A detailed approach for modeling the steam consumption in a multipurpose chemical batch plant was developed, tested, and used for analysis of the energy-efficiency. The main advantage of the approach presented in this paper compared to available modeling approaches is the ability to describe the transient steam consumption. Thus, the new approach can be used for the dynamic optimization of batch operations with respect to the energy efficiency. The bottom-up method was implemented by modeling particular unit operations (UOs) in a case study plant, and validation was accomplished with direct measurements on both UO and building level. The principle of the bottom-up model is a detailed energy balance of each particular UO for which process parameter measurements are necessary as input data. These were extracted from the measurements archive of the case study plant for a period of two months. Process data from almost 1000 sensors installed in ca. 100 UOs were acquired, transformed into a time-series with common time basis, and used as an input data for the model. Special attention was paid to model the losses of the UOs because in earlier studies it was found that these are significant. Loss models were developed in the form of empirical parametric equations considering the losses due to radiation and the internal losses in the heating/cooling system due to inefficient operation. The parameters of the loss models were fitted, based on the developed methodology, to steam measurements of 4 UOs and consequently integrated into the overall bottom-up model for modeling other UOs as well. The energy usage efficiency of the UOs was inferred and the optimization spots were identified. The results in the case study plant have indicated that the energy savings potential for particular UOs with low steam-usage efficiency can be easily identified and serve as a good hint for the overall plant energy auditing and steam consumption optimization.
Optimization of energy consumption for reducing the relevant costs and environmental impacts is constantly gaining attention in chemical batch production. Existing methodologies focus on heat integration considering scheduling constraints and typically result in trade-offs between capital investment and operational costs. However, in multipurpose batch plants, even the allocation of energy flows and the consistent operation according to production recipes pose a great challenge due to batch-to-batch variability and lack of energy utility consumption meters. This paper utilizes a bottom-up modeling approach for energy utility consumption and proposes a method for model-based identification of the energy saving potential in chemical batch plants. The bottom-up models can accurately track the energy utility consumption at various production levels and are used as "soft sensors" for energy efficiency analysis studies. In this context, a set of energy key performance indicators (EKPIs) is proposed for quantifying efficiency in energy use, and an energy saving potential index (ESPI) based on historical plant performance serves as a shortcut method in the case of missing or inaccurate production recipes. The methodology is applied to an industrial multipurpose batch plant for specialty chemicals, exemplifying the obtained efficiency results and targeting energy saving potential for steam consumption.
This works aims to demonstrate that hierarchical integration of planning and scheduling of industrial waste incineration improves the energy efficiency of the process, compared to available scheduling approaches. Through the integration with planning models, scheduling models can rely on more far-sighted information; therefore, energy deficits and excesses can be better compensated in the long run. Subsequently, the auxiliary fuel consumption of the incineration process can be further reduced, which leads to an overall increase of the energy efficiency. Planning and scheduling models are formulated as mixed-integer linear programming (MILP) problems with discrete time representation, based on single, uniform grids. The considered waste incineration system consists of storage tanks, a complex piping network, tank wagons for waste transport, unloading stations, and firing lances of incineration units. The conducted industrial case studies reveal substantial improvement potential of daily empirically based waste incineration routines and show that systematic integration of planning and scheduling outperforms consecutive stand-alone scheduling of industrial waste incineration both economically and environmentally by reducing auxiliary fuel usage and CO 2 emissions per ton of waste treated, by 16% and 1%, respectively.
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