Load optimisation within the cogeneration system is crucial in enhancing energy efficiency. Instead of constructing the mathematical optimisation model or applying the commercial utility optimisation software with a licensing fee, this study proposes a holistic P-graph method to model and optimise the cogeneration system using the free and user-friendly software, P-graph Studio. To consider actual performance of unit operations, novel slope-constant element is introduced in the P-graph structure to adapt the variable output-input ratios in the form of linear performance model with non-zero constant. This overcomes the functionality of the conventional P-graph structure that only considers fixed output-input ratio. A case study of an industrial cogeneration system is optimised using the proposed P-graph method, resulting in 1.24 % reduction of operating cost and CO2 emission: equivalent to savings of RM 12,822,300/year and 4,300 tonnes CO2 emission/year. Two operating strategies are proposed to revise the optimal operating method by modifying the P-graph superstructure to ensure adequacy of the utility margin in meeting the potential maximum utility demand. The operating cost saving of 0.53 % is achieved after revision to meet both operational efficiency and reliability of the cogeneration system which results in savings of RM 5,454,900/year and 1,800 tonnes CO2 emission/year.

Reduction of CO2 emissions from industrial facilities is of utmost importance for sustainable development. Novel process systems with the capability to remove CO2 will be useful for carbon management in the future. It is well-known that major determinants of performance in process systems are established during the design stage. Thus, it is important to employ a systematic tool for process synthesis. This work approaches the design of polygeneration plants with negative emission technologies (NETs) by means of the graph-theoretic approach known as the P-graph framework. As a case study, a polygeneration plant is synthesized for multiperiod operations. Optimal and alternative near-optimal designs in terms of profit are identified, and the influence of network structure on CO2 emissions is assessed for five scenarios. The integration of NETs is considered during synthesis to further reduce carbon footprint. For the scenario without constraint on CO2 emissions, 200 structures with profit differences up to 1.5% compared to the optimal design were generated. The best structures and some alternative designs are evaluated and compared for each case. Alternative solutions prove to have additional practical features that can make them more desirable than the nominal optimum, thus demonstrating the benefits of the analysis of near-optimal solutions in process design.