2021
DOI: 10.3390/en14144179
|View full text |Cite
|
Sign up to set email alerts
|

Technical Indicators for the Comparison of Power Network Development in Scenario Evaluations

Abstract: The problem of electric network expansion has different implications concerning the definition of criteria for the comparison of different candidate projects. Transmission expansion planning usually involves a set of economic and technical influences on market framework and on network operation over defined scenario evolutions, or even combining generation and transmission planning, although the application to real-sized networks usually implies cost-benefit analysis. In this paper, a methodology for performan… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
7
0

Year Published

2022
2022
2025
2025

Publication Types

Select...
5
3

Relationship

2
6

Authors

Journals

citations
Cited by 11 publications
(7 citation statements)
references
References 62 publications
0
7
0
Order By: Relevance
“…Today, the increase in the number of grid interconnection assumes an important role, because of the necessity to share as much as possible the generation resources and improving the system operation (e.g., in terms of losses reduction). The grid investments must be evaluated by considering more criteria, opening the possibility to introduce multi-criteria methods for ranking the potential investments (as in Dicorato et al [17], where a number of different candidate projects have been ranked with the use of Analytic Hierarchy Process). However, the increasing share of Variable Renewable Energy Sources (VRES), often installed at distribution system level, introduced the necessity to enlarge the system planning including both transmission and distribution systems, in particular when investments that are alternative to the network expansion are considered.…”
Section: Simulation Of Power Systems and Marketsmentioning
confidence: 99%
“…Today, the increase in the number of grid interconnection assumes an important role, because of the necessity to share as much as possible the generation resources and improving the system operation (e.g., in terms of losses reduction). The grid investments must be evaluated by considering more criteria, opening the possibility to introduce multi-criteria methods for ranking the potential investments (as in Dicorato et al [17], where a number of different candidate projects have been ranked with the use of Analytic Hierarchy Process). However, the increasing share of Variable Renewable Energy Sources (VRES), often installed at distribution system level, introduced the necessity to enlarge the system planning including both transmission and distribution systems, in particular when investments that are alternative to the network expansion are considered.…”
Section: Simulation Of Power Systems and Marketsmentioning
confidence: 99%
“…The first type of research mainly focuses on building a multi-dimensional evaluation index system and carrying out the ranking by assigning weight to quantify the score. Between the two types, the establishment of index weight system often adopts combination methods, also combining subjective weight and objective weight, including utilising improved analytic hierarchy process [2], fuzzy comprehensive evaluation method, entropy weight method [3], etc. However, the traditional index weight distribution is usually in the form of expert scoring or triangular fuzzy function.…”
Section: Introductionmentioning
confidence: 99%
“…However, the progressive penetration increase of RES requires network update to cope with the current power system issues. In particular, the influence of RES in electricity markets and transmission evolution planning has been developed in [11]- [12]. The lack of a suitable dataset to validate novel methods in several network conditions leads to the definition in [9] of the modified version of the IEEE 39-bus system with a one-year dataset of loads and RES.…”
Section: Introductionmentioning
confidence: 99%