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There are many indications that government policymakers and supporters of large-scale nuclear expansion in Poland have not seriously grappled with arguments critical of this direction of the country's power development. Instead, there is a mood of euphoric elation in these circles without even an attempt to reflect on why this kind of nuclear power is in a state of perennial crisis and lack of development prospects in Western countries.

The purpose of this chapter is to consider from an economic perspective the potential role of nuclear power in decarbonising the Polish power sector. It needs to answer two questions: why not develop large-scale nuclear power and why small modular reactors (SMRs) can be a better alternative for decarbonisation of the Polish power sector.

The primary research method used in the preparation of this chapter is a critical analysis and synthesis of the literature on the subject.

A technological revolution will offer electricity customers increasingly better alternatives. Among them there is also technology of SMRs which seems to be much less risky option in terms of its compatibility with the direction of the power sector's evolution as well as cost of sectors’ decarbonisation.

This article aims to explore (1) specific frames of dyadic relationship in policy network beyond a simplistic dichotomy of “friend or foe” and (2) the multi-dimensional drivers behind the framing patterns.

To that end, the interviews with the key actors in a nuclear energy policy network in South Korea were conducted, and their relationships in terms of three dimensions were analyzed: belief accordance, communication frequency and resource symmetry.

As a result, 12 relationships that can occur in the policy networks were identified: helping, collaborating, cooperating, unconcerned, stabilizing, observing, pushing, confronting, challenging, ignoring, watching and avoiding. These 12 frames were observed in various in-/congruent patterns between network actors.

The findings provide theoretical and practical implications on why and how the network actors may assess one another through the 12 discrete frames, which are drawn from the three dimensional drivers of belief accordance, communication frequency and resource symmetry.

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.

This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.

The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.

If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.

The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.

The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.

This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.

Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.

By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.

First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.

This study is a targeted review of some of the major changes in European regulation that guided energy policy decisions in the Iberian Peninsula and how they may have aggravated the problem of lack of flexibility. This study aims to assess some of the proposed short-term solutions to address this issue considering the underlying root causes and suggests a different course of action, that in turn, could help alleviate future market strains.

The evolution of the most important (macro) energy and price-related variables in both Portugal and Spain is assessed using market and grid operator data. In addition, the authors present critical viewpoints on some of the most recent EU and national regulation changes (official document analysis).

The Iberian energy policy and regulatory agenda has successfully promoted a rapid adoption of renewables (main goal), although with insufficient diversification of generation technologies. The compulsory closings of thermal plants and an increased tax (mainly carbon) added pressure toward more environmentally friendly thermal power plants. However, inevitably, this curbed the bidding price competitiveness of these producers in an already challenging market framework. Moving forward, decisions must be based on “a bigger picture” that does not neglect system flexibility and security of supply and understands the specificities of the Iberian market and its generation portfolio.

This work provides an original account of unprecedented spikes in energy prices in 2021, specifically in the Iberian electricity market. This acute situation worries consumers, industry and governments. Underlining the instability of the market prices, for the first time, this study discusses how some of the most important regulatory changes, and their perception and absorption by involved parties, contributed to the current environment. In addition, this study stresses that if flexibility is overlooked, the overall purpose of having an affordable and reliable system is at risk.