The Key Role of the Vector Optimization Algorithm and Robust Design Approach for the Design of Polygeneration Systems

Abstract

In recent decades, growing concerns about global warming and climate change effects have led to specific directives, especially in Europe, promoting the use of primary energy-saving techniques and renewable energy systems. The increasingly stringent requirements for carbon dioxide reduction have led to a more widespread adoption of distributed energy systems. In particular, besides renewable energy systems for power generation, one of the most effective techniques used to face the energy-saving challenges has been the adoption of polygeneration plants for combined heating, cooling, and electricity generation. This technique offers the possibility to achieve a considerable enhancement in energy and cost savings as well as a simultaneous reduction of greenhouse gas emissions. However, the use of small-scale polygeneration systems does not ensure the achievement of mandatory, but sometimes conflicting, aims without the proper sizing and operation of the plant. This paper is focused on a methodology based on vector optimization algorithms and developed by the authors for the identification of optimal polygeneration plant solutions. To this aim, a specific calculation algorithm for the study of cogeneration systems has also been developed. This paper provides, after a detailed description of the proposed methodology, some specific applications to the study of combined heat and power (CHP) and organic Rankine cycle (ORC) plants, thus highlighting the potential of the proposed techniques and the main results achieved.

Keywords

• vector optimization
• evolutionary genetic algorithm
• robust design optimization
• combined heat and power
• ORC systems