Markal, a linear-programming model for energy systems analysis: Technical description of the bnl version

Abstract

As part of a project to assess the value of new energy technologies, an international group of researchers created a linear‐programming model of national energy systems. This model, MARKAL, is driven by useful energy demands, optimizes over several time periods collectively, and allows multiobjective analyses to be performed quite easily. We describe here the technical structure of the model, defining the functions determined when satisfying the model's relations and the parameters that must be supplied to give the model content.

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

“…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. Although this study is the first attempt for Tianjin's energy system management through the developed IF-MEM, the model results suggest that this method is applicable of providing decisions for energy system management.…”

“…still be the dominant one although its proportion declined in the future. In conclusion, the amount of gasoline and diesel consumption from traffic systems would decrease [16,24] % and [12,23] %, respectively; and the amount of clean energy resources (i.e., LPG, electric and hydrogen) would increase [15,23] % during the planning periods. The results indicate traditional fossil fuels are still major fuel (i.e., gasoline and diesel) for traffic system.…”

“…(9) Constraints of mass for kerosene are expressed as follows: [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] where DMK þ t and DMK À t are the upper and lower bound of kerosene demands in period t (10 3 ton).…”

“…For example, the market allocation model (MARKAL) was developed as a large-scale, technology-oriented energy-activity analysis modeling system. Based on MARKAL, sectors of energy production, conversion, processing, transmission and consumption can be incorporated within a general framework to help formulate cost-effective energy-related plans [9e12, 23,24]. Brookhaven energy system optimization model (BESOM) was used to identify optimal mixing patterns of energy sources, technologies and investments within an energy management system under the minimized economic cost [8,25].…”

Energy Technology Expert Elicitations for Policy: Workshops, Modeling, and Meta-Analysis

“…The main objective was to provide insights to both DOE and EU policy makers about the allocation of RD&D funding across several technology areas: nuclear power, solar photovoltaics, concentrated solar power, biofuels, bioelectricity, vehicles, utility scale energy storage, and fossil power with and without carbon capture and storage. 4 5 Elicitations for the US were carried out between 2009 and 2011 and were designed so that their results could be used in MARKAL (Fishbone & Abilock, 1981), a widely -used energy-economic model, to provide insights about DOE funding decisions across different programs. Elicitations for the EU were carried out by FEEM between 2009 and 2011 within the FP7 project ICARUS and designed for use in WITCH (www.witchmodel.org), an integrated assessment energy model.…”