Optimization of district heating production with thermal storage using mixed-integer nonlinear programming with a new initialization approach

• Published in: Energy Informatics 2021-09, Vol.4 (Suppl 2), p.1-17, Article 34
• Main Authors: Bjørnskov, Jakob, Mortensen, Lasse Kappel, Filonenko, Konstantin, Shaker, Hamid Reza, Jradi, Muhyiddine, Veje, Christian
• Format: Article
• Language: English
• Subjects: Cogeneration; Computer Science; Convex analysis; Convexity; District heating; District heating scheduling; Heat storage; Heating; Information Systems and Communication Service; Initialization; MINLP; Mixed integer; Mixed integer non-linear optimization; Modeling; Monte Carlo simulation; Nonlinear programming; Operating costs; Optimization; Production planning; Production scheduling; Thermal storage; Tree search; Windows (intervals)
• ISSN: 2520-8942; 2520-8942
• DOI: 10.1186/s42162-021-00150-y

Non-convex scheduling of energy production allows for more complex models that better describe the physical nature of the energy production system. Solutions to non-convex optimization problems can only be guaranteed to be local optima. For this reason, there is a need for methodologies that consistently provide low-cost solutions to the non-convex optimal scheduling problem. In this study, a novel Monte Carlo Tree Search initialization method for branch and bound solvers is proposed for the production planning of a combined heat and power unit with thermal heat storage in a district heating system. The optimization problem is formulated as a non-convex mixed-integer program, which is incorporated in a sliding time window framework. Here, the proposed initialization method offers lower-cost production planning compared to random initialization for larger time windows. For the test case, the proposed method lowers the yearly operational cost by more than 2,000,000 DKK per year. The method is one step in the direction of more reliable non-convex optimization that allows for more complex models of energy systems.