It has value 0 if the TimeSlice does not pertain to the specific DayType, 1 if it does.īinary parameter linking one TimeSlice to a certain DaylyTimeBracket. It has value 0 if the TimeSlice does not pertain to the specific season, 1 if it does.īinary parameter linking one TimeSlice to a certain DayType. Length of one DailyTimeBracket in one specific day as a fraction of the year (e.g., when distinguishing between days and night: 12h/(24h*365d)).īinary parameter linking one TimeSlice to a certain Season. Region specific value for the discount rate, expressed in decimals (e.g. The sum of each entry over one modelled year should equal 1. It includes storage facilities in the model.ĭuration of a modelled time slice, expressed as a fraction of the year. This set is needed if storage facilities are included in the model. night, morning, afternoon, evening) and in which order these parts are sorted. It gives indication (by successive numerical values) of how many parts the day is split into (e.g. workday, weekend) are accounted for and in which order. It gives indication (by successive numerical values) of how many day types (e.g. winter, intermediate, summer) are accounted for and in which order. It gives indication (by successive numerical values) of how many seasons (e.g. In some occasions it might be computationally more convenient to model different countries within the same region and differentiate them simply by creating ad hoc fuels and technologies for each of them. For each of them, the supply-demand balances for all the energy vectors are ensured, including trades with other regions. For example, a CHP plant may produce heat in one mode of operation and electricity in another. any linear combination) of these input or output fuels, each mix can be accounted as a separate mode of operation. If a technology can have various input or output fuels and it can choose the mix (i.e. It defines the number of modes of operation that the technologies can have. Typical examples would include atmospheric emissions of greenhouse gasses, such as CO2. It includes any kind of emission potentially deriving from the operation of the defined technologies. These can be aggregate groups, individual flows or artificially separated, depending on the requirements of the analysis. It includes any energy vector, energy service or proxies entering or exiting technologies. Those seasons may be subdivided into aggregate ‘day types’ (such as workdays and weekends), and the day further sub divided (such as into day and night) depending on the level of demand. Thus, the annual demand may be split into aggregate seasons where demand levels are similar (such as ‘summer, winter and intermediate’). In order to reduce the computation time, these ‘slices’ are often grouped. It is necessary to assess times of the year when demand is high separately from times when demand is low, for fuels that are expensive to store. MESSAGE / MARKAL / TIMES), the annual demand is ‘sliced’ into representative fractions of the year. Common to several energy systems modelling tools (incl. It represents the time split of each modelled year, therefore the time resolution of the model. It may for example represent a single real technology (such as a power plant) or can represent a heavily aggregated collection of technologies (such as the stock of several million light bulbs), or may even simply be a ‘dummy technology’, perhaps used for accounting purposes.
TIMESLICE IN R FREE
As the model is an abstraction, the modeller is free to interpret the role of a technology at will, where relevant. All system components are set up as a ‘technology’ in OSeMOSYS. It includes any element of the energy system that changes a commodity from one form to another, uses it or supplies it. It represents the time frame of the model, it contains all the years to be considered in the study. The sets of OSeMOSYS are presented in the Table below. For instance, when a variable is defined as a function of the set ‘YEAR’ it will be indicated as variablename at it will be computed for every year listed in the set. They define the time domain and time split, the spatial coverage, the technologies and energy vectors to be considered, etc. The ‘sets’ define the physical structure of a model, usually independent from the specific scenarios which will be run.
TIMESLICE IN R HOW TO
How to contribute to the development of the tool.
0 kommentar(er)
