Stochastic Operation Scheduling Model for a Swedish Prosumer with PV and BESS in Nordic Day-Ahead Electricity Market
Paper i proceeding, 2019

In this paper, an optimal stochastic operation
scheduling model is proposed for a prosumer owning
photovoltaic (PV) facility coupled with a Battery Energy
Storage System (BESS). The objective of the model is to
maximize the prosumer’s expected profits. A two-stage
stochastic mixed-integer nonlinear optimization (SMINLP)
approach is used to cope with the parameters’ uncertainties.
Artificial Neural Networks (ANN) are used to forecast the
markets’ prices and the standard scenario reduction
algorithms are applied to handle the computational
tractability of the problem. The model is applied to a case
study using data from the Nordic electricity markets and
historical PV production data from the Chalmers University
of Technology campus, considering a scaled up 5MWp power
capacity. The results show that the proposed approach could
increase the revenue for the prosumer by up to 11.6% as
compared to the case without any strategy. Furthermore, the
sensitivity analysis of BESS’s size on the expected profit shows
that increasing BESS size could lead to an increase in the net

Swedish balance settlement system.

solar prosumer

Battery energy storage systems (BESS)

stochastic mixed-integer nonlinear optimization problem (SMINLP)


Christos Agathokleous

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

Anh Tuan Le

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

David Steen

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

13th IEEE PES PowerTech Conference 23-27 June 2019
Milano, ,

Fossil Free Energy Districts (FED)

European Commission, 2016-11-01 -- 2019-10-31.


Transportteknik och logistik


Annan elektroteknik och elektronik



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