The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed to minimize the electricity procurement cost. The local energy system may refer either to a small industrial site or to a residential neighborhood. Two mixed integer linear programming models are adopted, each for a different representation of the battery: A simple energy balance constraint and the Kinetic Battery Model. The paper describes the generation of the scenarios, the construction of the scenario tree and the intraday decision-making procedure based on the solution of the multistage stochastic programming. Moreover, the daily energy procurement costs calculated by using the stochastic programming approach are compared with those calculated by using the Monte Carlo method. The comparison is repeated for two different sizes of the battery and for two load profiles.
Comparison between Multistage Stochastic Optimization Programming and Monte Carlo Simulations for the Operation of Local Energy Systems / Orozco, C.; Borghetti, A.; Lilla, S.; Pulazza, G.; Tossani, F.. - ELETTRONICO. - (2018), pp. 8494563.1-8494563.6. (Intervento presentato al convegno 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 tenutosi a Campus of the University of Palermo, Complesso Didattico, Building 19, ita nel 12-15 June 2018) [10.1109/EEEIC.2018.8494563].
Comparison between Multistage Stochastic Optimization Programming and Monte Carlo Simulations for the Operation of Local Energy Systems
OROZCO CORREDOR, CAMILO;Borghetti, A.;LILLA, STEFANO;PULAZZA, GIORGIA;Tossani, F.
2018
Abstract
The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed to minimize the electricity procurement cost. The local energy system may refer either to a small industrial site or to a residential neighborhood. Two mixed integer linear programming models are adopted, each for a different representation of the battery: A simple energy balance constraint and the Kinetic Battery Model. The paper describes the generation of the scenarios, the construction of the scenario tree and the intraday decision-making procedure based on the solution of the multistage stochastic programming. Moreover, the daily energy procurement costs calculated by using the stochastic programming approach are compared with those calculated by using the Monte Carlo method. The comparison is repeated for two different sizes of the battery and for two load profiles.| File | Dimensione | Formato | |
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