The NIST Transactive Energy (TE) Modeling and Simulation Challenge for the Smart Grid (Challenge) spanned from 2015 to 2018. The TE Challenge was initiated to identify simulation tools and expertise that might be developed or combined in co-simulation platforms to enable the evaluation of transactive energy approaches. Phase I of the Challenge spanned 2015 to 2016, with team efforts that improved understanding of TE concepts, identified relevant simulation tools and co-simulation platforms, and inspired the development of a TE co-simulation abstract component model that paved the way for Phase II. The Phase II effort spanned Spring 2017 through Spring 2018, where the teams collaboratively developed a specific TE problem scenario, a common grid topology, and common reporting metrics to enable direct comparison of results from simulation of each team's TE approach for the defined scenario. This report presents an overview of the TE Challenge, the TE abstract component model, and the common scenario. It also compiles the individual Challenge participants' research reports from Phase II. The common scenario involves a weather event impacting a distribution grid with very high penetration of photovoltaics, leading to voltage regulation challenges that are to be mitigated by TE methods. Four teams worked with this common scenario and different TE models to incentivize distributed resource response to voltage deviations, performing these simulations on different simulation platforms. A fifth team focused on a co-simulation platform that can be used for online TE simulations with existing co-simulation components. The TE Challenge Phase II has advanced co-simulation modeling tools and platforms for TE system performance analysis, developed a referenceable TE scenario that can support ongoing comparative simulations, and demonstrated various TE approaches for managing voltage on a distribution grid with high penetration of photovoltaics.
Abstract-In this paper, we investigate two decomposition methods for their convergence rate which are used to solve security constrained economic dispatch (SCED): 1) Lagrangian Relaxation (LR), and 2) Augmented Lagrangian Relaxation (ALR). First, the centralized SCED problem is posed for a 6-bus test network and then it is decomposed into subproblems using both of the methods. In order to model the tie-line between decomposed areas of the test network, a novel method is proposed. The advantages and drawbacks of each method are discussed in terms of accuracy and information privacy. We show that there is a tradeoff between the information privacy and the convergence rate. It has been found that ALR converges faster compared to LR, due to the large amount of shared data.
This paper proposes a novel approach to designing technical and financial protocols needed to support the penetration of distributed energy resources (DERs). It first formulates a complex, hard-to-implement, centralized decisionmaking objective for providing end-to-end electricity service. It then introduces a new taxonomy of an end-to-end interactive operations planning framework. The taxonomy rests on the dynamic monitoring and decisions systems (DyMoNDS) principles for supporting interactive protocols of (i) end-to-end interactions within a complex, multilayered multi-voltage power system; (ii) dynamic energy resource management system (DERMS) interactions with their DERs as well as with the bulk power system (BPS) operators; and (iii) DERs interactions with DERMS. The distributed model predictive control for creating physically implementable cost functions is essential. Also, the minimal coordination of different layers utilizes an AC optimal power flow that is essential for ensuring power flow delivery. We next provide a proof-of-concept illustration on the IEEE 14 bus system augmented by two standardized microgrids of the proposed interactive protocols, and their potential use for enhancing dynamic host capacity (DHC). While novel, this approach is a natural outgrowth of the existing industry operations: It only requires enhancing decision-making tools by the stakeholders, and carefully-defined protocols for implementing their interactions.
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