The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments

Fulli, Gianluca; Masera, Marcelo; Covrig, Catalin-Felix; Profumo, F.; Bompard, Ettore; Huang, Tao

doi:10.3390/en10040425

Cited by 9 publications

(2 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our research aims at increasing energy efficiency by supporting the user-specific selection of DR methods that are used on HEMS in residential buildings (here Smart Homes) (Goebel et al 2014). Similar research activities fail to compare, evaluate, and benchmark DR methods, although they address, for example, distributed and renewable energy resources (e.g., (Berthold et al 2017;Dyson et al 2014)), islanded grids (e.g., (Vergara et al 2018; Ma and Billanes 2016)) or grids in general (e.g., (Steinbrink et al 2017)), the energy grid in smart cities (e.g., (Masera et al 2018;Stoyanova et al 2017)), security concerns (e.g., (Fulli et al 2017)), EVs and batteries in general (e.g., (Park et al 2016;Ma et al 2010)), energy contracts (e.g., (Basmadjian et al 2016)), or data and privacy concerns (e.g., (Cupelli et al 2018)).…”

Section: Related Workmentioning

confidence: 99%

Empowering the selection of demand response methods in smart homes: development of a decision support framework

et al. 2018

View full text Add to dashboard Cite

Demand Response (DR) facilitates the monitoring and management of appliances in energy grids by employing methods that, for example, increase the reliability of energy grids and reduce users' cost. Within energy grids, Smart Home scenarios can be characterized by a unique combination of appliances and user preferences. To increase their impact, a scenario-specific selection of the best performing DR methods is necessary. As the user faces a multitude of heterogeneous DR methods to choose from, a complex decision problem is present. The primary goal of this study is to develop a decision support framework that can determine the bestperforming DR methods. Building on literature analyses, expert workshops and expert interviews, we identify seven requirements, derive solution concepts addressing these requirements, and develop the framework by combining the concepts using a benchmarking process as a template. To demonstrate the framework's applicability, we conduct a simulation study that uses artificial (simulated) data for seven types of households. Within this study, we employ four DR methods, assume changing appliances over time and cost minimization as primary objective. The study indicates, that by using the framework and thus by identifying and using the best DR method for each scenario, the users can achieve further cost benefits. The application of the framework allows practitioners to increase the efficiency of the DR method selection process and to further enhance DR-related benefits, such as cost minimization, load profile flattening, and peak load reduction. Researchers benefit from guidance for benchmarking and evaluating DR methods.

show abstract

Section: Related Workmentioning

confidence: 99%

Empowering the selection of demand response methods in smart homes: development of a decision support framework

et al. 2018

View full text Add to dashboard Cite

show abstract

“…With regard to the concept of electricity security, energy transition is a systemic threat [20]. The motivation to finance electricity infrastructure, as in the case of Slovakia, is based on vulnerabilities that may arise from the exclusion of coal from the energy mix.…”

Section: Introductionmentioning

confidence: 99%

Regional Energy Transition: An Analytical Approach Applied to the Slovakian Coal Region

2020

View full text Add to dashboard Cite

This study presents an analytical framework supporting coal regions in a strategy toward the clean energy transition. The proposed approach uses a combination of value chain analysis and energy sector analysis that enables a comprehensive assessment considering local specificities. Its application to a case study of the Slovakian region Upper Nitra demonstrates practical examples of opportunities and challenges. The value chain analysis evaluates the coal mining industry, from coal extraction to electricity generation, in terms of jobs and business that are at risk by the closure of the coal mines. The complementary energy system analysis focuses on diversification of the energy mix, environmental impacts, and feasibility assessment of alternative energy technologies to the coal combusting sources. The results show a net positive cost benefit for all developed scenarios of replacing the local existing coal power plant. Although the installation of a new geothermal plant is estimated to be the most expensive option from our portfolio of scenarios, it presents the highest CO2 reduction in the electricity generation in Slovakia—34% less compare to the system employing the existing power plant. In addition, the development of a new industrial polo around deep geothermal technology can boost the economic activity in the region by attracting investments in companies providing geological exploration services, transferring the local knowledge from the coal mining industry into an emerging sector.

show abstract

An integrated framework for operational flexibility assessment in multi-period power system planning with renewable energy production

Abdin

Zio

2018

Applied Energy

View full text Add to dashboard Cite

To cite this version:Islam Abdin, Enrico Zio. An integrated framework for operational flexibility assessment in multiperiod power system planning with renewable energy production. Applied Energy, Elsevier, 2018, 222, pp.• Quantitative modeling framework for operational flexibility assessment.• Integration of short-term constraints in generation expansion planning model. • Renewable energy penetration drives flexibility needs higher than carbon limits. A B S T R A C TThis paper proposes an integrated framework for operational flexibility assessment in power system planning with a significant share of intermittent renewable energy sources (RES). The framework proposed includes: (i) the formulation of an integrated generation expansion planning (GEP) and unit commitment (UC) model accounting for key short-term technical constraints, (ii) the elaboration of accurate and systematic horizon reduction methods to alleviate the computational burden of the resulting large-sized optimization problems and (iii) the definition of suitable metrics for the operational flexibility assessment of the obtained plans. The framework is applied to a ten year planning horizon of a realistically sized case study representing the national power system of France, under several scenarios of RES penetration levels and carbon limits, spanning levels of up to 50%. The importance of incorporating the detailed short-term constraints within long-term planning models is shown. The results of the assessment show that, under high renewable energy penetration, neglecting the short-term constraints may lead to plans significantly short on flexibility, reaching shortage levels of up to 50% in frequency and several GWs in magnitude. Also, the load not served reaches levels of up to 3% and carbon emission is underestimated by up to 60%. Furthermore, the results highlight the importance of relying on suitable quantitative metrics for operational flexibility assessment in power systems planning rather than solely relying on generic performance measures, such as system costs and mixes of power plants, which are shown not to sufficiently reflect the flexibility levels of the obtained plans.improvements in the details considered (e.g. reliability and maintenance), policy developments, such as the restructuring of the power sector, renewable energy sources (RES) integration and support schemes, uncertainty and stochasticity modeling, and the consideration of real-options for adaptive power systems design [3].One of the most recent concerns in power systems planning is dealing with the high share of intermittent RES penetration required in the system, driven by strict environmental policies, such as the EU renewable energy directive [4] and its proposed revision [5], and other regional and national targets. The resulting increased variability in the net load (system demand minus RES production) requires that the

show abstract

The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments

Cited by 9 publications

References 41 publications

Empowering the selection of demand response methods in smart homes: development of a decision support framework

Empowering the selection of demand response methods in smart homes: development of a decision support framework

Regional Energy Transition: An Analytical Approach Applied to the Slovakian Coal Region

An integrated framework for operational flexibility assessment in multi-period power system planning with renewable energy production

Contact Info

Product

Resources

About