Electricity - PROMETHEUS
PROMETHEUS incorporates a detailed module for the representation of the investment and operation of the power sector. Total electricity generation is determined by electricity demand for the industrial, residential and transportation sectors, own-consumption of power plants and transmission and distribution losses in each region identified in the model. Electricity trade between regions is exogenous in the model.
PROMETHEUS is equipped with an enhanced portfolio of power generation technologies that compete to satisfy electricity requirements. The power sector model includes the following technologies: coal-firing, lignite-firing, open cycle oil, open cycle gas, gas turbines, Gas combined cycle (CCGT), nuclear, CCS-coal, CCS-gas, biomass-firing, CCS-biomass, wind onshore, hydro (large and small), solar photovoltaic, wind offshore, concentrated solar power (CSP) and others. The option of solar thermal power station combining solar power with natural gas is also included in the model.
Plant scrapping (normal and premature) and competition of alternative technologies in new capacity installations follow the pattern of the substitution mechanism. PROMETHEUS also accounts for already decided investments in specific power plants and the firmly adopted plans for decommissioning of old and inefficient ones in each region, as obtained from a wide literature review.
New generation capacity in each region is determined by the evolution of electricity demand in the various sectors, scrapping of power plants, firmly adopted plans for decommissioning of old and inefficient plants, the already decided investments in specific power plants for the period until 2015 (especially for nuclear and RES) and the security of supply margin. The allocation of new investments in power generation technologies is determined by the overall cost of the competing options, which includes capital, fixed and variable O&M and fuel costs as well as additional costs for integrating intermittent RES in the power grid or additional costs for capture and storage of CO2 for CCS technologies. The utilisation of the capacity of power plants for each time segment (dispatching of power plants) is endogenous in the model and is determined by the annual load duration curve in combination with variable O&M and fuel costs and the installed capacities of the different technologies.
The model associates a demand fluctuating profile to every use of electricity included in the demand sector modules (industry, transport, households). Regional load profiles change over time and in scenarios, depending on the relative shares of various electricity uses, the prices (which are higher for sectors with low load factors), the degree of energy savings (and the use of more efficient equipment) and special demand side management measures including smart metering, which in the transport sector are supposed to motivate battery recharging at off peak hours. When load profiles become smoother, capital intensive power technologies are favoured (like RES and nuclear) and reserve power requirements are lower, implying lower overall costs. Consumer prices of electricity are derived based on wholesale market prices, grid tariffs, subsidization of electricity prices and taxation including carbon emission pricing. Targets for renewables, penetration of natural gas and CO2 emissions are reflected in the model influencing both dispatching of plants and the choices in investment decision making. All economic/choice modeling (e.g. investment choice, fuel switching, dispatching) in PROMETHEUS reflects the financial perspective of power plant project developers and includes all costs, subsidies and taxes as well as other financial incentives that directly affect investment decisions. These financial instrument can potentially include feed-in tariffs, RES promoting policies, fuel standards, strategy for cleaner electricity dispatch and risk premiums differentiated by technology. The potential for RES is represented by nonlinear cost-supply curves distinguished by type of source (wind onshore, photovoltaics, solar thermal, wind offshore, hydro and biomass).
Electricity prices are determined by the long term average generation costs and are calculated separately for the final electricity demand sectors (industry and domestic sectors). Differences in electricity prices between sectors mostly arise from the fact that different technologies supply different segments of the load duration curve and from differential distribution and grid costs. The electricity prices in PROMETHEUS are calculated in order to recuperate all costs, including capital and operating costs, costs related to schemes supporting renewables, grid costs and supply costs. The power sector model simulates a wholesale market subject to technical plant operation constraints and reserve requirements, represents dispatching of power plants and can simulate investment in new power plants. The market bidding of power plants aims at recovering fixed and capital costs. Power grids are implicitly represented as capital assets evolving based on investment, which in turn depends on demand evolution and the penetration of variable decentralized RES sources (that increase grid requirements and hence grid costs).
Investment in RES based electricity is dominated by the consideration of capital costs. On the other hand such technologies are generally characterised by limitations as to their potential. In most cases this is taken into account by incorporating reductions in availability as such potentials are approached (i.e. the most suitable sites being exploited earlier and less suitable ones increasingly sought). This effectively results in a supply curve where costs increase non-linearly with the gradual exhaustion of potential. The cost-supply curve implies that additional RES deployment is accompanied by a reduction in availability and hence increase in RES costs for electricity production due to the depletion of suitable sites, the difficulty of getting access to resource and grid connection difficulties. In establishing such curves, a wide range of bibliography is used. The modelling also simulates the site retaining factor, i.e. the cost incentive to install a new renewable power plant in the same place where an old one existed.
PROMETHEUS can take into account support for RES technologies in each of the ten regions identified in the model by assuming different levels of feed-in tariff and other supporting schemes for renewables in the alternative scenarios simulated. The main RES facilitation policies that can be simulated with the PROMETHEUS model include subsidies for RES technologies, feed-in tariffs and obligation/target for specific RES deployment. In constructing the supply curves for biomass, a number of studies were taken into account which include technical and economic assessment of biomass potential. However, their estimates vary significantly, implying high uncertainty regarding biomass economic potential. Such uncertainty is introduced explicitly in the specification of the biomass cost equations, according to which the deployment of biomass technologies is constrained by limited land and waste energy resource availability. Driven by emission reduction targets or by carbon pricing, CCS competes with other emissions reduction options, such as carbon free power generation (renewable energy, nuclear), the fuel switching towards low emitting forms and the reduction of energy consumption. The power plants that are equipped with CCS are more expensive in terms of capital and O&M costs and have lower net thermal efficiency compared to similar plants without carbon capture. Non-linear cost-supply curves are simulated for underground storage of carbon dioxide. Public acceptance issues can be modelled through parameters lowering CCS potential and making the technology more expensive.
Nuclear deployment depends on the evolution electricity demand, load profiles, economic features of competing technologies and carbon prices (and other energy and climate policies assumed in each of the ten regions identified in the model). The unit cost of investment depends on the nuclear technology: nuclear PWR and fourth generation technologies are represented in the model. The unit cost of investment take into account costs for future decommissioning (15% provision). Variable and fuel costs of nuclear power take into account waste recycling and disposal costs. Nuclear costs have been revised upwards following the Fukushima accident. Due to the long construction times for new nuclear power plants, the increasing public acceptability concerns and the difficulty to licence and build new nuclear plants, the development of nuclear power is calibrated until 2025 taking into account the already decided investments and the firmly adopted plans for decommissioning of nuclear power plants in each region identified in the model. The building of a power generation plant usually requires several years (especially with regard to nuclear and hydro technologies). This has important implications for cost evaluation of alternative technologies that influence power system planning and choice of plant type. The model considers the financial costs associated with the construction period of each power generation technology, which can be significant in the case of nuclear power plants.
|No previous version available|
|Institution||E3Modelling (E3M), Greece, https://e3modelling.com/modelling-tools.|
|Solution concept||Partial equilibrium (price elastic demand)|
|Anticipation||Energy system simulation.Foresight is included only is some sub-modules (i.e. electricity generation)|