Hyppää sisältöön
    • Suomeksi
    • På svenska
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • LUTPub
  • Tieteelliset julkaisut
  • Näytä aineisto
  •   Etusivu
  • LUTPub
  • Tieteelliset julkaisut
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

Decentralized cooperative scheduling of prosumer flexibility under forecast uncertainties

Mashlakov, Aleksei; Pournaras, Evangelos; Nardelli, Pedro H.J.; Honkapuro, Samuli (2021-03-10)

Katso/Avaa
mashlakov_et_al_decentralized_cooperative_published_version.pdf (2.159Mb)
Lataukset: 


Publishers version

Mashlakov, Aleksei
Pournaras, Evangelos
Nardelli, Pedro H.J.
Honkapuro, Samuli
10.03.2021

Applied Energy

290

Elsevier

School of Energy Systems

https://doi.org/10.1016/j.apenergy.2021.116706
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi-fe202103127227

Tiivistelmä

Scheduling of prosumer flexibility is challenging in finding an optimal allocation of energy resources for heterogeneous prosumer goals under various forecast uncertainties and operation constraints. This study addresses this challenge by introducing a bottom-up framework for cooperative flexibility scheduling that relies on a decentralized network of scheduling agents to perform a coordinated decision-making and select subset of households’ net load schedules that fulfills the techno-socio-economic prosumer objectives in the resource operation modes and ensures the reliability of the grid. The resource flexibility in terms of alternative operation schedules is mathematically modeled with multiobjective optimization that attains economic, environmental, and energy self-sufficiency prosumer goals with respect to their relative importance. The coordination is achieved with a privacy-preserving collective learning algorithm that aims to reduce the aggregated peak demand of the households considering prosumers’ willingness to cooperate and accept a less preferred resource schedule. By utilizing the framework and real-world data, the novel case study is demonstrated for prosumers equipped with solar battery systems in a community microgrid. The findings show that the flexibility scheduling with an optimal prosumer cooperation level decreases the global costs of collective peak shaving by 83% while increasing the local prosumer costs by 28% in comparison with noncooperative scheduling. However, the forecast uncertainty in net load and parameters of the frequency containment reserve causes imbalances in the planned schedules. It is suggested that the imbalances can be decreased if the flexibility modeling takes into account variable specific levels of forecast uncertainty.

Lähdeviite

Mashlakov, A., Pournaras, E., Nardelli, P.H.J., Honkapuro, S. (2021). Decentralized cooperative scheduling of prosumer flexibility under forecast uncertainties. Applied Energy, vol. 290. DOI: 10.1016/j.apenergy.2021.116706

Kokoelmat
  • Tieteelliset julkaisut [783]
LUT-yliopisto
PL 20
53851 Lappeenranta
Ota yhteyttä | Lähetä palautetta | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

JulkaisuajatTekijätNimekkeetKoulutusohjelmaAvainsanatSyöttöajatYhteisöt ja kokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy
LUT-yliopisto
PL 20
53851 Lappeenranta
Ota yhteyttä | Lähetä palautetta | Tietosuoja | Saavutettavuusseloste