Cost-benefit Analysis of the Selected National Cases : D4.3

Gómez, Inés and Riaño, Sandra and Madina, Carlos and Rossi, Marco and Kuusela, Pirkko and Koponen, Pekka and Aghaie, Hamid and Migliavacca, Gianluigi and Rivero, Enrique and Xu, Han and Kockar, Ivana (2019) Cost-benefit Analysis of the Selected National Cases : D4.3. [Report]

[img]
Preview
Text (Gomez-etal-SmartNet-2019-Cost-benefit-analysis-of-the-selected-national-cases)
Gomez_etal_SmartNet_2019_Cost_benefit_analysis_of_the_selected_national_cases.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial 4.0 logo

Download (15MB)| Preview

    Abstract

    The main objective of the SmartNet project is to provide optimised architectures for Transmission System Operator (TSO) – Distribution system operator (DSO) interaction [1][2]. Such optimisation must take into account the economic behaviour of each different coordination scheme (CS) and, thus, a costbenefit analysis (CBA) is of utmost importance. Since the main objective of this deliverable is the analysis of the CSs from an economic perspective, an exhaustive definition of these CSs has not been included in it. However, sections from 5.3.1 to 5.3.4 show a brief overview of their main characteristics. For a more detailed information on the CSs definition, please see SmartNet deliverable 1.3 [1]. The CBA is oriented to identify the impacts at system-level (also called “macro-level analysis”), since the aim of the economic assessment was to identify which CS provides more efficient results in each country. Additionally, coordination schemes must also allow the involved actors to have a profitable business case, that is, that costs and benefits are properly allocated among them, which required a business-level analysis (also called “micro-level analysis”). In order to carry out such CBA, an ad-hoc simulation platform was developed [3], where different scenarios were analysed for the three countries where SmartNet focuses: Italy, Denmark and Spain [4]. The flexibility market considered in the SmartNet project, which is called “Integrated Reserve Market”, is aimed at solving real-time imbalances and congestions between gate closure of intraday markets and real time until the opening of the next intraday market session [2], [3], [4], [5]. Its operation time is compatible with the timings of existing manual Frequency Restoration Reserve (mFRR) and Replacement Reserve (RR) markets [6], depending on the country. Although more details can be found in [2], for simplification purposes, the reader can understand that Integrated Reserve Market, SmartNet market, tertiary regulation market and mFRR market are the same kind of market. Likewise, automatic Frequency Restoration Reserve (aFRR) market can be assumed to be the same as secondary regulation market. The results obtained in the simulation environment were the core input for the CBA described in this report. However, these results required an appropriate methodology to be applied. In a first step, a review of the literature related to economic assessment methodologies was performed, with a view to select the metrics to be considered within the CBA described in this report. The CBA is an integral part of the long-term analysis performed for the three countries considered within SmartNet. In parallel to the development of the simulation software [3] and the definition of the 2030 scenarios [4], the most appropriate metrics were selected. Then, based on the results of simulations, which were also used for the laboratory tests [7], metrics were calculated and monetised to feed the system-wide CBA. The value chain was identified in parallel to the system-wide CBA, so that some guidelines on how to run a business-level CBA could also be extracted.