ARTICLE / MAKALE erational risk management. The shift is not yet complete be cause the standard formulation of planning and scheduling problems remains deterministic. it is implicitly assumed that the process is free from any disturbance and- consequentlythat future evolution can be predicted precisely. in practice, however, this strict assumption does not usually hold- sometimes deviations are considerable. Where does this uncer tainty come from? The performance of a production system is influenced not only by its controlled (hence: certain) variables, but also by unmeasurable (hence: uncertain) perturbations such as changes in machine condition, or input product qual ity. Another example of uncertain disturbance is related to demand forecasts, which trigger the production plans. Two examples are considered below: Cement production: Major decision problems comprise opti mizing kiln fuel combustion and scheduling production of different cement grades on different milis. Uncertainty affects demand, outages, process parameters, and production costs. Power generation: The principle decisions include: schedul ing unit commitment, selling electricity , bidding on the spot u Production of Process A Unit 1 Q) �•n�ırr 1 °0 1 ° 1 •oha! 1 Q) � �v ı n:ı'. u�� PtH �� !�I g o 20 40 60 80 100 120 140 160 u Productiori of Process A Unit 2 � � IA 1 n 1 jR ı� 1 � 1 1 /\ Q) }\ E ı ı H g o 20 40 60 80 100 120 140 160 0 Production of Process B Unit 1 i l��tıftfıfmrrf�ı□qj j O 20 40 60 80 100 120 140 160 Time (h) i � i..!.iE�'[Ti} LdJ et O 20 40 60 80 100 120 140 160 Delivered product (Demand) 1 :� EUıı:ı:ı:JiLI � O 20 40 60 80 100 120 140 160 Time (h) market, and planning maintenance. Uncertainty is present in demand (load), future spot price, fuel price, and outages. Eff i cient optimization solutions explicitly taking uncertainty into account are therefore needed. Economical versus ecological impact What role do environmental aspects play in econometric opti mization? At a first glance, economic objectives often seem at odds with ecological ones. This is not necessarily the case: in fact, the problem of optimally allocating limited resources is, by definition, economics. Moreover, the meaning of "optimality" is strongly influenced by legislation. 1 shows that the environmental factor is an element which can impact the overall econometric measure. A somewhat speculative though legitimate question is thus: To what extent can the proposed approach contribute to sustainability? Again the examples of cement production and of power gen eration are considered. in the former, a typical planı consumes about 70 kg of coal to produce one tonne of cement. This process creates approximately 175 kg 2) of carbon dioxide (COJ Now if the cement kiln is operated with an optimized combustion strategy (eg, mixing with alternative fuels) leading to a 3% reduction in coal tor a planı producing 350 tonnes of cement per hour, the corresponding reduction in CO 2 amounts to 1 6,000 tonnes/year. Applied to global cement production (1 .8x109 tonnes/year ), the theoretical reduction reaches 1 O million tonnes of CO2 per year. A standard gas turbine plant (thermal efficiency: 35%) neces sitates about 220 kg of natura! gas to generale one MWh of electrical energy. Combustion of the fuel creates almost 600 kg of carbon dioxide. it is reasonable to assume that a 1 % reduction in fuel consumption is achievable through optimized operation/maintenance. For a planı with an average power of 100 MW, the yearly reduction in CO2 corresponds to 5,200 tonnes. By extension to ali gas turbines (worldwide: 4.5 x1012 kWh/ year (3), the CO 2 savings would be higher than 25 mil lion tonnes per year. An economic quantification of environmental impact, eg, through emission rights dynamically traded on a market, would further increase the weight of the ecological cost component in the overall asset optimization. lf one tonne of CO 2 is traded say at a price of $10, then the value of the CO 2 saved by the 100 MW power planı would reach $50.000 per year. For the 350 tonne cement plant, the emission value saved each year would be $160.000. in addition, savings achieved from reduced fuel costs would be several times bigger. Conslusion üne major goal of an industrial owner is to secure and con solidat � the profitability of its assets. The ability to allocate limited resources dynamically in an optimal way is crucial. Therefore ABB customers will increasingly need solutions that help them to control and optimize their production processes while hedging their decisions against uncertainty. Together with the expertise of ETH Zurich, ABB's technology has en tered a new phase: true optimization of production and operational risk management are now much closer. t 1 ENERJİ & KOJENERASYON DÜNYASI . EKiM 2005 ♦ 6 - -O -+:::..:::.:..::::.:..::..:: ::::.::.:: ::.:::.:..=.:.::::=::::.::=----' ==========- "AB'ye Giriş Sürecinde Türkiye'de Kojenerasyon-Yeni Gelişmeler"
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