Towards metamodeling the neighborhood-level grid impact of low-carbon technologies

Abstract

Heating electrification and distributed renewable generation in the residential sector are among prominent solutions advocated for energy saving and carbon emission reduction. However, research shows these low-carbon technologies may create issues at the low-voltage (LV) distribution grid. High-level policy assessment currently lacks the support to take into account such local grid restrictions. To achieve this, we propose the use of a probabilistic simulation framework in combination with metamodeling, that allows to assess the potential LV grid impact for a wide range of cases. The probabilistic framework is first presented, which is developed for Belgian residential neighborhoods with air-source heat pumps and rooftop PV, based on previous work. Given the complexity and computational requirements of this approach, the paper furthermore proposes metamodeling as a technique to obtain inexpensive evaluation of low-voltage grid impact indicators, suitable for high-level assessments. Although metamodeling is extensively used in various engineering domains, no application in district-level grid-related indicators is available. Consequently, this paper's focus lies on discussing the various steps and options of the metamodeling procedure, while emphasizing problemspecific challenges. Lastly, the proposed metamodeling methodology is used for training simple metamodels for voltage indicators in neighborhood-level LV grids. Linear regression performed fairly well in predicting the minimum voltage levels, though less accurately close to the lower voltage limit, while logistic regression effectively detected feeders with violations.

Simulation Metamodeling Approach to Complex Design of Garment Assembly Lines

“…In this paper, simulation metamodeling was proposed as a technique to obtain inexpensive evaluation of garment assembly line design and determine the relationship between input variables and the response. Although metamodeling is extensively used in various engineering domains, no application for the design of complex garment assembly line system is available [19]. Consequently, the present paper demonstrates the applicability and suitability of designing a complex garment assembly line using simulation metamodeling.…”

“…This is because adding the resource in the bottleneck workstation reduces both cycle time and work in progress (WIP). In spite of the fact that the metamodel was not used for further model prediction, the present study found it most suitable for inference [19] and initial solution (local optimal) for optimization process [37]. The inference was drawn from the regression metamodel to analyze the factors' effects on the production throughput.…”

“…While the latter requires a metamodel that accurately approximates the system's response, without seeking an explanation for the outcome [19].…”

“…The metamodeling has also been extensively used in analysis of building structures [17]. While the other application areas of metamodeling include cyberphysical systems [18] and grid system low carbon energy technology [19].…”

Simulation metamodeling approach to complex design of garment assembly lines

“…The most commonly used approaches for metamodel construction are statistic-based and machine-learning. The former solely depends on the data received from the simulation experiments which includes linear (polynomial) regression, support vector regression, multivariate adaptive regression spline, Gaussian process regression (kriging), and radial basis function [19,[27][28][29][30][31]. The latter is based on neural networking, rule learning, and fuzzy logic [16,18,32,33].…”