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http://elar.urfu.ru/handle/10995/102125
Полная запись метаданных
Поле DC | Значение | Язык |
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dc.contributor.author | Herrmann, J. K. | en |
dc.contributor.author | Savin, I. | en |
dc.date.accessioned | 2021-08-31T15:01:57Z | - |
dc.date.available | 2021-08-31T15:01:57Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Herrmann J. K. Optimal policy identification: Insights from the German electricity market / J. K. Herrmann, I. Savin. — DOI 10.1016/j.techfore.2017.04.014 // Technological Forecasting and Social Change. — 2017. — Vol. 122. — P. 71-90. | en |
dc.identifier.issn | 401625 | - |
dc.identifier.other | Final | 2 |
dc.identifier.other | All Open Access, Green | 3 |
dc.identifier.other | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019064081&doi=10.1016%2fj.techfore.2017.04.014&partnerID=40&md5=128549b0ddce7a5438ac208eef497d11 | |
dc.identifier.other | https://publikationen.bibliothek.kit.edu/1000055424/3854092 | m |
dc.identifier.uri | http://elar.urfu.ru/handle/10995/102125 | - |
dc.description.abstract | The diffusion of renewable electricity technologies is widely considered as crucial for establishing a sustainable energy system in the future. However, the required transition is unlikely to be achieved by market forces alone. For this reason, many countries implement various policy instruments to support this process, also by re-distributing related costs among all electricity consumers. This paper presents a novel history-friendly agent-based study aiming to explore the efficiency of different mixes of policy instruments by means of a Differential Evolution algorithm. Special emphasis of the model is devoted to the possibility of small scale renewable electricity generation, but also to the storage of this electricity using small scale facilities being actively developed over the last decade. Both combined pose an important instrument for electricity consumers to achieve partial or full autarky from the electricity grid, particularly after accounting for decreasing costs and increasing efficiency of both due to continuous innovation. Among other things, we find that the historical policy mix of Germany introduced too strong and inflexible demand-side instruments (like feed-in tariff) too early, thereby creating strong path-dependency for future policy makers and reducing their ability to react to technological but also economic shocks without further increases of the budget. © 2017 Elsevier Inc. | en |
dc.format.mimetype | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | Elsevier Inc. | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.source | Technol. Forecast. Soc. Change | 2 |
dc.source | Technological Forecasting and Social Change | en |
dc.subject | DIFFERENTIAL EVOLUTION | en |
dc.subject | ELECTRICITY STORAGE | en |
dc.subject | ENERGY GRID | en |
dc.subject | FEED-IN TARIFF | en |
dc.subject | RENEWABLE ENERGY | en |
dc.subject | BUDGET CONTROL | en |
dc.subject | COMMERCE | en |
dc.subject | ELECTRIC ENERGY STORAGE | en |
dc.subject | ELECTRIC POWER UTILIZATION | en |
dc.subject | EVOLUTIONARY ALGORITHMS | en |
dc.subject | OPTIMIZATION | en |
dc.subject | POWER MARKETS | en |
dc.subject | DIFFERENTIAL EVOLUTION | en |
dc.subject | ELECTRICITY STORAGES | en |
dc.subject | ENERGY GRIDS | en |
dc.subject | FEED-IN TARIFF | en |
dc.subject | RENEWABLE ENERGIES | en |
dc.subject | ELECTRIC POWER TRANSMISSION NETWORKS | en |
dc.subject | ALGORITHM | en |
dc.subject | ELECTRICITY GENERATION | en |
dc.subject | ELECTRICITY SUPPLY | en |
dc.subject | ENERGY MARKET | en |
dc.subject | FUTURE PROSPECT | en |
dc.subject | POLICY ANALYSIS | en |
dc.subject | POLICY IMPLEMENTATION | en |
dc.subject | POLICY MAKING | en |
dc.subject | RENEWABLE RESOURCE | en |
dc.subject | TARIFF STRUCTURE | en |
dc.subject | GERMANY | en |
dc.title | Optimal policy identification: Insights from the German electricity market | en |
dc.type | Article | en |
dc.type | info:eu-repo/semantics/article | en |
dc.type | info:eu-repo/semantics/publishedVersion | en |
dc.identifier.doi | 10.1016/j.techfore.2017.04.014 | - |
dc.identifier.scopus | 85019064081 | - |
local.contributor.employee | Herrmann, J.K., Friedrich Schiller University of Jena, Faculty of Economics and Business Administration, Germany | |
local.contributor.employee | Savin, I., Chair for Economic Policy, Karlsruhe Institute of Technology, Germany, Bureau d'Economie Théorique et Appliquée, UMR 7522 Université de Strasbourg - CNRS, Strasbourg, France, Chair for Econometrics and Statistics, Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russian Federation | |
local.description.firstpage | 71 | - |
local.description.lastpage | 90 | - |
local.volume | 122 | - |
dc.identifier.wos | 000407184300007 | - |
local.contributor.department | Friedrich Schiller University of Jena, Faculty of Economics and Business Administration, Germany | |
local.contributor.department | Chair for Economic Policy, Karlsruhe Institute of Technology, Germany | |
local.contributor.department | Bureau d'Economie Théorique et Appliquée, UMR 7522 Université de Strasbourg - CNRS, Strasbourg, France | |
local.contributor.department | Chair for Econometrics and Statistics, Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russian Federation | |
local.identifier.pure | 9b3a3abc-59ed-48cc-8883-1a592eb58e63 | uuid |
local.identifier.pure | 1971245 | - |
local.identifier.eid | 2-s2.0-85019064081 | - |
local.identifier.wos | WOS:000407184300007 | - |
Располагается в коллекциях: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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2-s2.0-85019064081.pdf | 2,09 MB | Adobe PDF | Просмотреть/Открыть |
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