A Heuristic Algorithm for Combined Heat and Power System Operation Management

Energies

Roberto Saraceno¹  Seshadhri Srinivasan²  Carmine Mongiello³  Davide Liuzza⁴  Muhammad Faisal Shehzad⁵  Valerio Mariani⁵  Luigi Glielmo⁵  Mainak Dan⁶ 

[1] AtenaTech srl, 00044 Frascati,Rome, Italy;Berkeley Education Alliance for Research in Singapore, Singapore 138602, Singapore;ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development), Energy Technologies and Renewable Sources Department, 80055Portici, Italy;ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development), Fusion and Technology for Nuclear Safety and Security Department, 00044 Frascati,Rome, Italy;Group for Research on Automatic Control Engineering, Department ofEngineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy;Interdisciplinary Graduate Programme, Nanyang Technological University Computational Intelligence Laboratory, Blk N4, B1a-02,Singapore 639798, Singapore;

关键词: combined heat and power;    co-generation;    energy storage system;    energy management;    heuristics;    genetic algorithm;   

DOI  :  10.3390/en14061588

来源: DOAJ

【 摘 要 】

This paper presents a computationally efficient novel heuristic approach for solving the combined heat and power economic dispatch (CHP-ED) problem in residential buildings considering component interconnections. The proposed solution is meant as a substitute for the cutting-edge approaches, such as model predictive control, where the problem is a mixed-integer nonlinear program (MINLP), known to be computationally-intensive, and therefore requiring specialized hardware and sophisticated solvers, not suited for residential use. The proposed heuristic algorithm targets simple embedded hardware with limited computation and memory and, taking as inputs the hourly thermal and electrical demand estimated from daily load profiles, computes a dispatch of the energy vectors including the CHP. The main idea of the heuristic is to have a procedure that initially decomposes the three energy vectors’ requests: electrical, thermal, and hot water. Then, the latter are later combined and dispatched considering interconnection and operational constraints. The proposed algorithm is illustrated using series of simulations on a residential pilot with a nano-cogenerator unit and shows around 25–30% energy savings when compared with a meta-heuristic genetic algorithm approach.

【 授权许可】

Unknown