Flexible Distributed Multienergy Generation System Expansion Planning Under Uncertainty
A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand si...
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Published in | IEEE transactions on smart grid Vol. 7; no. 1; pp. 348 - 357 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
IEEE
01.01.2016
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Subjects | |
Online Access | Get full text |
ISSN | 1949-3053 1949-3061 |
DOI | 10.1109/TSG.2015.2411392 |
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Abstract | A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems. |
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AbstractList | A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems. |
Author | Capuder, Tomislav Mancarella, Pierluigi Martinez Cesena, Eduardo A. |
Author_xml | – sequence: 1 givenname: Eduardo A. surname: Martinez Cesena fullname: Martinez Cesena, Eduardo A. email: eduardo.martinezcesena@manchester.ac.uk organization: Dept. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK – sequence: 2 givenname: Tomislav surname: Capuder fullname: Capuder, Tomislav organization: Fac. of Electr. Eng. & Comput., Univ. of Zagreb, Zagreb, Croatia – sequence: 3 givenname: Pierluigi surname: Mancarella fullname: Mancarella, Pierluigi organization: Dept. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK |
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SubjectTerms | Cogeneration Distributed generation Electric power distribution Electricity Flexibility Heat pumps Investment Mathematical analysis Methodology multienergy systems Planning planning under uncertainty real options (ROs) Resistance heating risk Smart grid storage Uncertainty Vectors Vectors (mathematics) |
Title | Flexible Distributed Multienergy Generation System Expansion Planning Under Uncertainty |
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