Abstract
This paper focuses on expansion co-planning studies of natural gas and electricity distribution systems. The aim is to develop a mixed-integer linear programming (MILP) model for such problems to guarantee the finite convergence to optimality. To this end, at first the interconnection of electricity and natural gas networks at demand nodes is modelled by the concept of energy hub (EH). Then, mathematical model of expansion studies associated with the natural gas, electricity and EHs are extracted. The optimization models of these three expansion studies incorporate investment and operation costs. Based on these separate planning problems, which are all in the form of mixed-integer nonlinear programming (MINLP), joint expansion model of multi-carrier energy distribution system is attained and linearized to form a MILP optimization formulation. The presented optimization framework is illustratively applied to an energy distribution network and the results are discussed.
Highlights
In the era of modern energy systems, electricity and natural gas networks are becoming more and more interdependent [1,2,3,4]
Motivated by the aforementioned points, this paper aims to propose a mixed-integer linear programming (MILP) model for natural gas and electricity distribution networks co-planning studies considering different energy hubs (EH)
The energy distribution systems, that is, energy hub, natural gas distribution system and electricity figure, the problem modelling starts with the formulation of three general parts of multi-carrier figure, the problem modelling starts with the formulation of three general parts of multi-carrier energy distribution network expansion planning problems
Summary
In the era of modern energy systems, electricity and natural gas networks are becoming more and more interdependent [1,2,3,4]. It is essential to run integrated studies of electricity and gas systems to improve the overall efficiency of the energy system. Stochastic models based on the Monte Carlo simulation are developed in Reference [3,4] to perform day-ahead scheduling and obtain energy flow solution for integrated natural gas and electricity power systems, respectively. In Reference [5], a two-stage stochastic look-ahead dispatch is proposed for integrated electricity power and gas systems which can adjust the improper day-ahead dispatch plan (Stage 1) in the second stage. In Reference [7], a multi-area, multi-stage model is proposed to integrate the long-term expansion planning studies of generation and transmission of natural gas and electricity systems. An optimization model is developed in Reference [8] to reach optimal expansion plans for gas power plants, electricity transmission lines and gas pipelines in terms
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