Poly-Generation Planning: Useful Lessons from Models and Decision Support Tools

Introduction

Energy is a vital input for social and economic development of any nation. Nowadays, several innovations have been driven by fast evolution of the technologies in the energy sector. Increasing environmental concerns and the trends towards deregulation of energy markets have become an integral part of energy policy planning. Consequently, the requirement for environmentally sound energy production technologies has gained much ground in the energy business. Poly-generation has been gradually accepted as one of the most efficient and economical ways of producing energy commodities in the future. Poly-generation means that two or more energy commodities (e.g. electricity, heat, cooling, hydrogen or other chemical products) are generated simultaneously in a single integrated production process. It is a leading technology responding to competitive and economic pressures to cut expenses, to increase efficient use of energy, and to reduce emissions of air pollutants and greenhouse gases. Combined heat and power (CHP, also called cogeneration) has been a proven and reliable technology with a history of more than 100 years. Thomas (1994) stated that CHP is a global solution to voltage dip, pollution and energy efficiency. Combined cooling, heating and power (CCHP), or tri-generation, is booming. Tri-generation is directly derived from CHP by making use of the low-value waste heat energy in the process to produce high-value cooling energy. Cogeneration and tri-generation have found wide applications in district heating, large buildings and different industries such as paper, wood, food and semiconductors (Chicco & Mancarella, 2007). The concept of poly-generation can be derived from the concept of tri-generation, as referred to the production of electric power, cooling and heat, with two latter ones in case available at different enthalpy (temperature/pressure) levels. Furthermore, poly-generation can encompass the provision of additional outputs such as hydrogen, dehumidification, or other chemical substances used in the specific process (Chicco & Mancarella).

The energy sector is one of the core application areas in operations research, decision science and artificial intelligent techniques due to the fact the energy systems require large investments and are technologically challenging to implement. However, in contrast to the well-established planning and decision support tools for power-only generation systems, the tools for poly-generation systems are scant because poly-generation planning is inherently more complicated than power-only generation planning. The interdependence between the generation of different energy commodities in poly-generation plants imposes great challenge in planning. In a poly-generation plant, generation of different energy commodities follows a joint characteristic, which means that planning must be done in coordination among different energy commodities. A survey of the relevant publications on scientific journals in the last years (2001-2007) shows that the largest part of these publications is still related to cogeneration. However, the number of research papers related to poly-generation concepts and applications has been increasing lately. Onovwiona and Ugursal (2006) reviewed the current technology used for residential cogeneration systems. Salgado and Pedrero (2008) collected the literature for the short-term operational planning on cogeneration systems from 1983 to 2006. But this survey did not include the literature for tri-generation and poly-generation (more than three energy commodities) planning. In addition, the survey did not cover the literature for decision analysis, long-term planning and strategic decision. Huang, Poh and Ang (1995) and Zhou, Ang and Poh (2006) reviewed the decision analysis in energy and environmental modeling in general but without focus on cogeneration, tri-generation or poly-generation. Pohekar and Ramachandran (2004) reviewed the application of multi-criteria decision making (MCDM) to energy planning in general. Jebaraj and Iniyan (2006) reviewed comprehensive energy modeling at macro and national levels in general. Hiremath, Shikha and Ravindranath (2007) focused on decentralized energy planning in general. Metaxiotis and Kagiannas (2005) reviewed the application of intelligent techniques in the energy sector in general. Wu and Wang (2006) reviewed technology development for tri-generation and Chicco and Mancarella (2007) reviewed the application of cogeneration, tri-generation and poly-generation systems.