Under the increasing penetration of distributed energy resources and new smart network technologies, distribution utilities face new challenges and opportunities to ensure reliable operations, manage service quality, and reduce operational and investment costs. Simultaneously, the research community is developing algorithms for advanced controls and distribution automation that can help to address some of these challenges. However, there is a shortage of realistic test systems that are publically available for development, testing, and evaluation of such new algorithms. Concerns around revealing critical infrastructure details and customer privacy have severely limited the number of actual networks published and that are available for testing. In recent decades, several distribution test feeders and US-featured representative networks have been published, but the scale, complexity, and control data vary widely. This paper presents a first-of-a-kind structured literature review of published distribution test networks with a special emphasis on classifying their main characteristics and identifying the types of studies for which they have been used. This both aids researchers in choosing suitable test networks for their needs and highlights the opportunities and directions for further test system development. In particular, we highlight the need for building large-scale synthetic networks to overcome the identified drawbacks of current distribution test feeders.

Rapid increases in distributed energy resources on distribution systems are prompting research efforts to improve and evaluate electric power distribution algorithms; however, there is a shortage of realistic, large-scale, U.S.-style test systems for the evaluation of such advanced algorithms. Some available tools to build large-scale test systems are of European style, and their application to studies focused on the United States might not be desirable given very different characteristics between the European and U.S. distribution designs. Motivated by this need, this paper develops detailed algorithms to build large-scale U.S. distribution systems and incorporates them in a new Reference Network Model, RNM-US. The approach starts with information from street maps and a catalog with electric equipment that includes power lines, transformers, voltage regulators, capacitors, and switching devices. The paper presents the algorithms through an illustrative case study of the different steps that comprise the process of building a synthetic distribution grid. Finally, the paper presents a medium-and a large-scale data set covering 10 million electrical nodes and 120,000 km of power lines, demonstrating the applicability of the proposed method to build very large-scale synthetic distribution systems.

This article proposes a predictive traffic regulation model for metro loop lines on the basis of the optimization of a cost function along a time horizon. The regulation strategies typically compensate timetable and headway deviations modifying the train run times. The existing optimization methods are based on simplified traffic models with analytical solutions or based on more realistic models (usually non-linear) that have real-time computational limitations. A quadratic programming model is proposed here, suitable to include in an efficient way the main operation constraints: minimum interval, limits in the control actions, and the typical operation criterion of preventing the actuation of signalling systems between platforms. Efficiency is measured by the computing time required to solve long-term predictive models with standard optimization tools. Long-term prediction improves regulation performance and stability and simplifies the tuning of regulation parameters according to the operation requirements. The use of standard optimization tools improves the implementation of the proposed regulator and its maintainability. Although the proposed method is valid for both timetable and headway operation, the analysis in the article is focused on headway operation. In this case, it is possible to observe the offered commercial speed and to adjust the quality criteria that will measure the performance of the headway operation.

In many parts of the world, access to basic electricity services remains a significant challenge. The status quo mode of electrification is central grid extension; however, in many areas, off-grid (OG) technologies like minigrids (MGs) and standalone (SA) systems are more suitable for promoting electricity access under cost constraints. Unfortunately, these opportunities are often overlooked due to the complexities of electrification planning, especially for large areas. Researchers have designed technoeconomic planning tools that can be scaled to cut through aspects of this complexity and be fit to address different places and contexts. This paper describes a computer-based optimization model--named the reference electrification model (REM)--which performs automatic electrification planning and is able to identify lowest cost system designs to most effectively provide desired levels of electricity access to populations of any given size. In doing so, REM determines the most suitable modes of electrification for each individual consumer by specifying whether customers should be electrified via grid extension, OG MGs, or SA systems. For each system, REM supplies detailed technical designs at the individual customer level. We have used this model in real planning activities in sub-Saharan Africa and South Asia. The description of REM's capabilities is supported by case examples. REM stands apart from other electrification planning models because of its high granularity and its capability to provide concrete plans for a wide range of geographical scales. Because of these benefits, REM has the potential to help rationalize electrification planning and expedite progress toward universal electricity access worldwide.