4.7 Article

Stochastic network-constrained co-optimization of energy and reserve products in renewable energy integrated power and gas networks with energy storage system

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 223, Issue -, Pages 747-758

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.03.021

Keywords

Day-ahead market clearing; Natural gas transmission system; Compressed air energy storage; Wind energy sources; Two stage stochastic programming

Funding

  1. FEDER funds through COMPETE 2020
  2. Portuguese funds through FCT [SAICT-PAC/0004/2015 (POCI-01-0145-FEDER-016434), 02/SAICT/2017 (POCI-01-0145-FEDER-029803), UID/EEA/50014/2019 (POCI-01-0145-FEDER-006961)]

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Increasing penetration of variable nature wind energy sources (WES) due to environmental issues, impose several technical challenges to power system operation as it is difficult to predict its output power because of wind intermittency. Power generation based on gas turbine with fast starting fitness and high ramping could better deal with inherent uncertainties comparing to other power generation sources. Considering natural gas network constraints impacts flexibility and participation of gas-fueled generation units on reserve and energy markets. Hence, the use of flexible energy storage system can reduce renewable sources alternation and the gas network limitation effects on power system operation cost. This paper proposes a two-stage stochastic network-constrained unit commitment based market clearing model for energy and reserve products in coordinated power and gas networks with the integration of compressed air energy storage (CAES) and WES. A six-bus electric system with a six-node gas system and IEEE reliability test system (RTS) 24-bus electric system with a ten-node gas network are considered to perform numerical tests and demonstrate the performance of the proposed model. The effect of including the constraints of the gas system on the power system operation cost in day-ahead co-optimization of energy and reserve products is evaluated using numerical studies. Also, including CAES reduces the power system operation cost, load shedding and wind spillage. Crown Copyright (C) 2019 Published by Elsevier Ltd. All rights reserved.

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