Yulianto Suharto

Clean energy investment scenarios using the Bayesian network

Clean energy investment decisions are getting more difficult to make due to public reactions. In order to support the policies in the field, analysis of the positive conditions is needed. This research aims to construct the positive scenarios for nuclear energy and renewable energy investments in the state of Oregon, USA. The Bayesian network technique will be used to create the scenarios. Oregon has a wide range of renewable energies; hence, investment is becoming more complex. Criteria affecting the decisions are taken from the literature, but were reviewed with energy authorities in Oregon in order to define the interactions.

Methods and Tools Applied in Strategic Technology Planning

The relationship between strategic technology planning and the overall business strategy has been one of the growing fields that attract much interest both from academic and industry points of view. The increasingly important role that technology plays in today’s business success is well established. The ability to create, modify and maintain the alignment of technology planning to the overall business strategy—as market/business conditions change, new opportunities arise, and new capabilities are developed—can define the success or failure in the market. An increasing number of studies have been carried out over the years, contributing to the development of strategic technology planning literature. However, there has been no effort made to present an overview of the methodologies and tools that have been cited in technology planning literature. This chapter surveys technology plan development using literature review and classification of articles from 1970–2010 with keyword index in order to explore how technology planning methodologies and applications has developed in this period. The main content of the chapter is related to the works published in leading international journals that involve certain research methodologies or techniques.

Technology Assessment: Energy Storage Technologies for Wind Power Generation

The problems in generation imbalance for wind power require multi-criteria analysis for the decision makers. In addition to the required multi-criteria analysis, there is also a problem of uncertainty inherent in future changes as a result of interdependence among these criteria. To counter this two problems, this paper describes a systematic approach of Bayesian causal maps and systematic probability generation method. Bayesian causal maps, which is built from causal maps, is used to develop a proposed framework on scenario-based assessment of energy storage technologies for wind power generation. Causal maps provides a rich representation of ideas, through the modeling of complex structures, representing the chain of arguments, as networks.