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A platform for research: civil engineering, architecture and urbanism
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation
A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lineslocations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems. ; This work has received funding from the EU's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO); from FEDER Funds through COMPETE program; from National Funds through FCT under the project UID/EEA/00760/2019 and from the project PTDC/EEI-EEE/28983/2017 - CENERGETIC. Bruno Canizes is supported by FCT Funds through SFRH/BD/110678/2015 PhD scholarship.
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation
A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lineslocations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems. ; This work has received funding from the EU's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO); from FEDER Funds through COMPETE program; from National Funds through FCT under the project UID/EEA/00760/2019 and from the project PTDC/EEI-EEE/28983/2017 - CENERGETIC. Bruno Canizes is supported by FCT Funds through SFRH/BD/110678/2015 PhD scholarship.
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation
Bruno Canizes (author) / João Soares (author) / Fernando Lezama (author) / Cátia Silva (author) / Zita Vale (author) / Juan M. Corchado (author)
2019-02-06
oai:zenodo.org:3066002
Renewable Energy 138
Article (Journal)
Electronic Resource
English
DDC:
690
| American Institute of Physics | 2020