A Novel Method for Evaluating the Resilience of Distribution Networks during Heat Waves

Abstract

This paper describes a methodology for the evaluation of the distribution networks resilience in large metropolitan areas during heat waves. These weather conditions (very hot and dry periods) in recent years have become more and more frequent due to climate changes. Thus, procedures to evaluate their impact on electricity networks assumed a particular interest. In the paper, a novel approach for the modeling of heat waves is presented and an example is provided based on a simple network in order to better highlight how the procedure works, the results obtained and the methodology potentials. A combination of three in-cascade models is used to evaluate the fault risk of each network component: a thermal, an aging and a reliability model. On the basis of the work described in this paper, a software tool has been implemented, used by the Italian DSO Areti SpA for evaluating the resilience of the distribution system of the Italian capital of Rome. 

A Tabu-search-based Algorithm for Distribution Network Restoration to Improve Reliability and Resiliency

“…A heat wave is a period of extremely hot weather, and climate change makes heat waves more intense and frequent, stressing underground cables. The increase of power demand, caused by massive and contemporary use of air conditioners, and a reduction of the heat transfer from cables to the soil, affect feeder's temperature [21]. Therefore, the weakest parts of the feeder chain, i.e., the electric power cable joints, experience an increasing number of failures [22].…”

Distribution Network Mixed-harmonic Separation Method Based on Characteristic Vector

“…The mixed vector coordinates and the module values of solution vectors are solved, and the relations among the module value sizes of solution vectors are analyzed. Accordingly, the calculation of such parameters as the work load rate, harmonic injection, and harmonic contribution of various harmonic sources and the calculation of mixed-harmonic separation in a distribution network can also be equivalent to gathering the harmonic characteristic vectors of the harmonic source and the distribution network's mixed harmonic in the aspect of harmonic analysis and separation [9][10][11] .…”

“…The characteristic vector of residents' live load harmonic is 1 [60.1, 0.2,9.6, 0.1, 7.7, 0.2, 4.2, 0.1, 2.1, 0, 1.5, 0, 0.8, 0.3, 0, 0.1] A  (10) The characteristic vector of converter harmonic is 2 [41.9, 0, 2.8, 0, 4.1, 0,3.9, 0,1.8, 0, 2.5, 0,1. 6, 0, 0.2, 0, 0.1] A  (11) The characteristic vector of electrical arc furnace steel harmonic is 3 [115.4, 4,9.9, 22.3, 7.1,10.6,3.5,5.1, 0.9, 2 .1, 0.5,1.0, 0.2, 0.6, 0, 0.2, 0, 0.2] A  (12) The characteristic vector of single-crystal silicon growth furnace harmonic is 4 [72.5, 0, 6.8, 0, 4.9, 0,3.9, 0,1.7, 0,16.4, 0,1 4.4, 0, 0. We obtained harmonic source amplitude matrix Aas follows: 60.1 0.2 9.6 0.1 7.7 0.2 4.2 0.1 2.1 0 1.5 0 0.8 0 0.3 0 0.1 41.9 0 2.8 0 4.1 0 3.9 0 1.8 0 2.5 0 1.6 0 0.2 0 0.1 115.4 9.9 22.3 7.1 10.6 3.5 5.1 0.9 2.1 0.5 1.0 0.2 0.6 0 0.2 0 0.2 72.5 0 6.8 0 4.9 0 3.9 0 1.7 0 16.4 0 14.4 0 0.3 0 0.2…”

Intentional Islanding of Active Distribution Networks by GenSets: An Analysis of Technical Constraints and Opportunities

“…Moreover, in some countries, additional measures have been taken to deal with exceptional events, like those caused by large weather accidents: snowfalls, waterfoods, and windstorms. In Italy, for example, the DSOs must prepare a three-year horizon plan (so-called resilience plan) and send it to ARERA, the national energy regulatory authority, for approval [5,6]. Tis plan must include a set of actions selected by the DSO to contain the risk of power outages against the main critical factors that may impact the distribution network.…”