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Risk Explicit Interval Linear Programming Model for CCHP System Optimization Under Uncertainties

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Geo-Spatial Knowledge and Intelligence (GSKI 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 849))

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Abstract

A risk explicit interval linear programming model for CCHP system optimization was proposed to provide better system cost-risk tradeoff for decision making. This method is an improved interval parameter programming, which can overcome the shortages of traditional interval parameter programming. The proposed approach can provide explicit system cost-risk tradeoff information by introducing aspiration level and system risk metric objective function. The explicit optimal strategies for decision maker with certain risk tolerance degree is more executable than the interval solutions in practice. The developed approach was applied to the CCHP system for a residential area. The results indicated that the aspiration level would have great effects on the system investment and operation decision making. For the pessimistic decision maker, the total cost would be higher with less system risk and safer system operation. For the optimistic decision maker, the total cost would be lower with higher system risk.

L. Ji—Research field in energy system optimization.

This study is financial supported by National Natural Science Foundation of China (No. 71603016) and Natural Science Foundation of Beijing Municipality (No. 9174028).

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Acknowledgement

The authors gratefully acknowledge the financial support from National Natural Science Foundation of China (No. 71603016) and Natural Science Foundation of Beijing Municipality (No. 9174028).

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Correspondence to Ling Ji .

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Ji, L., Huang, L., Xu, X. (2018). Risk Explicit Interval Linear Programming Model for CCHP System Optimization Under Uncertainties. In: Yuan, H., Geng, J., Liu, C., Bian, F., Surapunt, T. (eds) Geo-Spatial Knowledge and Intelligence. GSKI 2017. Communications in Computer and Information Science, vol 849. Springer, Singapore. https://doi.org/10.1007/978-981-13-0896-3_68

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  • DOI: https://doi.org/10.1007/978-981-13-0896-3_68

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0895-6

  • Online ISBN: 978-981-13-0896-3

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