• Energy Research

Abstract Paper aims This paper presents a manufacturing process model for assessing the effects on economic, social, and environmental targets, given variations on corporate strategies of production, innovation, marketing, and demand for final goods. Originality The model integrates economic, social, and environmental dimensions that are validated through three main scenarios: Business as Usual (no strategic application), Business as Investment (strategic application), and Business as Vision (changes in demand). Research method The model estimates the social, environmental, and economic performance through time based on the System Dynamics methodology. Main findings The results demonstrate the model's suitability as a decision-support tool for sustainability planning in a corporate environment. Implications for theory and practice The model facilitates the analysis of the effects of resource allocation on corporate strategy.

This paper aims to estimate the three-phase voltage sensitivity matrix and the network topology of a low-voltage distribution network from smart meter data, which measures voltage magnitude, current magnitude, and power factor with a lead/lag indicator. The targeted networks are three-phase networks with single-phase loads. Understanding network sensitivity and topology is crucial for fault detection, unmetered load identification, and addressing Dynamic Operating Envelope problems. The problem is formulated as a constrained optimization problem to estimate both the three-phase voltage sensitivity and the low-voltage transformer voltage. The estimated voltage sensitivity is used to further identify the network topology, by implementing an enhanced Recursive-Grouping and Backtracking algorithm, as well as a candidate topology selection technique. The proposed method is tested on the 55-node European feeder and several synthetic networks. Compared to the state-of-the-art, the results show a four-fold improvement in the accuracy of voltage sensitivity estimation and substantially fewer mistakes in the topology estimates. The result underscores the efficacy of a three-phase network model and voltage angle approximation in enhancing estimation accuracy.