The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments
- Characterising electricity security via features at the cross-roads of policy and science.
- Reviewing the electricity security modelling and assessment approaches across sectors.
- Proposing elements for a novel electricity security decision-analytic framework for the EU.
- Contextualising the proposed framework in EU’s Energy Union grid design initiatives.
2. Electricity Security Characterisation
- A multi-threat problem. The threats—potentially materialising into adverse events perturbing the power system’s delivery mission—can be characterised in terms of impact areas, time duration, provenance (internal or external to the power system), and their intrinsic nature: natural (e.g., storms or earthquakes), malicious (e.g., cyber or physical attacks), accidental (e.g., technical or human errors), and systemic (mostly linked to the energy system transition).
- A multi-time scale problem. Various time frames need to be considered due to the inherently different electricity security challenges, system performances and actions which can be put in place. The following time frames are considered in this work: Short-term (from real time up to tens of minutes), Mid-term (up to weeks), Long-term (up to years), Very long-term (up to decades).
- A multi-spatial scale problem. Electricity security has both local and far-reaching geographical features and this research mostly compares the EU, regional and national scales.
- A multi-dimension problem. The following four overarching dimensions (see Figure 2) of electricity security are identified, and they can be visualised as the physical or virtual corridors across which the electricity commodity/services travel to reach the users:
- The infrastructure dimension, i.e., the electricity value chain;
- The source dimension, i.e., the wider energy system providing the primary sources converted in electricity;
- The regulation and market dimension, i.e., the set of laws, rules, market arrangements and price schemes governing the electricity operations and transactions;
- The geopolitical dimension, i.e., the geographical and political spaces in which decisions on energy infrastructure build and energy resource transportation are made.
- A multi-property problem. Electricity security can be characterised as a combination of several electricity security properties—presenting though possible overlaps—all having to do with the system’s capability to regain a certain performance level after adverse events. Different definitions for electricity security properties can be adopted, also because there is no consensus/standardisation on some of them (flexibility, resilience and robustness). In this work we consider what follows (see Figure 3) [13,14,15,16,17,18,19]:
- Operational security is the short-term electricity security linked to events (e.g., short circuits or unplanned outages) mainly occurring in the infrastructure and source dimensions.
- Flexibility is the short-/mid-term electricity security linked to events (e.g., unpredicted variability of renewable energy) mainly occurring in the infrastructure, source and market and regulation dimensions.
- Adequacy is the long-/mid-term electricity security linked to events (e.g., scarcity of back-up capacity) mainly occurring in the infrastructure, source and market and regulation dimensions.
- Resilience is the mid-/long-term electricity security linked to events (e.g., a cyber-attack gradually affecting a control centre’s operations, or unplanned reverse power flows from the distribution grids) mainly occurring in the infrastructure, source and market and regulation dimensions.
- Robustness is the long-/very-long term electricity security linked to events (e.g., a policy of nuclear power phase-out or the unilateral decision to interrupt primary energy flows across pipelines) potentially occurring in any dimension: infrastructure, source, market and regulation, and geopolitical.
- Reliability: it mainly covers operational security, flexibility and adequacy.
- (Absence of) vulnerability: it mainly covers robustness and resilience (linked to safeguardability).
- A multi-stakeholder and multi-disciplinary problem. Numerous and diversified players interact in different fields, spatial scales and time frames of the electricity security problem. Electricity security stakeholders with different backgrounds, interests and expertise fields (political, economic, regulatory, scientific, technical, etc.) are involved in observing, assessing and safeguarding electricity security. They include: scientists, academics, project developers, policy decision makers, regulators, practitioners, system operators, market operators, generation companies, asset owners, aggregators, manufacturers, consumers, emerging actors (offering new services and/or proposing new business models) [23,24,25,26].
- Both a complicated and complex problem. Electricity security can “just” be addressed as a complicated problem—the electricity grid is often defined as the most complicated man-made machinery ruled by nonlinear equations—or as a complex problem, where very diverse actors interact in multiple dimensions (infrastructure, source, market and regulation, geopolitical) and layers (component, communication, information, function and business) and whose collective/systemic behaviour can be hardly described by closed mathematical formulations.
- A multi-model problem. Several models are deployed, either independently or in combination, and they can be grouped in the following clusters: dynamic power system/grid models, static power system/grid models, power market/system models, energy system/power market models .
- A multi-assessment approach problem. Mirroring the grouping of the electricity security properties, three main electricity security assessment approaches are identified:
- Reliability methodologies (generally addressing operational security, flexibility and adequacy), focusing on the ability of the system to accomplish its intended function .
- Solutions for integrated analyses, like those based upon cost-benefit analyses, multi-criteria analyses and indicators, are also deployed .
- A multi-action problem. Decision makers can promote/deploy several courses of actions to prevent, mitigate and respond to electricity security threats. Depending on the time scale, stakeholders can resort to operational actions, operational planning and scheduling actions, system planning actions, strategic energy planning (and engineering design) actions to safeguard electricity security [15,16].
3. Electricity Security Models and Approaches
- The dynamic power system/grid models provide a detailed short-term description of the power system, grid and protection components. They mainly target the infrastructure dimension of electricity security, i.e., they portray as endogenous factors/variables belonging to the electricity value chain. The typical time horizon is up to seconds (minutes) and the time steps are in the order of milliseconds or their fractions. The dynamic power system/grid models necessarily embed a static model of the power system/grid (see the next bullet point).
- The static power system/grid models offer detailed (component by component) representations of the power grid. The static power system/grid models mainly target as endogenous the infrastructure dimension (some elements of the source dimension might be included). The typical time horizon is one or several years. The time steps largely vary depending on the very different models within this cluster (power flow, topological, graph-based, etc.): they might not even be specified (when studying system snapshots or topological features) or they could typically be hours or fractions of hours.
- The power market/system models generally represent the demand-supply equilibrium, and might use simplified assumptions to describe the grid (“single node” or more detailed representations). They mainly consider as endogenous factors within the infrastructure and the primary energy source dimensions, as well as some aspects of the market and regulation dimension. The typical time horizon is one to several years and the typical time steps are hours/weeks (or weeks/months).
- The energy system/power market models represent the whole energy system and selected portions of the power system/market. They target the source and the market and regulation dimensions (the latter, as well as the geopolitical dimension, may be exogenous to the model). The typical time horizon is up to years or decades and the typical time steps are weeks/months (i.e., a few ten time slices per year).
- The reliability assessment approaches—generally addressing operational security, flexibility and adequacy—target the capacity of the system to perform its intended role and are traditionally used in power system operation, design and planning. Two main methods are employed: deterministic and probabilistic; the deterministic methods are simpler, requires little data and are somehow easier to communicate to policy decision makers; however, they cannot account for inherent stochastic features (e.g., load and renewable energy forecast errors); the probabilistic methods, increasingly more used, are based on the risk models which combine system components reliability performances. Reliability analyses provide insights on the likely system behaviour, in terms of indices defining frequency, duration and magnitude of the expected failures. This information allows decision makers to understand the general capacity of the system to accomplish its intended role and what are some of the causes generating system unreliability. Reliability targets—typically based on historical patterns and common practices—are generally fixed ex ante. Since reliability analyses focus on the likely system behaviour, events assessed to have low probability/frequency of incidence do not grandly—or at all—impact the results (rare events can cover a large fraction of the consequences on the system) [38,39].
- The vulnerability assessment approaches—generally addressing the lack of resilience and robustness—focus on the weakness of the network to withstand strains and on the effects of the consequent failures. Reliability analyses illustrate the probable behaviour of the system, but fail to detect less likely scenarios with higher consequences—these are targeted by vulnerability analyses. These latter ones include emerging approaches used within critical infrastructure management. Vulnerability analyses are less concerned with understanding the role of frequency/probability of failures; their emphasis is more on the identification of system flaws accessible to unknown threats, following a system failure or strain. Aspects like threats interdependence, adverse events/failure propagation cannot be easily captured by reliability analyses [43,44,45,46,47,48,49,50,51].
- Cost-benefit analyses. A balance should exist between the benefits and the costs of improving the security of the energy system. Ideally, also from a societal perspective, as many benefits and costs as possible should be monetised so that the interests of all the stakeholders are properly reflected. However monetary valuation can hardly be used when there is no thorough knowledge on the security threats, the severity of the impact and the prevention possibilities. Other approaches may be used (e.g., multi-criteria analyses and indicators) when not enough information is available [57,58]
- Indicators. Also named complex or composite indicators, they are created by merging into a single index the results from several quantitative indicators. This index value can be read as a representation of an overall level of ‘insecurity’. A scoring system is needed as well as a weighting system to generate an index value [39,59,60,61]
4. Electricity Security Stakeholder Interactions and Actions
- At national level, even if each EU Member State is still largely in charge of the energy security assessment and safeguard, stakeholders’ roles and responsibilities greatly differ. Member States assess different electricity security risks, consider different crisis scenarios, take different emergency measures at different times in response, roles and responsibilities differ. The main electricity security actors are the governmental/regulatory bodies and the Transmission System Operators (TSOs). Member States behave very differently to prevent, prepare and manage crisis situations and national rules and practices tend to disregard what happens across borders. The TSOs own very detailed datasets and dynamic and static models of the national transmission system under their responsibility. The further modelling moves away from grids towards market/energy systems, the larger is the number of actors, including market operators, having a stake (in terms of data ownership) and playing a role (in terms of assessment perspectives). Electricity security models are used for supporting decision making across all the electricity security actions—operation, operational planning and scheduling, system planning, strategic energy planning. The scientific community (R&D actors) frequently contribute to electricity security analyses and propose methodological improvements, however it generally lacks reliable data for the models. The whole range of electricity security analyses is conducted, both on reliability (operational security, flexibility, adequacy) and vulnerability (resilience and robustness) aspects. Electricity models, from the time frame viewpoint, tend to be more and more combined or at least soft linked; probabilistic approaches (vs. deterministic ones) are increasingly used—but their results are not necessarily embedded in the decision making process—for reliability analyses, whereas vulnerability analyses rely upon the most diversified (and not necessarily sophisticated) approaches, also because there is no common understanding of electricity crisis situations and scenarios [20,23,36].
- At the regional (cross-national) level, there are emerging actors which started performing electricity security analyses and actions: particularly, the Pentalateral Energy Forum (PLEF), the Nordic Contingency Planning and Crisis Management Forum (NordBER) and other nascent regional operational initiatives (see Figure 5), including the Coordination of Electricity System Operators (CORESO), the Transmission System Operator Security Cooperation (TSC) and—beyond the EU—the Security Coordination Center (CSC). Also, R&D actors are less active than at national and EU level as the regional scale represents a rather recent EU development and entails different cooperation efforts. Electricity models are quite detailed and (compared to the ones at the national scale) better capture the cross-border static and dynamic aspects of the region under study. The electricity security models are used more to support operational planning & scheduling actions and system planning actions (since operational actions and strategic energy planning actions are beyond the current remit of these regional bodies). As for the electricity security analyses, reliability assessments seem to have priority on vulnerability analyses: even though the network codes set out harmonised technical principles for operation planning and scheduling processes (required to anticipate real time operation security issues), common/harmonised administrative and political approaches to help national authorities to prevent and manage crisis situations in co-operation with each other are missing in most EU’s regions and countries. Time-wise, selected electricity security models are better linked and probabilistic approaches (vs deterministic ones) begin to be used for reliability analyses [65,66,67,68,69,70]
- At the EU level, the main actors are the European Network of Transmission System Operators for Electricity (ENTSO-E), the Agency for the Cooperation of Energy Regulators (ACER) and the European Commission. ENTSO-E is tasked to perform EU-wide analysis and coordinated national/regional studies. ENTSO-E is progressing well in combining primarily static power system/grid models with power market/system models. As explained above for the regional scale, the electricity security models are used for supporting decision making (especially) on operational planning and scheduling actions and system planning actions, (rather than on) operational actions and strategic energy planning actions. In the scientific area, several R&D projects produce advanced models although with partially representative datasets (in the absence of formal agreements with the system operators/data owners). Probabilistic approaches (vs. deterministic ones) begin to be proposed in the reliability assessment area, particularly for power system adequacy and flexibility. As for vulnerability, the Critical Infrastructure Protection initiatives have mainly encouraged bilateral instead of truly supra-national cooperation. At this level, the visibility/observability of dynamics/issues occurring at regional/local level is somewhat limited [71,72,73,74]
- Operational actions (generally short-term): transient/dynamic stability management, pre-fault and post-fault remedial actions (based on contingency analyses) and system balancing.
- Operational planning and scheduling actions (generally mid-term): forecasting, power scheduling, ancillary service procurement, outage coordination and asset management.
- Planning actions (generally long-term): system (network) optimisation, enhancement and expansion.
- Strategic energy planning actions (generally long-term): strategic energy planning/provision and wide ranging policy and regulatory initiatives (impacting the energy system beyond the electricity system).
5. A Novel Electricity Security Decision-Analytic Framework
5.1. Governance Features
- Multi-stakeholder platforms, with proper governance and structured interaction mechanisms, should be further developed at all spatial scales—national, regional and pan-European—to carry out harmonised assessments and concerted actions in the electricity security field.
- The regional scale of decision making should be fostered and streamlined. The current regional pilots offer valuable experience and lessons learned; still, harmonising the geographical/physical boundaries of the regions, given the host and the variable geometry of the initiatives currently in place, is a prerequisite.
- More collaborative and integrated security analyses—again at a wider geographical scale (than the traditional national one)—should be performed to combine different electricity security aspects and properties. Improved electricity security analyses should take into account the different perspectives/interests of the electricity system stakeholders. Additionally, given the interdependence of the main energy policy objectives—security, affordability and sustainability—these integrated security analyses, even if focused on electricity security, should be framed in a wider socio-economic context.
- Cooperative decision making mechanisms, steering the coordinated implementation of concerted actions stemming from the integrated security analyses, should be established. Even if the best spatial scale would be the EU-wide or continental one, since addressing security issues does not just entail solving technical problems but also letting several actors and decision makers interact effectively, it may turn out as more doable to implement regional (cross-national) electricity security analyses-actions, also considering the evolving EU policy framework.
5.2. Strategic Features
- All the electricity security dimensions should be assessed: infrastructure, sources, market and regulation, and geopolitics. The electricity security assessment methodologies should be better able to observe and interpret the interactions of the electricity value chain system with the wider energy system and the other dimensions.
- Smart/super grid and multi-energy carrier systems assessments should be intensified. The modelling efforts in emerging areas—like distributed energy resources, end user’s demand response—shall be boosted with the aim to integrate these aspects in wider national/regional models. On the same note, the modelling efforts and the electricity security analysis on super grids shall be interlinked with the modelling efforts on smart grids since major tensions are emerging at the transmission-distribution interface.
- Electricity security analyses should expand from covering electricity flow/commodity security to including electricity service security. This could help identifying different means and pathways to safeguard security and identify different threats and opportunities throughout the supply chain (e.g., linked to demand response).
- Emerging vulnerability assessment approaches—increasingly based on complex network science—should be promoted further, also at the regional scale, to complement reliability assessment approaches—focusing more on how the system should work.
- A deeper interplay between complex network and engineering approaches should be pursued as both disciplines have their distinguishing features and might be instrumental to assessing different aspects of electricity security.
5.3. Methodological Features
- Stakeholders should agree upon common definitions of crucial electricity security properties—particularly: flexibility, resilience and robustness—which (differently from other attributes like operational security and adequacy) are not consented at the EU level.
- Cost-benefit analyses should be preferred to multi-criteria analyses whenever doable in reliability studies. However this methodology can hardly be used in vulnerability analyses.
- Multi-criteria analyses and indicators should be used to help in decision making under uncertainty if economic/financial information is not available. Multi-criteria analyses can be used to analyse both qualitative and quantitative aspects. Composite indicators, aggregating data—coming from model outputs and/or expert opinions—over time and/or space, are generally easier to communicate but might conceal and/or underestimate specific security properties.
- Sensitivity analyses should be embedded in security analyses. Sensitivity analyses can indeed help systemically explore different scenarios and range variations of factors/variables and can help understanding how initial assumptions and boundary conditions influence the results of the models.
- Energy system/power market models, Power market/system models, Static power system/grid models and Dynamic power system/grid models would need to be utilised—and, depending on cases, soft or hard linked—in so far as they address complementary electricity security aspects and properties.
- Flexibility should be increasingly used as driver for modelling integration in the reliability analysis area. A consented flexibility assessment approach can help identify the required modifications to system operations and increase renewable energy integration and acceptance.
- Probabilistic approaches should complement and—in specific assessment areas (e.g., flexibility and adequacy of power systems with high penetration of renewables)—largely supplant the deterministic approaches when assessing reliability aspects of the electricity security problem.
5.4. Enabling Features
- Advanced model-based and Geographic Information System (GIS)-based visual analytics should be extensively adopted to support the interactions with the policy makers while presenting, analysing and interpreting electricity security scenarios/results.
- Decision makers and analysts should take advantage of supercomputers, real time simulators and parallel processing to develop detailed full-scale models of the power grids, and possibly make the high performance computing technology available for real-time daily operations.
- Reliable, representative datasets should be made available to researchers and analysts.
Conflicts of Interest
- European Commission. Energy Union Package, A Framework Strategy for a Resilient Energy Union with a Forward-Looking Climate Change Policy; European Commission: Brussels, Belgium, 2015. [Google Scholar]
- European Commission. A Policy Framework for Climate and Energy in the Period from 2020 to 2030; COM(2014) 15 Final; European Commission: Brussels, Belgium, 2014. [Google Scholar]
- European Commission. European Energy Security Strategy; COM(2014) 330 Final; European Commission: Brussels, Belgium, 2014. [Google Scholar]
- European Parliament and Council of the European Union. Directive 2005/89/EC Concerning Measures to Safeguard Security of Electricity Supply and Infrastructure Investment; European Parliament and Council of the European Union: Brussels, Belgium, 2005. [Google Scholar]
- European Commission. Proposal for a Regulation of the European Parliament and of the Council on Risk-Preparedness in the Electricity Sector and Repealing Directive 2005/89/EC; COM(2016) 862 Final; European Commission: Brussels, Belgium, 2016. [Google Scholar]
- European Commission. European Programme for Critical Infrastructure Protection; COM(2006) 786 Final; European Commission: Brussels, Belgium, 2006. [Google Scholar]
- European Parliament and Council of the European Union. Directive 2009/72/EC Concerning Common Rules for the Internal Market in Electricity; European Parliament and Council of the European Union: Brussels, Belgium, 2009. [Google Scholar]
- European Parliament and Council of the European Union. Directive (EU) 2016/1148 Concerning Measures for a High Common Level of Security of Network and Information Systems across the Union; European Parliament and Council of the European Union: Brussels, Belgium, 2016. [Google Scholar]
- European Commission. EU Energy Trends to 2030; European Commission: Brussels, Belgium, 2009–2010. [Google Scholar]
- European Commission. Energy Roadmap 2050; COM(2011) 885 Final; European Commission: Brussels, Belgium, 2011. [Google Scholar]
- European Commission. State of the Energy Union; COM(2015) 572 Final; European Commission: Brussels, Belgium, 2015. [Google Scholar]
- Panteli, M.; Mancarella, P. The Grid: Stronger, Bigger, Smarter: Presenting a Conceptual Framework of Power System Resilience. IEEE Power Energy Mag. 2015, 13, 58–66. [Google Scholar] [CrossRef]
- Bompard, E.; Fulli, G.; Ardelean, M.; Masera, M. It’s a Bird, It’s a Plane, It’s a ... Supergrid! Evolution, Opportunities, and Critical Issues for Pan-European Transmission. IEEE Power Energy Mag. 2014, 12, 40–50. [Google Scholar]
- Bompard, E.; Huang, T.; Wu, Y.; Cremenescu, M. Classification and trend analysis of threats origins to the security of power systems. Int. J. Electr. Power Energy Syst. 2013, 50, 50–64. [Google Scholar] [CrossRef]
- Fulli, G. Electricity Security: Models and Methods for Supporting the Policy Decision Making in the European Union. Ph.D. Thesis, Politecnico di Torino, Turin, Italy, 2016. [Google Scholar]
- International Education Association (IEA). Learning from the Blackout; IEA: Paris, France, 2005. [Google Scholar]
- Gracceva, F.; Zeniewski, P. A systemic approach to assessing energy security in a low-carbon EU energy system. Appl. Energy 2014, 123, 335–348. [Google Scholar] [CrossRef]
- Hosseini, S.; Barker, K.; Ramirez-Marquez, J.E. A Review of Definitions and Measures of System Resilience. Reliab. Eng. Syst. Saf. 2016, 145, 47–61. [Google Scholar] [CrossRef]
- Johansson, M.B.; Nilsson, L.J. Assessing energy security: An overview of commonly used methodologies. Energy 2014, 73, 1–14. [Google Scholar]
- Johansson, J.; Hassel, H.; Zio, E. Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems. Reliab. Eng. Syst. Saf. 2013, 120, 27–38. [Google Scholar] [CrossRef]
- Allan, R.; Billinton, R. Probabilistic assessment of power systems. Proc. IEEE 2000, 88, 140–162. [Google Scholar] [CrossRef]
- Sarewitz, D.; Pielke, R., Jr.; Keykhah, M. Vulnerability and risk: Some thoughts from a political and policy perspective. Risk Anal. 2003, 23, 805–810. [Google Scholar] [CrossRef] [PubMed]
- European Commission. Review of Current National Rules and Practices Relating to Risk Preparedness in the Area of Security of Electricity Supply—Final Report; European Commission: Brussels, Belgium, 2014. [Google Scholar]
- Agency for the Cooperation of Energy Regulators (ACER). Regional Initiatives Status Review Report; ACER: Ljubljana, Slovenia, 2014.
- Council of European Energy Regulators (CEER). Security of Electricity Supply Report; CEER: Brussels, Belgium, 2004. [Google Scholar]
- Pierre, I. Security of Electricity Supply—Roles, responsibilities and experiences within the EU; Eurelectric–Union of the Electricity Industry: Brussels, Belgium, 2006. [Google Scholar]
- Kröger, W.; Zio, E. Vulnerable Systems; Springer: London, UK, 2011. [Google Scholar]
- Aven, T. On some recent definitions and analysis frameworks for risk, vulnerability, and resilience. Risk Anal. 2011, 31, 515–522. [Google Scholar] [CrossRef] [PubMed]
- Cuadra, L.; Salcedo-Sanz, S.; del Ser, J.; Jiménez-Fernández, S.; Geem, Z.W. A Critical Review of Robustness in Power Grids Using Complex Networks Concepts. Energies 2015, 8, 9211–9265. [Google Scholar] [CrossRef]
- Deane, J.P.; Gracceva, F.; Chiodi, A.; Gargiulo, M.; Gallachóir, B.P.Ó. Assessing power system security. A framework and a multi model approach. Int. J. Electr. Power Energy Syst. 2015, 73, 283–297. [Google Scholar]
- Söderholm, P. Fuel flexibility in the West European power sector. Resour. Policy 2000, 26, 157–170. [Google Scholar] [CrossRef]
- Denholm, P.; Hand, M. Grid Flexibility and Storage Required to Achieve Very High Penetration of Variable Renewable Electricity. Energy Policy 2011, 39, 1817–1830. [Google Scholar] [CrossRef]
- Chaudry, M.; Ekins, P.; Ramachandran, K.; Shakoor, A.; Skea, J.; Strbac, G.; Wang, X.; Whitaker, J. Building a Resilient UK Energy System; UK Energy Research Centre: London, UK, 2011. [Google Scholar]
- Poncelet, K.; Delarue, E.; Duerinck, J.; Six, D.; D’haeseleer, W. The Importance of Integrating the Variability of Renewables in Long-Term Energy Planning Models; KU Leuven: Leuven, Belgium, 2014. [Google Scholar]
- Ventosa, M.; Baillo, Á.; Ramos, A.; Rivier, M. Electricity market modeling trends. Energy Policy 2005, 33, 897–913. [Google Scholar] [CrossRef]
- Foley, A.M.; Gallachóir, B.P.Ó.; Hur, J.; Baldick, R.; McKeogh, E.J. A strategic review of electricity systems models. Energy 2010, 35, 4522–4530. [Google Scholar] [CrossRef]
- González, H.; Castello, P.R.; Sgobbi, A.; Nijs, W.; Quoilin, S.; Zucker, A.; Thiel, C. Addressing flexibility in energy system models. JRC Sci. Policy Rep. 2015. [Google Scholar] [CrossRef]
- Aien, M.; Hajebrahimi, A.; Fotuhi-Firuzabad, M. A comprehensive review on uncertainty modeling techniques in power system studies. Renew. Sustain. Energy Rev. 2016, 57, 1077–1089. [Google Scholar] [CrossRef]
- Martínez-Anido, C.B.; Bolado, R.; de Vries, L.; Fulli, G.; Vandenbergh, M.; Masera, M. European power grid reliability indicators, what do they really tell? Electr. Power Syst. Res. 2012, 90, 79–84. [Google Scholar] [CrossRef]
- O’Sullivan, J.; Rogers, A.; Flynn, D.; Smith, P.; Mullane, A.; O’Malley, M. Studying the Maximum Instantaneous Non-Synchronous Generation in an Island System—Frequency Stability Challenges in Ireland. IEEE Trans. Power Syst. 2014, 29, 2943–2951. [Google Scholar]
- Holttinen, H.; Tuohy, A.; Milligan, M.; Lannoye, E.; Silva, V.; Müller, S.; Sö, L. The Flexibility Workout: Managing Variable Resources and Assessing the Need for Power System Modification. IEEE Power Energy Mag. 2013, 11, 53–62. [Google Scholar] [CrossRef]
- Koppelaar, R.H.E.M.; Keirstead, J.; Shah, N.; Woods, J. A review of policy analysis purpose and capabilities of electricity system models. Renew. Sustain. Energy Rev. 2016, 59, 1531–1544. [Google Scholar]
- Baldick, R.; Chowdhury, B.; Dobson, I.; Dong, Z.; Gou, B.; Hawkins, D.; Huang, H.; Joung, M.; Kirschen, D.; Li, F.; et al. Initial review of methods for cascading failure analysis in electric power transmission systems. In Proceedings of the IEEE PES CAMS Task Force on Understanding, Prediction, Mitigation and Restoration of Cascading Failures, Power and Energy Society General Meeting, Pittsburgh, PA, USA, 20–24 July 2008; pp. 1–8. [Google Scholar]
- Dobson, I.; Carreras, B.A.; Newman, D.E. A loading dependent model of probabilistic cascading failure. Probab. Eng. Inf. Sci. 2005, 19, 15–32. [Google Scholar] [CrossRef]
- Dobson, I.; Carreras, B.A.; Lynch, V.E.; Newman, D.E. An initial model for complex dynamics in electric power system blackouts. In Proceedings of the 34th Hawaii International Conference on System Sciences, Maui, HI, USA, 3–6 January 2001; pp. 710–718. [Google Scholar]
- Jansen, J.C.; Seebregts, A.J. Long-term energy services security: What is it and how can it be measured and valued? Energy Policy 2010, 38, 1654–1664. [Google Scholar] [CrossRef]
- Haimes, Y.Y.; Crowther, K.; Horowitz, B.M. Homeland security preparedness: Balancing protection with resilience in emergent systems. Syst. Eng. 2008, 11, 287–308. [Google Scholar] [CrossRef]
- O’Brien, G.; Hope, A. Localism and energy: Negotiating approaches to embedding resilience in energy systems. Energy Policy 2010, 38, 7550–7558. [Google Scholar]
- Yusta, J.M.; Correa, G.J.; Lacal-Arantegui, R. Methodologies and applications for critical infrastructure protection: State-of-the-art. Energy Policy 2011, 39, 6100–6119. [Google Scholar] [CrossRef]
- Carreras, B.A.; Lynch, V.; Dobson, I.; Newman, D.E. Complex dynamics of blackouts in power transmission systems. Chaos 2004, 14, 643–652. [Google Scholar] [CrossRef] [PubMed]
- Bompard, E.; Napoli, R.; Xue, F. Analysis of structural vulnerabilities in power transmission grids. Int. J. Crit. Infrastruct. Prot. 2009, 2, 5–12. [Google Scholar]
- Rosas-Casals, M.; Bologna, S.; Bompard, E.; D’Agostino, G.; Ellens, W.; Pagani, G.A.; Scala, A.; Verma, T. Knowing power grids and understanding complexity science. Int. J. Crit. Infrastruct. 2015, 11, 4–14. [Google Scholar] [CrossRef]
- Hines, P.; Cotilla-Sanchez, E.; Blumsack, S. Do topological model provide good information about electricity infrastructure vulnerability? Chaos 2010, 20, 033122. [Google Scholar] [CrossRef] [PubMed]
- Buzna, L.; Issacharoff, L.; Helbing, D. The evolution of the topology of high-voltage electricity networks. Int. J. Crit. Infrastruct. 2009, 5, 72–85. [Google Scholar] [CrossRef]
- Pagani, G.A.; Aiello, M. The Power Grid as a complex network: A survey. Phys. A Stat. Mech. Appl. 2013, 392, 2688–2700. [Google Scholar] [CrossRef]
- Rinaldi, S.M.; Peerenboom, J.P.; Kelly, T.K. Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst. 2001, 21, 11–25. [Google Scholar] [CrossRef]
- Forsten, K. The integrated grid—A Benefit-Cost Framework; Electric Power Research Institute (EPRI): Palo Alto, CA, USA, 2015. [Google Scholar]
- European Network of Transmission System Operators (ENTSO-E), Guidelines for Cost Benefit Analysis of Grid Development Projects; ENTSO-E: Brussels, Belgium, 2015.
- Giordano, V.; Vasiljevska, J.; Vitiello, S. Evaluation of Smart Grid Projects within the Smart Grid Task Force Expert Group 4; JRC Scientific and Policy Report; Publications Office of the European Union: Brussels, Belgium, 2013. [Google Scholar]
- Portugal-Pereira, J.; Esteban, M. Implications of paradigm shift in Japan’s electricity security of supply: A multi-dimensional indicator assessment. Appl. Energy 2014, 123, 424–434. [Google Scholar]
- Andzsans-Balogh, K.; Gregor, A.; Habis, H.; Kaderják, P.; Kerekes, L.; Kiss, A.; Mezősi, A.; Pató, Z.; Szolnoki, P.; István Tóth, A.I.; et al. Security of energy supply in Central and South-East Europe; Aula Kiadó: Budapest, Hungary, 2011. [Google Scholar]
- Huang, Z.; Nieplocha, J. Transforming power grid operations via high performance computing. In Proceedings of the 2008 IEEE Power and Energy Society General Meeting—Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA, USA, 20–24 July 2008; pp. 1–8. [Google Scholar]
- Nga, D.V.; See, O.H.; Quang, N.; Xuen, C.Y.; Chee, L.L. Visualization Techniques in Smart Grid. Smart Grid Renew. Energy 2012, 3, 175–185. [Google Scholar]
- National Academies of Sciences, Engineering, and Medicine. Analytic Research Foundations for the Next-Generation Electric Grid; The National Academies Press: Washington, DC, USA, 2016. [Google Scholar]
- Pentalateral Energy Forum (PLEF). Second Political Declaration; PLEF: Brussels, Belgium, 2015. [Google Scholar]
- Nordic Contingency Planning and Crisis Management (NCPCM), The Nordic Forum for Emergency Matters Regarding the Power Sector; NCPCM: Laxå, Sweden, 2005.
- Coordination of Electricity System Operators (CORESO). Available online: www.coreso.eu (accessed on 11 January 2017).
- Transmission System Operator Security Cooperation (TSC). Available online: www.tscnet.eu (accessed on 11 January 2017).
- Security Coordination Centre (SCC). Available online: www.scc-rsci.com (accessed on 11 January 2017).
- European Commission. Ecorys, ECN, DNV GL, Options for Future European Electricity System Operation; European Commission: Brussels, Belgium, 2015. [Google Scholar]
- European Network of Transmission System Operators (ENTSO-E). Ten Year Network Development Plan; ENTSO-E: Brussels, Belgium, 2014. [Google Scholar]
- European Network of Transmission System Operators (ENTSO-E). Regional Cooperation and Governance in the Electricity Sector; Policy Paper; ENTSO-E: Brussels, Belgium, 2016. [Google Scholar]
- European Network of Transmission System Operators (ENTSO-E). Target Methodology for Adequacy Assessment; Updated Version after Consultation; ENTSO-E: Brussels, Belgium, 2014. [Google Scholar]
- European Network of Transmission System Operators (ENTSO-E). Scenario Outlook & Adequacy Forecast; ENTSO-E: Brussels, Belgium, 2015. [Google Scholar]
- Rodilla, P.; Batlle, C. Security of electricity supply at the generation level: Problem analysis. Energy Policy 2012, 40, 177–185. [Google Scholar] [CrossRef]
|Model Cluster||Time Horizon||System Representation Detail|
|Short Term||Mid Term||Long Term||Very Long Term||Energy System||Power Market||Power System/Gird|
|Dynamic power system/grid models||X||-||-||-||-||-||H|
|Dynamic power system/grid models||X||X||X||-||-||M||H|
|Power market/system models||X||X||X||-||-||H||M/l|
|Energy system/power market models||-||X||X||X||H||H/m||-|
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Fulli, G.; Masera, M.; Covrig, C.F.; Profumo, F.; Bompard, E.; Huang, T. The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments. Energies 2017, 10, 425. https://doi.org/10.3390/en10040425
Fulli G, Masera M, Covrig CF, Profumo F, Bompard E, Huang T. The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments. Energies. 2017; 10(4):425. https://doi.org/10.3390/en10040425Chicago/Turabian Style
Fulli, Gianluca, Marcelo Masera, Catalin Felix Covrig, Francesco Profumo, Ettore Bompard, and Tao Huang. 2017. "The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments" Energies 10, no. 4: 425. https://doi.org/10.3390/en10040425