Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/102125
Title: Optimal policy identification: Insights from the German electricity market
Authors: Herrmann, J. K.
Savin, I.
Issue Date: 2017
Publisher: Elsevier Inc.
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.
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.
Keywords: DIFFERENTIAL EVOLUTION
ELECTRICITY STORAGE
ENERGY GRID
FEED-IN TARIFF
RENEWABLE ENERGY
BUDGET CONTROL
COMMERCE
ELECTRIC ENERGY STORAGE
ELECTRIC POWER UTILIZATION
EVOLUTIONARY ALGORITHMS
OPTIMIZATION
POWER MARKETS
DIFFERENTIAL EVOLUTION
ELECTRICITY STORAGES
ENERGY GRIDS
FEED-IN TARIFF
RENEWABLE ENERGIES
ELECTRIC POWER TRANSMISSION NETWORKS
ALGORITHM
ELECTRICITY GENERATION
ELECTRICITY SUPPLY
ENERGY MARKET
FUTURE PROSPECT
POLICY ANALYSIS
POLICY IMPLEMENTATION
POLICY MAKING
RENEWABLE RESOURCE
TARIFF STRUCTURE
GERMANY
URI: http://elar.urfu.ru/handle/10995/102125
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85019064081
WOS ID: 000407184300007
PURE ID: 9b3a3abc-59ed-48cc-8883-1a592eb58e63
1971245
ISSN: 401625
DOI: 10.1016/j.techfore.2017.04.014
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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