Reliability Evaluation in Distribution Networks with Microgrids: Review and Classification of the Literature

Abstract

Modern power systems must provide efficient, reliable, and environmentally responsible energy. Recently, the inclusion of Microgrids (MGs) has allowed us to overcome some difficulties and face important challenges in this direction, especially related to the use of alternative energy sources. Increased and probabilistic demand, as well as limited energy supply, pose the need to evaluate the reliability of any distribution system (DS) when MGs are introduced. Here we reviewed and classified the state-of-the-art of reliability assessment (RA) in MGs. Initially, we contextualize RA in distribution systems. Next, each of the MGs subsystems components are introduced and the questions (1) why is it important to evaluate the reliability in Microgrids? (2) how do Microgrids influence the reliability of distribution systems? and (3) how does each of its subsystems influence the reliability of the Microgrids? are addressed. A total of 1395 research studies were published between 2002 and 2020. Using the PRISMA model, 147 met the inclusion criteria (71% correspond to research papers and 29% to reviews; 62% were published in journals, 34% were conference papers and 4% were books). The first study dates from 1971. Despite immense advances in MGs, we identified that (1) real test systems constitute an emerging trend; (2) although new MG configurations sound promising, the development and application of new RA techniques are a necessary step towards the identification of potential pitfalls of such architectures; (3) new RA methods or variations of the existing ones, whether analytical or simulation-based, are constantly being proposed, but their comparison for a particular DS, including MGs, are yet to be performed; and (4) more research studies are needed to assess how new control strategies and information and communications technology impact MGs reliability. Future lines of research could build upon these gaps to enhance reliability, especially when alternative energy resources are available.

Evaluation of service quality of distribution systems with critically located generators

“…The same structure is used to present ENS values, showing an increase of more than 2 MW, in case type 2, with four DG capacity steps, compared to the case without DG. According to Figure 6, case type 1, with a single DG step added, presents the best network quality of service results, reinforcing what had already been studied by other authors, with the objectives of achieving good reliability indices, reducing losses, and maximizing the use of clean energy circulating throughout the distribution network 1,6,15,27,41,42 …”

“…The mean time to repair (MTTR) is the average or expected repair time, which represents the number of hours required for a given component to be repaired after the occurrence of a fault 25 . To obtain these reliability indices at each load point, Equations (1)–(3) are used, based on Table 2 data 1,26,27 where λ i and λ k are the failure rates of component i and load point k , and r i and r k are the average failure durations of components i and load point k , respectively.…”

“…On the other hand, Monte Carlo simulations can provide a probabilistic approach to the same objective by generating a chronological sequence of random events, thus building the history of each component over a given period. It can create a significant sample of system behavior for several years 7,27,30 …”

“…To simulate these times in hours, a uniform distribution function is used, which can be further used to draw the time and durations of each state and generate random values in the range [0, 1]. The time to failure of a given component i is given by (9) and the time to repair is given by (10) 8,27,31 where R i is a random number ranging between 0 and 1, λ i is the failure rate of component i , and MTTR i is the mean time to repair of component i .…”

Advanced Metering Infrastructure—Towards a Reliable Network

“…Many of the current works focus on issues related to the integration of SM with building integrated photovoltaic in various climatic and environmental conditions [21,22] or to remote monitoring of the operation of a rural network [19]. Much importance is placed in the literature on research on the cooperation of the AMI with microgrids [23] but also on their operation in large rural/urban areas [24].…”