Blackout risk mitigation by using medium size gas turbines. (1st April 2018)

• Record Type: Journal Article
• Authors: Canca, David; Arcos-Vargas, Ángel; Núñez, Fernando
• Is Part Of: Energy. Volume 148(2018)
• Page Start: 32
• Page End: 48
• Publication Date: 2018-04-01
• Subjects: Distribution network -- Power at risk -- Distributed generation -- Electricity and gas market -- Mixed integer linear programming; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.01.113
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper aims to analyze the economic aspects of the network power at risk mitigation by using gas turbine distributed generation. Two different Mixed-Integer Programming optimization models are proposed with the goal of selecting both, the most appropriate turbine models and the year of installation. The first model considers the existence of a global network agreement among generation companies and distributor in order to cover at least partially all the points at risk. The second one leaves the distributed generators full freedom to choose among the locations proposed by the distributor. Since electricity distribution is a regulated activity and manages public resources, one of the decisions that must be taken is how much the generators should be economically encouraged to install the appropriate generation power at the points at risk. To this end, a possible regulated remuneration that compensates for the power installation at certain points is considered. The proposed approach is illustrated by applying both models in a big scenario concerning approximately the half of the Spanish distribution network. A sensitivity analysis considering different values of remuneration and gas price is carried out. The analysis demonstrates the importance of gas price in order to apply the distributed generation mechanism. Highlights: Power at risk mitigation using gas turbine generation is studied. Two planning optimization models are proposed under two kind of agreements. The first one considers the obligation of generators to cover all points at risk. The second one gives them full freedom in choosing place and power to install. The use of a regulated remuneration to generators as an incentive is studied.