Stochastic Operation Scheduling Model for a Swedish Prosumer with PV and BESS in Nordic Day-Ahead Electricity Market
Paper in proceedings, 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 profits.

Swedish balance settlement system.

Battery energy storage systems (BESS)

stochastic mixed-integer nonlinear optimization problem (SMINLP)

solar prosumer

Author

Christos Agathokleous

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Anh Tuan Le

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

David Steen

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

2019 IEEE Milan PowerTech, PowerTech 2019

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

Fossil Free Energy Districts (FED)

Region Västra Götaland, 2017-07-01 -- 2019-10-31.

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

Subject Categories

Transport Systems and Logistics

Control Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering

Areas of Advance

Energy

DOI

10.1109/PTC.2019.8810651

More information

Latest update

3/16/2020