Meteorological data for RES-E integration studies: State of the art review

The ongoing growth of RES-E requires power system modellers to adapt both methodologies and datasets, in particular time series for electricity generation from wind and PV. Meteorological models are increasingly used for this purpose. This report provides on overview on the methodologies available and the approaches pursued by recent RES-E integration studies. Based on this review, recommendations for best practice are identified.JRC.F.6-Energy Technology Policy Outloo

Cost development of low carbon energy technologies: Scenario-based cost trajectories to 2050, 2017 edition

Future costs of low carbon energy technologies differ widely depending on assumptions and methods used. This report addresses this gap by presenting internally consistent trajectories of capital investment costs to 2050 for selected low carbon energy technologies. In order to do so, it combines global scenario projections of technology deployment with the one-factor learning rate method. Global scenarios are used to identify a range, based on potential deployment, in line with baseline assumptions and two long-term decarbonisation pathways. A sensitivity analysis is performed based on different learning rates and results are compared with literature. It is found that, depending on the technology, a 15 % to 55 % reduction in capital investment costs of offshore wind turbines, photovoltaics, solar thermal electricity and ocean energy may be achieved by 2030 compared to 2015. From then onwards, cost reduction may slow down yet remains substantial especially for photovoltaics and ocean energy. However, the assumed deployment pathway (global scenario) and learning rate influences the cost trajectories and cost reduction potential of these technologies. For onshore wind turbines, geothermal energy, biomass CHPs and CCS technologies cost reduction is less pronounced and results between scenarios do not differ significantly. The main aspects that deserve further research are firstly, the decomposition of technology cost-components and the distinction between the parts in the cost-structure that learning applies from those that need to be estimated with different methods and secondly, the influence of raw material prices in future cost trajectories of low carbon energy technologies.JRC.C.7-Knowledge for the Energy Unio

Dispa-SET 2.0: unit commitment and power dispatch model

Most analyses of the future European energy system conclude that in order to achieve energy and climate change policy goals it will be necessary to ramp up the use of renewable energy sources. The stochastic nature of those energies, together with other sources of short- and long-term uncertainty, already have significant impacts in current energy systems operation and planning, and it is expected that future energy systems will be forced to become increasingly flexible in order to cope with these challenges. Therefore, policy makers need to consider issues such as the effects of intermittent energy sources on the reliability and adequacy of the energy system, the impacts of rules governing the curtailment or storage of energy, or how much backup dispatchable capacity may be required to guarantee that energy demand is safely met. Many of these questions are typically addressed by detailed models of the electric power sector with a high level of technological and temporal resolution. This report describes one of such models developed by the JRC's Institute for Energy and Transport: Dispa-SET 2.0, a unit commitment and dispatch model of the European power system aimed at representing with a high level of detail the short-term operation of large-scale power systems. The new model is an updated version of Dispa-SET 1.0, in use at the JRC since 2009.JRC.F.6-Energy Technology Policy Outloo

Energieforschung am JRC der EU-Kommission

Energy research at the JRC includes a number of diverse activities which all provide support to the policy making process of the European Commission. Concrete examples are world class laboratories, the knowledge centre for energy efficiency (KCEE), the development of models and the support to the European SET-plan.JRC.F.6-Energy Technology Policy Outloo

The Highly Unusual Chemical Composition of the Hercules Dwarf Spheroidal Galaxy

We report on the abundance analysis of two red giants in the faint Hercules dwarf spheroidal (dSph) galaxy. These stars show a remarkable deficiency in the neutron-capture elements, while the hydrostatic alpha-elements (O, Mg) are strongly enhanced. Our data indicate [Ba/Fe] and [Mg/Fe] abundance ratios of <-2 dex and ~+0.8 dex, respectively, with essentially no detection of other n-capture elements. In contrast to the only other dSph star with similar abundance patterns, Dra 119, which has a very low metallicity at [Fe/H]=-2.95 dex, our objects, at [Fe/H]~-2.0 dex, are only moderately metal poor. The measured ratio of hydrostatic/explosive alpha-elements indicates that high-mass (~35 M_sun) Type II supernovae progenitors are the main, if not only, contributors to the enrichment of this galaxy. This suggests that star formation and chemical enrichment in the ultrafaint dSphs proceeds stochastically and inhomogeneously on small scales, or that the IMF was strongly skewed to high mass stars. The neutron capture deficiencies and the [Co/Fe] and [Cr/Fe] abundance ratios in our stars are similar to those in the extremely low metallicity Galactic halo. This suggests that either our stars are composed mainly of the ejecta from the first, massive, population III stars (but at moderately high [Fe/H]), or that SN ejecta in the Hercules galaxy were diluted with ~30 times less hydrogen than typical for extreme metal-poor stars.Comment: 5 pages, 3 figures, accepted by Astrophysical Journal Letter

Integrated modelling of future EU power and heat systems: The Dispa-SET v2.2 open-source model

This report describes the implementation of the Dispa-SET model version 2.2. It extensively describes the model equations, the model inputs, and the resolution process. This version of Dispa-SET focuses more specifically on the inclusion of the heating sector, with a new dedicated module. It allows simulating the potential interactions between heat and power and the exploitation of thermal storage as a flexible resource. The model is an open-source tool and comes with an open dataset for testing purposes. It can therefore be freely re-used or modified to fit the needs of a particular case study.JRC.C.7-Knowledge for the Energy Unio

Case study on the impact of cogeneration and thermal storage on the flexibility of the power system

This work investigates the optimal operation of cogeneration plants combined with thermal storage. To do so, a combined heat and power (CHP) plant model is formulated and incorporated into Dispa-SET, a JRC in-house unit commitment and dispatch model. The cogeneration model sets technical feasible operational regions for different heat uses defined by temperature requirements.JRC.C.7-Knowledge for the Energy Unio

Case study on the impact of cogeneration and thermal storage on the flexibility of the power system

This work investigates the optimal operation of cogeneration plants combined with thermal storage. To do so, a combined heat and power (CHP) plant model is formulated and incorporated into Dispa-SET, a JRC in-house unit commitment and dispatch model. The cogeneration model sets technical feasible operational regions for different heat uses defined by temperature requirements

Systematic mapping of power system models: Expert survey

The power system is one of the main subsystems of larger energy systems. It is a complex system in itself, consisting of an ever-changing infrastructure used by a large number of actors of very different sizes. The boundaries of the power system are characterised by ever-evolving interfaces with equally complex subsystems such as gas transport and distribution, heating and cooling, and, increasingly, transport. The situation is further complicated by the fact that electricity is only a carrier, able to fulfil demand for such things as lighting, heat or mobility. One specific and fundamental feature of the electricity system is that demand and generation must match at any time, while satisfying technical and economic constraints. In most of the world’s power systems, only relatively small quantities of electricity can be stored, and only for limited periods of time. A detailed analysis of supply and demand is thus needed for short time intervals. Mathematical models facilitate power system planning, operation, transmission and distribution, demonstrating problems that need to be solved over different timescales and horizons. The use of modelling to understand these processes is not only vital for the system’s direct actors, i.e. the companies involved in the generation, trade, transmission, distribution and use of electricity, but also for policy-makers and regulators. Power system models can provide evidence to support policy-making at European Union, Member State and Regional level. As a consequence of the growth in computing power, mathematical models for power systems have become more accessible. The number of models available worldwide, and the degree of detail they provide, is growing fast. A proper mapping of power system models is therefore essential in order to: - provide an overview of power system models and their applications available in, or used by, European organisations; - analyse their modelling features; - identify modelling gaps. Few reviews have been conducted to date of the power system modelling landscape. The mission of the Knowledge for the Energy Union Unit of the Joint Research Centre (JRC) is to support policies related to the Energy Union by anticipating, mapping, collating, analysing, quality checking and communicating all relevant data/knowledge, including knowledge gaps, in a systematic and digestible way. This report therefore constitutes: - From the energy modelling perspective, a useful mapping exercise that could help promote knowledge-sharing and thus increase efficiency and transparency in the modelling community. It could trigger new, unexplored avenues of research. It also represents an ideal starting point for systematic review activities in the context of the power system. - From the knowledge management perspective, a useful blueprint to be adopted for similar mapping exercises in other thematic areas. Finally, this report is aligned with the objectives of the European Commission's Competence Centre on Modelling, (1) launched on 26 October 2017 and hosted by the JRC, which aims to promote a responsible, coherent and transparent use of modelling to support the evidence base for European Union policies. In order to meet the objectives of this report, an online survey was used to collect detailed and relevant information about power system models. The participants’ answers were processed to categorise and describe the modelling tools identified. The survey, conducted by the Knowledge for the Energy Union Unit of the JRC, comprised a set of questions for each model to ascertain its basic information, its users, software characteristics, modelling properties, mathematical description, policy-making applications, selected references, and more. The survey campaign was organised in two rounds between April and July 2017. 228 surveys were sent to power system experts and organisations, and 82 questionnaires were completed. The answers were processed to map the knowledge objectively. (2) The main results of the survey can be summarised as follows: - Software-related features: about two thirds of the models require third-party software such as commercial optimisation solvers or off-the-shelf software. Only 14% of the models are open source, while 11% are free to download. - Modelling-related features: models are mostly defined as optimisation problems (78%) rather than simulation (33%) or equilibrium problems (13%). 71% of the models solve a deterministic problem while 41% solve probabilistic or stochastic problems. - Modelled power system problems: the economic dispatch problem is the most commonly modelled problem with a share of approximately 70%, followed by generation expansion planning, unit commitment, and transmission expansion planning, with around 40‒43% each. Most of the models (57%) have non-public input data while 31% of models use open input data. - Modelled technologies: hydro, wind, thermal, storage and nuclear technologies are widely taken into account, featuring in around 83‒94% of models. However, HVDC, wave tidal, PSTs, and FACTS (3) are not often found unless the analysis is specifically performed for those technologies. - Applicability in the context of European energy policy: more than half of the mapped models (56%) were used to answer a specific policy question. Of the five Energy Union strategic dimensions, integration of the European Union internal energy market was addressed the most often (27%), followed by climate action (23%), research, innovation and competitiveness (21%), and energy efficiency (15%). This report includes JRC recommendations based on the results of the survey, on future research avenues for power system modelling and its applicability within the Energy Union strategic dimensions. More attention should be paid, for example, to model uncertainty features, and collaboration among researchers and practitioners should be promoted to intensify research into specific power system problems such as AC (4) optimal power flow. The report includes factsheets for each model analysed, summarising relevant characteristics based on the participants’ answers. While this report represents a scientific result per se, one of the expected (and welcomed) outcomes of this mapping exercise is to raise awareness of power system modelling activities among European policy makers.JRC.C.7-Knowledge for the Energy Unio

Addressing flexibility in energy system models

The present report summarises the discussions and conclusions of the international workshop on "Addressing flexibility in energy system models" held on December 4 and 5 2014 at the premises of the JRC Institute for Energy and Transport in Petten. Around 40 energy modelling experts and researchers from universities, research centres, the power industry, international organisations, and the European Commission (DGs ENER and JRC) met to present and discuss their views on the modelling of flexibility issues, the linkage of energy system models and sector-detailed energy models, the integration of high shares of variable renewable energy sources, and the representation of flexibility needs in power system models. The discussions took into account modelling and data-related methodological aspects, with their limitations and uncertainties, as well as possible alternatives to be implemented within energy system models.JRC.F.6-Energy Technology Policy Outloo