Abstract
Global trends such as the growing share of renewable energy sources in the generation mix, electrification, e-mobility, and the increasing number of prosumers reshape the electricity value chain, and distribution systems are necessarily affected. These systems were planned, developed, and operated as a passive structure for decades with low level of observability. Due to the increasing number of system states, real time operation planning and flexibility services are the key in transition to an active grid management. In this pathway, distribution system state estimation (DSSE) has a great potential, but the real demonstration of this technique is in an early stage, especially on low-voltage level. This paper focuses on the gap between theory and practice and summarizes the limits of low-voltage DSSE implementation. The literature and the main findings follow the general structure of a state estimation process (meter placement, bad data detection, observability, etc.) giving a more essential and traceable overview structure. Moreover, the paper provides a comprehensive mapping of the possible use-cases state estimation and evaluates 27 different experimental sites to conclude on the practical applicability aspects.
Highlights
Since its first proposal by Schweppe in 1969, state estimation (SE) has become a central element of power system operation, especially in high voltage (HV) transmission networks
High quality reviews of distribution system state estimation (DSSE) in general have been presented in a number of papers lately
The scope of this section is to analyze pilot applications and compare the approaches to theoretical research, underlining the limitations occurring from the technical circumstances, economic viability, and the need of the Distribution system operator (DSO)
Summary
Since its first proposal by Schweppe in 1969, state estimation (SE) has become a central element of power system operation, especially in high voltage (HV) transmission networks. The challenges transforming power systems (electrification, smart grids, variable renewable energy sources, distributed generation, etc.) have brought the need for SE to the forefront of distribution network operation and planning as well. This has led to increased research activities culminating in hundreds of papers published in this field. Primadianto introduces a summary of state-of-the-art DSSE techniques, grouping scientific papers based on the type of algorithm they use [1]. A similar scientific scope was defined by Majdoub et al in [2], with the aim of highlighting the spread of techniques that are based on evolutionary algorithms
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