Author ORCID Identifier

0000-0001-7076-8558

Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Electrical and electronic engineering

Publication Details

IET Generation, Transmission and Distribution

Abstract

Over the last decades, electricity generation from natural gas has substantially increased, mostly driven by low natural gas prices due to fracturing and lower extraction costs. The geographic distance between natural gas resources and load centers calls for a holistic tool for joint expansion of power systems and natural gas networks. In this paper, a Dynamic Stochastic Joint Expansion Planning (DSJEP) of power systems and natural gas networks is proposed to minimize the investment and operational costs of power and natural gas systems. Electrical and natural gas storage (ENGS) are considered as an option for decision-makers in the DSJEP problem. The proposed approach takes into account long-term uncertainties in natural gas prices and electric and natural gas demands through scenario realizations. In dynamic planning, more scenario needs more time for computation; therefore, scenario reduction is implemented to eschew unnecessary scenarios. The proposed formulation is implemented on a four-bus electricity system with a five-node natural gas network. To demonstrate the efficiency and scalability of the proposed approach, it is also tested on the IEEE 118-bus system with a 14-node natural gas network. The numerical results demonstrate that ENGS can reduce the total investment cost, up to 52% in the test cases, and operational cost, up to 3%. In this paper, co-planning of power and natural gas systems considering natural gas and electrical storage is represented. Also, electrical and natural gas load growth uncertainties are taken into account to model the real situations. The purpose of the model is to minimize investing and operational costs.

DOI

https://doi.org/10.1049/gtd2.12277

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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