Modelling and optimisation of electricity, steam and district heating production for a local Swedish utility

Interval-fuzzy municipal-scale energy model for identification of optimal strategies for energy management – A case study of Tianjin, China

“…Several finding can be revealed as follows: (i) the city's energy structure tends to transition from coaldominated into diversity energy structure. Coal's consumption would decrease [10,12]%. While, natural gas would become the one of the most competitive resources, which with a growth rate of [74.2, 139.1]%; liquefied petroleum gas (LPG) would grow up 4 times over the planning horizon; (ii) coal-fired holds the dominant position, but its proportion would reduce from 81% in period 1 to 66% in period 3; (iii) traditional fossil fuels for traffic system would be limited and comparatively clean energy would be encouraged, gasoline and diesel consumptions from traffic system would decrease [16,24]% and [12,23]%, respectively; the comparatively clean energy resources (i.e., LPG, electric and hydrogen) would increase [15,23]% during the planning periods, which would contribute about [20,32]% [20,31]%, and 10% reductions in CO, HC and NOX emissions; (iv) SO2, NOx and PM10 emissions from electricity and heat generations would reduce [10.1, 11.2]%, [4.7, 9.6]% and [8.6, 8.7]% during the planning periods, because of the restriction of fossil fuels and the development of clean and renewable energy technologies.…”

Methodology of optimisation of local energy infrastructure development

“…Another model which may be helpful to local administration is MODEST components [11,12]. MODEST is a linear programming model that minimizes the costs of supplying heat and electricity during the analyzed period.…”

“…One of the most popular energy models which may be used in the local scale (although it's geographical scope is universal -including region and country) is Perseus [5,11,14,27]. It is a dynamic, linear, optimization model which selects the best technologies and fuels to meet the given demand for various energy forms.…”

A general spatio-temporal model of energy systems with a detailed account of transport and storage

“…They were not developed to determine the design and operation of the energy network, which requires consideration of storage and transport, and therefore they have a very limited spatial and temporal 115 resolution (see also Section 7). Other examples of lumped models include MESSAGE [19] and MODEST [20,21]. Distributed models explicitly account for spatial dependency and are usually employed in supply chain models (e.g.…”

“…Many future energy system models are multiperiod such as in [17,18,19,20,21,24,28], the peak/average version of the TURN model for urban energy systems design [30], and the BVCM [22] which reduces to a multiperiod model with staged investment when seasonality is not considered. Finally, dynamic models consider a much finer resolution for 140 time, often using daily or shorter intervals, and are designed to look at short-term operational aspects of the energy system, such as how to account for storage (a dynamic inventory balance must be written) or how to account for the limited rate at which technologies can change load (hence ramp-up/ramp-down constraints are used and link the operation of the technologies from one time period to the next).…”