Stochastic network-constrained co-optimization of energy and reserve products in renewable energy integrated power and gas networks with energy storage system
Mirzaei, Mohammad Amin; Yazdankhah, Ahmad Sadeghi; Mohammadi-ivatloo, Behnam; Marzband, Mousa; Shafie-khah, Miadreza; Catalão, João P. S. (2019-06-20)
Mirzaei, Mohammad Amin
Yazdankhah, Ahmad Sadeghi
Mohammadi-ivatloo, Behnam
Marzband, Mousa
Shafie-khah, Miadreza
Catalão, João P. S.
Elsevier
20.06.2019
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2019102334353
https://urn.fi/URN:NBN:fi-fe2019102334353
Kuvaus
vertaisarvioitu
Tiivistelmä
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.
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