Co‐planning of electricity and gas networks considering risk level assessment

Abstract

This study provides a risk‐based gas and electricity expansion planning model to coordinate the expansion of electricity and gas networks in a multi‐carrier energy network. Generally, electricity and gas networks have separate owners having no mechanisms to share information. In this study, a distributed algorithm based on alternative direction method of multipliers is developed to preserve the privacy of electricity and gas networks while maintaining a coordination link. Probabilistic outage of components is implemented into the expansion planning model to investigate the interactions between electricity and gas networks and evaluate the risk of contingencies in generating units, transmission lines, and pipelines. Second fuel of gas consuming generating units is modelled to have a holistic approach while studying electricity and gas interactions in the case of contingencies. Moreover, conditional value at risk is used to adjust a balance between risk and investment where each of energy parties can decide on the risk level of their expansion plans. The proposed expansion planning approach is applied to a realistic case study to evaluate its performance.

Information and communications technology (ICT) infrastructure supporting smart local energy systems: A review

“…The communication time intervals of data in SLES (i.e. how frequently the data are sent/received) may also be relevant with the time resolution of the scheduling conducted in SLES, for example, the day-ahead generation or load scheduling with an hourly update, as those in [36,43,44,63,73,74]. Besides this, the flexibility markets in SLES usually involve frequent updates of prices (e.g.…”

“…The operation-oriented measurements include mass flow temperature at the inlet and outlet of pipelines in supply/return District heating network (DHN), MFRs of heat stations in DHN, pressure heads of the supply/return DHN, mixed temperature at a node in supply/return DHN, minimum/maximum temperature at different nodes in supply/return DHN, and water flow at different nodes in DHN [53,54,62,63] The management-oriented measurements include total rate of heat energy available at the central source for district heating need, available heat energy at central energy source, efficiency of water pumps in heat stations, heat transfer coefficient of pipelines, and coefficients of pressure loss in water pipelines [56,57].…”

A cyber‐secure model to decentralized co‐expansion planning of gas and electricity networks

“…Gas nodal balance is modeled by (12). Restrictions imposed by compressors at the output pressure of active pipelines are dictated by (13). 25 Compressors gas consumption is approximated using ( 14) with node i/j as primary/secondary side.…”

Review on the state‐of‐the‐art multi‐objective optimisation of hybrid standalone/grid‐connected energy systems

“…The application of gas turbines in the power system has increased the interactions between electricity and gas networks [148]. Hence, the planning of gas–electricity multi‐carrier system has attracted the most attention [149–151]. The planning studies on multi‐energy water–electricity systems can investigate the interactions between electricity supply, hydropower, water pumping and water desalination systems [152–154].…”