Combined Heat and Power (CHP) is a highly fuel-efficient energy technology, which puts to use waste heat produced as a by-product of the electricity generation process. CHP can increase the overall efficiency of fuel utilization to more than 75% Gross Calorific Value – compared with around 40% achieved by fossil fuel electricity generation plants in operation today, and up to 50% from modern Combined Cycle Gas Turbines – and has the potential to save substantially on energy bills. CHP is the simultaneous generation of usable heat and power (usually electricity) in a single process. Most new CHP schemes use natural gas, but a significant proportion burn alternative, renewable fuels and some, such as those bio-fuels that are suitable for use, qualify for additional support (e.g. under the Renewable Obligation). CHP is not only more efficient through utilization of heat, but it also avoids transmission and distribution losses and can provide important network services such as “black start”, improvements to power quality, and the ability to operate in “island mode” if the distribution network goes down.
Published in Chapter:
Artificial Immune System in the Management of Complex Small Scale Cogeneration Systems
Fabio Freschi (Politecnico di Torino, Italy) and Maurizio Repetto (Politecnico di Torino, Italy)
Copyright: © 2009
|Pages: 18
DOI: 10.4018/978-1-60566-310-4.ch007
Abstract
The increasing cost of energy and the introduction of micro-generation facilities and the changes in energy production systems require new strategies to reach their optimal exploitation. Artificial Immune System (AIS) metaphor can be used to reach this aim. In this kind of management, the energy system can be seen as a living body which must react to external stimuli (cost of fuel, energy prices, fares, etc.) fulfilling its internal requirements (user loads, technical constraints, etc.). In this chapter, a developed procedure based on AIS is described and applied to this problem. Its performance is compared with the mixed integer linear programming on the same test. The result shows that AIS based method obtained better results, in terms of computational efficiency, compared with classical energy production management procedures based on Mixed Integer Linear Programming.