Stepwise investment plan optimization for large scale and multi-zonal transmission system expansion

This paper develops a long term transmission expansion optimization methodology taking the probabilistic nature of generation and demand, spatial aspects of transmission investments and different technologies into account. The developed methodology delivers a stepwise investment plan to achieve the optimal grid expansion for additional transmission capacity between different zones. In this paper, the optimization methodology is applied to the Spanish and French transmission systems for long term optimization of investments in interconnection capacity

Long term investment optimization methodology for multi-zonal transmission expansion

This paper introduces a stepwise investment optimization methodology for transmission system expansion planning. The objective of the developed methodology is to determine transmission expansion plans to realize a desired interconnection capacity between multiple zones minimizing investment and operational costs. The methodology uses MILP optimization and a modified A∗ shortest path algorithm sequentially in order to determine the optimal investment time point, transmission topology, technology and routing. Spatial constraints and their effects on the installation cost are taken into account in the technology and route optimization. A possible application of the methodology is demonstrated on a stepwise investment plan for the North Sea region

Combined Unbalanced Distribution System State and Line Impedance Matrix Estimation

To address the challenges that the decarbonization of the energy sector is bringing about, advanced distribution network management and operation strategies are being developed. Many of these strategies require accurate network models to work effectively. However, distribution network data are known to contain errors, and attention has been given to techniques that allow to derive improved network information. This paper presents a novel method to derive line impedance values from smart meter measurement time series, with realistic assumptions in terms of meter accuracy, resolution and penetration. The method is based on unbalanced state estimation and is cast as a non-convex quadratically constrained optimization problem. Both line lengths and impedance matrix models can be estimated based on an exact nonlinear formulation of the steady-state three-phase network physics. The method is evaluated on the IEEE European Low Voltage feeder (906 buses) and shows promising results

Towards a Sustainable Meat Production with Precision Livestock Farming

In future years, modern farmers will be under greater pressure to care for a large number of animals in order to remain economically viable. There is a growing global awareness of welfare conditions in animal production and a tendency towards more intensive production, resulting in a need for better genetics and a more precise way to monitor them. The challenge and the success of intensive farming will lie in how precisely we can steer the animals towards their genetic potential. Sensors have the potential to replace the eyes, ears and nose of the farmer by continuously assessing different key indicators throughout the production process, 24 hours a day and 7 days a week. The continuous automated monitoring of varying needs of individual living farm animals at every moment and anywhere is called Precision Livestock Farming (PLF). The aim of this paper is to describe how PLF-systems are used within the EU-PLF project to work towards an automated assessment of sustainability on farm level, by continuous monitoring of animal behaviour. The roadmap towards a sustainable meat production, viewed from a technologist’s point of view, is described hereafter in four steps. This phase comprises an implementation of PLF tools, where the basic inputs are measured and monitored in function of time. In a next step, a more complete control of the production process is pursued. In this step, the animal is used as a sensor to gather evidence on the animals’ bio response to its environment and management by the farmer. The final step towards the management of the meat production is through the monitoring of emissions and resource efficiency. PLF-technology and continuous monitoring of animal bio responses will improve the understanding of the production process. This will allow the farmer to manage his process by exception. Production data collection and sharing will enhance the transparency throughout the production chain and help the consumer make educated decisions

Smart Energy Network Digital Twins: Findings from a UK-Based Demonstrator Project

Digital Twins promise to deliver a step-change in distribution system operations and planning, but there are few real-world examples that explore the challenges of combining imperfect model and measurement data, and then use these as the basis for subsequent analysis. In this work we propose a Digital Twin framework for electrical distribution systems and implement that framework on the Smart Energy Network Demonstrator microgrid in the UK. The data and software implementation are made available open-source, and consist of a network model, power meter measurements, and unbalanced power flow-based algorithms. Measurement and network uncertainties are shown to have a substantial impact on the quality of Digital Twin outputs. The potential benefits of a dynamic export limit and voltage control are estimated using the Digital Twin, using simulated measurements to address data quality challenges, with results showing curtailment for an exemplar day could be reduced by 56%. Power meter data and a network model are shown to be necessary for developing algorithms that enable decision-making that is robust to real-world uncertainties, with possibilities and challenges of Digital Twin development clearly demonstrated

Primary and secondary power control of multiterminal HVDC grids

Postprint (published version

Backup Protection Algorithm for Failures in Modular DC Circuit Breakers

Funding: 10.13039/100010661-Horizon 2020 Framework ProgrammePeer reviewedPostprin

How to increase cross border transmission capacity? A case study: Belgium.

Cross border capacity allows electric energy to be traded internationally. The electricity sector used to be vertically integrated and often state-owned. High voltage grids were generally developed within the borders of a country. Connecting different national high voltage grids was done to improve the security of the system and to accomodate for a few historical long term contracts. By doing so, the different systems could share their reserve generation capacity. Since the liberalization of the electricity sector, cross border capacity has gained a renewed interest as this can increase the competition in the market. This paper aims to give an overview of recent and planned investments which increase the cross border capacity of Belgium. Also we give an insight into the different technologies which can be used and their advantages and drawbacks are discussed.