With the increased penetrations of distributed energy resources (DERs), need for integrated transmission and distribution system analysis (T&D) is imperative. This paper presents an unbalanced T&D framework using iteratively coupled co-simulation approach. The systems are solved separately dedicated solvers. An iterative approach developed interface coupling to ensure convergence boundary variables. To do so, analytical expressions governing obtained. First-order second-order convergent...

Increasing penetration of proactive agents, including distributed energy resources (DERs) and responsive loads (RLs), in distribution systems motivates methods to incentivize market participation from demand-side resources. The complexity resulting large-scale integration agents has challenged the viability centrally managing grid a system environment motivated decentralized frameworks coordinate transactions. Existing are primarily focused on designing transaction mechanisms. They neither...

The critical need to model and analyze transmission distribution (T&D) systems together, given the increasing levels of distributed energy resource (DER) penetrations, has led development several T&D co-simulation platforms, both commercial open-source. strength coupling between system dictates accuracy studies; however, higher comes at cost increased computational burden. objective this paper is (1) systematically different protocols, viz. decoupled (DC), loosely coupled (LC), tightly (TC),...

Analyzing the interactions between transmission and distribution (T&D) systems is becoming imperative with increased penetrations of distributed energy resources (DERs) on electric power networks. An assessment impacts DERs connected to system operations required especially for conditions leading level unbalance. In this paper, a coupled T&D analysis framework developed through co-simulation approach. The separately solves decoupled models. are captured by exchanging flow solutions at point...

The ever-growing complexity of power grid is increasing the interactions between its different integrated subsystems and rendering traditional analysis tools insufficient for high-fidelity studies. Specifically, integration distributed energy resources (DERs) transmission distribution (T&D) systems. decoupled methods T&D system cannot capture systems thus, calling new in analysis. Lately, several co-simulation frameworks have been developed to model by exchanging flow solutions at point...

Reinforcement learning algorithms have been found useful in solving optimal power flow (OPF) problems electric distribution systems. However, the use of largely model-free reinforcement that completely ignore physics-based modeling grid compromises optimizer performance and poses scalability challenges. This paper proposes a novel approach to synergistically combine models with learning-based using imitation solve distribution-level OPF problems. Specifically, we propose based improvements...

The need for integrated transmission and distribution system analysis (T & D) has been recently identified by research industry alike. This paper presents an unbalanced T D framework using iteratively coupled co-simulation approach. systems are solved separately dedicated solvers. An iterative approach is developed interface coupling to ensure convergence of the boundary variables. To do so, analytical expressions governing obtained first-order convergent methods Fixed-point iteration (FPI)...

Common practice in transmission and distribution (T&D) systems analysis has been to treat them independently by decoupling those at the point of common coupling (PCC). With large amount distributed energy resources (DER) being added networks, interactions between T&D PCC produce unacceptable errors. This study discusses an alternate approach for combined using co-simulation technique. The proposed framework couples two iteratively exchanging power flow variables PCC. is implemented IEEE...

With the growing penetrations of distributed energy resources (DERs), it is imperative to evaluate their impacts on transmission system operations. In this paper, an iteratively coupled and distribution (T&D) co-simulation framework employed study increasing distribution-connected photovoltaic (PV) systems voltages. The introduces iterative coupling unbalanced analysis that help accurately replicate standalone T&D results without resorting computational challenge developing large-scale...

Battery energy storage systems (BESS) are proving to be an effective solution in providing frequency regulation services the bulk grid. However, there several concerns for transmission/distribution system operators (TSO/DSO) with frequent dispatching of distribution-connected fast-responding systems. Unfortunately, existing decoupled models transmission and distribution (T&D) simulations unable capture complex interactions between two especially concerning problems due rapidly varying...

This paper presents an adaptive ECG enhancement procedure based on Synchrosqueezing Transform (SST) to eliminate Powerline interference (PLI) from signal. work also incorporates the principles of modified discrete cosine transform (MDCT) and wiener filter. PLI is a major source artifacts in signal which can affect its interpretation. Separating poses great challenge analysis. The existing removal techniques suffer two drawbacks such as Mode Mixing, inability deal with non-stationary...

With the growing penetrations of distributed energy resources (DERs), it is imperative to evaluate their impacts on transmission system operations. In this paper, an iteratively coupled and distribution (T&D) co-simulation framework employed study increasing distribution-connected photovoltaic (PV) systems voltages. The introduces iterative coupling unbalanced analysis that help accurately replicate standalone T&D results without resorting computational challenge developing large-scale T\&D...

We introduce an open-source platform to interface the OpenAI gym environment (an repository for RL algorithms) with OpenDSS distribution system simulator). The proposed OpenDSS-RL wrapper enables seamless application of reinforcement learning (RL) algorithms power systems using a standardized environment. Specifically, provides user ability perform training and testing any state-of-the-art algorithm on models available in OpenDSS. demonstrate voltage regulation applications IEEE 13-bus,...