Bi-level planning for integrated electricity and natural gas systems with wind power and natural gas storage. (June 2020)

• Record Type: Journal Article
• Authors: Wang, Xu; Bie, Zhaohong; Liu, Fan; Kou, Yu; Jiang, Lizhou
• Is Part Of: International journal of electrical power & energy systems. Volume 118(2020)
• Publication Date: 2020-06
• Subjects: Bi-level planning -- Integrated electricity and natural gas system -- Selected scenarios -- Wind power -- Natural gas storage -- Benders decomposition; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2019.105738
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Wind farm, power-to-gas and gas storages are incorporated in the planning model. Scenario-based stochastic planning model is set up for the uncertainty of wind power. A Bender-based decomposition algorithm is developed to solve the planning model. Gas storage and power-to-gas play an important role in alleviating the lack of gas. Abstract: Power-to-gas facilities (PtG) are able to convert excess renewable energy into synthetic natural gas that can be stored in natural gas storage units. The coordinated planning of gas-fired generators, PtG and natural gas storage offers the prospect of mitigating energy shortages and accommodating renewable energy within integrated electricity and natural gas systems (IEGS). This paper presents a bi-level planning model for IEGS that minimizes the investment costs of candidate assets, especially wind farms, PtG facilites and natural gas storage units, as well as the operational cost over the planning horizon. A small number of carefully selected scenarios are presented to illustrate the uncertainty of wind power. IEGS operation is also analyzed on the basis of these temporal scenarios, including the operational characteristics and constraints of two systems to assess the potential role of natural gas storage and PtG. The proposed model is a scenario-based planning model that is solved by a bi-level iterative algorithm. The upper-level base-scenario based planning problem determines the candidate assets while the lower-level problem checks the feasibility using the determined components for other scenarios. Two sets of numerical tests are presented to demonstrate the effectiveness of the proposed planning model and associated algorithms.