The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Lihsing Shih - One of the best experts on this subject based on the ideXlab platform.

  • renewable energy Policy evaluation using real option model the case of taiwan
    Energy Economics, 2010
    Co-Authors: Shun Chung Lee, Lihsing Shih
    Abstract:

    Abstract This study presents a Policy benefit evaluation model that integrates cost efficiency curve information on renewable power generation technologies into real options analysis (ROA) methods. The proposed model evaluates quantitatively the Policy value provided by developing renewable energy (RE) in the face of uncertain fossil fuel prices and RE Policy-related factors. The economic intuition underlying the Policy-making process is elucidated, while empirical analysis illustrates the option value embedded in the current development Policy in Taiwan for wind power. In addition to revealing the benefits that RE development provides when considering real options, analytical results indicate that ROA is a highly effective means of quantifying how Policy Planning uncertainty including managerial flexibility influences RE development. In addition to assessing the Policy value of current RE development Policy, this study also compares Policy values in terms of internalized external costs and varying feed-in tariff (FIT). Simulation results demonstrate that the RE development Policy with internalized CO2 emission costs is appropriate Policy Planning from sustainability point of view. Furthermore, relationship between varying FIT and Policy values can be shown quantitatively and appropriate FIT level could be determined accordingly.

Patricia L. Riley - One of the best experts on this subject based on the ideXlab platform.

Matthew James Keeling - One of the best experts on this subject based on the ideXlab platform.

  • the interaction between vector life history and short vector life in vector borne disease transmission and control
    PLOS Computational Biology, 2016
    Co-Authors: Samuel Brand, Kat S Rock, Matthew James Keeling
    Abstract:

    Epidemiological modelling has a vital role to play in Policy Planning and prediction for the control of vectors, and hence the subsequent control of vector-borne diseases. To decide between competing policies requires models that can generate accurate predictions, which in turn requires accurate knowledge of vector natural histories. Here we highlight the importance of the distribution of times between life-history events, using short-lived midge species as an example. In particular we focus on the distribution of the extrinsic incubation period (EIP) which determines the time between infection and becoming infectious, and the distribution of the length of the gonotrophic cycle which determines the time between successful bites. We show how different assumptions for these periods can radically change the basic reproductive ratio (R0) of an infection and additionally the impact of vector control on the infection. These findings highlight the need for detailed entomological data, based on laboratory experiments and field data, to correctly construct the next-generation of Policy-informing models.

Hamed Zamanisabzi - One of the best experts on this subject based on the ideXlab platform.

  • improving renewable energy Policy Planning and decision making through a hybrid mcdm method
    Energy Policy, 2020
    Co-Authors: R Alizadeh, Leili Soltanisehat, Peter Lund, Hamed Zamanisabzi
    Abstract:

    Abstract Shifting from fossil to clean energy sources is a major global challenge, but in particular for those countries with substantial fossil-fuel reserves and economies depending on fossil-fuel exports. Here we introduce an improved framework for renewable energy Planning and decision-making to help such countries to more effectively harness their abundant renewable energy resources. We use Iran as a case for the analysis. The framework includes identifying and removing barriers that prevent the use of renewables. It is based on combining two models: Benefit, Opportunity, Cost, Risk (BOCR) and Analytic Network Process (ANP) models. In the analyses, the mutual weight of strategic criteria is employed such as technology, economy, energy vulnerability, security, global effects, and human wellbeing. Using the integrated model, we find that solar energy would be the preferential renewable energy source for Iran. Also, the role of infrastructures, policies, and administrative structures in renewable energy to facilitate their development was analyzed. The renewable energy Policy-making framework presented is applicable to other countries as well.

Thomas E. Drennen - One of the best experts on this subject based on the ideXlab platform.

  • Technological learning and renewable energy costs: implications for US renewable energy Policy
    Energy Policy, 2006
    Co-Authors: Peter Holmes Kobos, Jon D Erickson, Thomas E. Drennen
    Abstract:

    This paper analyzes the relationship between current renewable energy technology costs and cumulative production, research, development and demonstration expenditures, and other institutional influences. Combining the theoretical framework of 'learning by doing' and developments in 'learning by searching' with the fields of organizational learning and institutional economics offers a complete methodological framework to examine the underlying capital cost trajectory when developing electricity cost estimates used in energy Policy Planning models. Sensitivities of the learning rates for global wind and solar photovoltaic technologies to changes in the model parameters are tested. The implications of the results indicate that institutional Policy instruments play an important role for these technologies to achieve cost reductions and further market adoption.