the task of: 1. modeling distribution assets consisting of diverse feeder datasets for the distribution simulator and balanced three-phase level assets for the transmission system simulator, and 2. populating the distribution system with loads having stochastic profiles for timestep simulations. The load profiles used in the distribution system models are created using concepts from one-dimensional random walk theory to mimic the energy consumption behavior of residential class of consumers. The algorithms can simulate large scale distribution system assets linked to a transmission system for co-simulation applications. The proposed algorithms are tested on the standard test system – Roy Billinton Test System (RBTS) to model detailed distribution assets linked to a selected transmission node. Two open source power system simulators—MATPOWER© and GridLAB-D© are used for the transmission and distribution simulation process. The algorithms accurately create detailed distribution topology populated with 4026 residential loads expanded from the transmission node, bus 2 in RBTS. Thus, an automated modeling of power system transmission and distribution assets is proposed along with its application using a standard test system is provided

Optimal Scheduling of Electrolyzer in Power Market with Dynamic Prices

Optimal scheduling of hydrogen production in dynamic pricing power market can maximize the profit of hydrogen producer; however, it highly depends on the accurate forecast of hydrogen consumption. In this paper, we propose a deep leaning based forecasting approach for predicting hydrogen consumption of fuel cell vehicles in future taxi industry. The cost of hydrogen production is minimized by utilizing the proposed forecasting tool to reduce the hydrogen produced during high cost on-peak hours and guide hydrogen producer to store sufficient hydrogen during low cost off-peak hours

Plug-and-Play Regional Models for Real-Time Electromagnetic Transient Simulations of Large-Scale Power Grids: A Case Study of New York State Power Grid

Modeling large-scale electric power systems for electromagnetic transient (EMT) studies in real-time simulations is challenging due to factors such as real-time constraints, computational workload, extensive modeling efforts, and model accuracy. Developing a detailed and accurate EMT model of large-scale modern transmission networks is time-consuming and requires advanced computational capabilities. This paper proposes a Plug-and-Play (PnP) regional modeling approach to address the abovementioned challenges. An entire power grid is split into multiple regions, and each region is modeled with the PnP feature. A multi-regional model can be easily formed by merging multiple regional models due to the PnP capability. The advantage of PnP regional models is that it enhances the computational efficiency of an EMT simulation. Regional EMT models enable the accurate representation of a portion of the power system, allowing for accelerated simulation of local EMT models while providing a Thevenin equivalent of the rest of the system. A comprehensive procedure to develop and maintain the PnP regional models will be presented in this paper. A case study of the New York State (NYS) power grid is taken into consideration to demonstrate how utilities can utilize the proposed approach to develop their power grid models for EMT studies. A detailed explanation of using the PnP feature to form a multi-regional model is presented to provide a solid perspective on the application of developed PnP regional models. Furthermore, a code-based automated process is developed to maintain the real-time models up-to-date, which involves automatically processing input models and generating a real-time model accommodating all the changes. The significance of this study is to provide a guideline for handling large-scale power system modeling and deliver insight into the industry to the researcher