Optimising block bids of district heating operators to the day-ahead electricity market using stochastic programming
نویسندگان
چکیده
The wide spread of district heating in Denmark offers a massive potential for flexibility an energy system with intermittent renewable production. To leverage this potential, cost-efficient power market integration combined heat and (CHP) units systems is important. We propose stochastic program optimising block bids to the day-ahead CHP under uncertain prices. Block allow internalisation start-up costs. Based on program, we develop solution approach based sample average approximation (SAA) solve large number price scenarios. present results case study from Middelfart, Denmark. consists two sub-networks that have lately been connected. analyse bidding behaviour without connection using real data different seasons. show varies significantly depending seasons layout network. Furthermore, SAA reduces computation time while maintaining quality. • Two-stage optimal heat-and-power production •Power uncertainty leads problem •Efficient Sample Average Approximation •Analysis Danish out-of-sample performance proposed methods
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A Stochastic Programming Model for a Day-Ahead Electricity Market: a Heuristic Methodology and Pricing
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ژورنال
عنوان ژورنال: Smart energy
سال: 2021
ISSN: ['2666-9552']
DOI: https://doi.org/10.1016/j.segy.2021.100004