In this article, a novel framework for the design of mixed (combined direct and indirect) integration for batch process systems is presented. The framework is based on the concept of pseudo-direct energy integration (PDEI) which reformulates indirect integration as direct integration using pseudo-process streams. Two algorithms are presented to achieve energy integration for batch processes operating cyclically (in a campaign mode). The first algorithm targets maximization of energy recovery and overcomes the limitations of some of the existing contributions for design of mixed integrated systems. The second algorithm provides a network reduction methodology to generate a cadre of integrated designs while exploring the trade-off between capital (number of heat exchangers and storage units) and operating costs (utility consumption). The proposed framework is illustrated using a benchmark example of two hot and two cold streams.Add the pseudo-process streams obtained in the ith interval to the set of pseudo-process streams for the (i 1 1)th interval. Figure 3. Algorithm for minimum utility design using pseudo-direct energy integration.

Heat integration in batch processes strongly depends on the production schedule due to time-dependent availability of hot and cold process streams. Schedule delays in batch process operation are inevitable and can significantly reduce the practical benefits promised by heat integration. This paper presents a systematic framework to analyze the effect of schedule delays on achievable heat recovery in batch process systems. To this end, a time delay analysis method is proposed to generate heat recovery profile as a function of stream delay. The analysis computes maximum theoretical heat recovery (with a modified heat exchanger network) as well as practically achievable heat recovery (with the same network). The results of time delay analysis are then used to define three robustness measures to assess the sensitivity of a heat-integrated batch process network toward schedule delays. The presented framework allows identification of sensitive process streams as well as provides an operational measure to screen competing design alternatives. Two relevant example systems are considered to illustrate the effectiveness of the proposed framework.

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