A stochastic integrated planning of electricity and natural gas networks for Queensland, Australia considering high renewable penetration. (15th June 2018)

• Record Type: Journal Article
• Authors: Nunes, Juliana Barbosa; Mahmoudi, Nadali; Saha, Tapan Kumar; Chattopadhyay, Debabrata
• Is Part Of: Energy. Volume 153(2018)
• Page Start: 539
• Page End: 553
• Publication Date: 2018-06-15
• Subjects: Electricity network -- Gas network -- High renewable energy penetration -- Long-term integrated planning -- Stochastic optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.03.116
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This study develops a long-term integrated planning approach to electricity and gas aiming at economically optimizing the 2030's investments of both networks while considering new policies towards future clean energy. A static stochastic cost minimization model is formulated, which takes into account the short-term uncertainties of renewable power, i.e. wind and utility-scale solar photovoltaic (PV) as well as the long-term uncertainties of load growth and gas price. The equivalent networks of both electricity and gas are driven to accurately capture their existing supplies and transmission networks. In addition, the integrated planning model allows determining the location of new power plants and gas supply facilities with their optimized capacities, as well as new transmission lines and pipelines. An extension of the proposed scheme is considered to accommodate higher penetrations of renewable energy and assess their impacts on both systems. The proposed model is applied to the state of Queensland in Australia, which is a prime example of a region actively integrating electricity and gas. Highlights: A comprehensive electricity and gas integrated planning approach is proposed. Stochastic programming is formulated to model uncertainties faced by both systems. Impact of high penetration of renewable energy is assessed on planning outcomes. The proposed model is validated on a realistic case of Queensland in Australia. The usefulness of the given planning model is shown through several analyses.