Zugl.: Diss. Univ. Duisburg-Essen, 2006.

This master thesis is concerned with the topic of deaccessioning from public art museums in the Czech Republic. This practice is almost never carried out due to high legal restrictions and very demanding administration. Nevertheless, deaccessioning is becoming common practice in other European countries such as United Kingdom or the Netherlands. The goal of the thesis is to suggest main topics in the hypothetical regulation of deaccessioning in the Czech Republic considering the current theoretical framework, already conducted research and newly conducted research within this thesis. The latter is open coding analysis of guidelines on collection deaccessioning made by United Kingdom Museum Association. The main conclusions are that a few topics should be subject to regulation. Firstly, the reason to dispose (either economic or other), secondly, the acceptable use of the income from deaccessioning, thirdly, decision making process and supervision. At last, selection of collection or items to be disposed and question of new collection owner should be solved.

Zugl.: Diss. University Duisburg-Essen, 2007.

Infrastructure systems around the world face immediate crises and smoldering long-term challenges. Consequently, system owners and managers must balance the need to repair and replace the aging and deteriorating systems already in place against the need for transformative investments in deep decarbonization, climate adaptation, and transportation that will enable long-term competitiveness. Complicating these decisions are deep uncertainties, finite resources, and competing objectives. These challenges motivate the integration of “hard” investments in physical infrastructure with “soft” instruments like insurance, land use policy, and ecosystem restoration that can improve service, shrink costs, scale up or down as future needs require, and reduce vulnerability to population loss and economic contraction. A critical advantage of soft instruments is that they enable planners to adjust, expand, or reduce them at regular intervals, unlike hard instruments which are difficult to modify once in place. As a result, soft instruments can be precisely tailored to meet near-term needs and conditions, including projections of the quasi-oscillatory, regime-like climate processes that dominate seasonal to decadal hydro-climate variability, thereby reducing the need to guess the needs and hazards of the distant future. The objective of this dissertation is to demonstrate how potentially predictable modes of structured climate variability can inform the design of soft instruments and the formulation of adaptive infrastructure system plans. Using climate information for sequential adaptation requires developing credible projections of climate variables at relevant time scales. PartI considers the drivers of river floods in large river basins, which is used throughout this dissertation as an example of a high-impact hydroclimate extreme. First, chapter 2 opens by exploring the strengths and limitations of existing methodologies, and by developing a statistical-dynamical causal chain framework within which to consider flood risk on interannual to secular time scales. Next, chapter 3 describes the physical mechanisms responsible for heavy rainfall (90th percentile exceedance)and flooding in the Lower Paraguay River Basin (LPRB), focusing on a November-February(NDJF) 2015-16 flood event that displaced over 170 000 people. This chapter shows that: 1. persistent large-scale conditions over the South American continent during NDJF 2015-16 strengthened the South American Low-Level Jet (SALLJ), bringing warm air and moisture to South East South America (SESA), and steered the jet towards the LPRB, leading to repeated heavy rainfall events and large-scale flooding; 2. while the observed El Niño event contributed to a stronger SALLJ, the Madden-JulienOscillation (MJO) and Atlantic ocean steered the jet over the LPRB; and 3. while numerical sub-seasonal to seasonal (S2S) and seasonal models projected an elevated risk of flooding consistent with the observed El Niño event, they had limited skill at lead times greater than two weeks, suggesting that improved representation of MJO and Atlantic teleconnections could improve regional forecast skill. Finally, chapter 4 shows how mechanistic understanding of the physical causal chain that leads to a particular hazard of interest – in this case heavy rainfall over a large area in the Ohio River Basin (ORB) – can inform future risks. Taking the GFDL coupled model, version 3 (CM3) as a representative general circulation model (GCM), this chapter shows that 1. the GCM simulates too many regional extreme precipitation (REP) events but under-simulates the occurrence of back to back REP days; 2. REP days show consistent large-scale climate anomalies leading up to the event; 3. indices describing these large-scale anomalies are well simulated by the GCM; and 4. a statistical model describing this causal chain and exploiting simulated large-scale in-dices from the GCM can be used to inform the future occurrence of REP days. Even the best climate projections must confront epistemic uncertainties. Part II of this dissertation explores how intrinsically flawed projections should inform sequential adaptation.First, chapter5reviews approaches for planning under uncertainty, considering the role of classical decision theory, optimization, probability, and non probabilistic approaches. Next, chapter 6 considers how different physical mechanisms impart predictability at different timescales and the implications of secular, low-frequency cyclical, and high-frequency cyclical variability for selection between instruments with long and short planning periods. In particular, this chapter builds from three assertions regarding the nature of climate risk: 1. different climate risk mitigation instruments have different project lifespans; 2. climate risk varies on many scales; and 3. the processes which dominate this risk over the planning period depend on the planning period itself. Defining M as the nominal design life of a structural or financial instrument and N as the length of the observational record (a proxy for total informational uncertainty), chapter 7 presents a series of stylized computational experiments to probe the implications of these premises. Key findings are that: 1. quasi-periodic and secular climate signals, with different identifiability and predictability, control future uncertainty and risk; 2. adaptation strategies need to consider how uncertainties in risk projections influence the success of decision pathways; and 3. stylized experiments reveal how bias and variance of climate risk projections influencerisk mitigation over a finite planning period. Chapter 7 elaborates these findings through a didactic case study of levee heightening in the Netherlands. Integrating a conceptual model of low-frequency variability with credible projections of sea level rise, chapter 7 uses dynamic programming to co-optimize hard (levee increase) and soft (insurance) instruments. Key findings are that 1. large but distant and uncertain changes (e.g., sea level rise) do not necessarily motivate immediate investment in structural risk protection; 2. soft adaptation strategies are robust to different model structures and assumptions while hard instruments perform poorly under conditions for which they were not de-signed; and 3. increasing the hypothetical predictability of near-term climate extremes significantly lowers long-term adaptation costs. Finally, part III seeks to unpack the conceptual experiments of parts I and II to inform policy and future research. Chapter 8 describes how constructive narratives about climate change can discourage climate fatalism. Instead, chapter 8 emphasizes that while climate change is and will be a critical stressor of infrastructure systems, individuals, communities, and regions have agency and can mitigate its consequences. Finally, chapter9concludes by discussing the key findings of this dissertation and exploring how future work on decision under uncertainty, technology, and earth systems science can aid the design and management of effective infrastructure services.

[pt] No mundo inteiro o Setor Elétrico têm passado por mudanças radicais. A principal meta desse processo de restruturação foi promover a competição nos segmentos de geração, distribuição e comercialização energia elétrica e a participação de agentes privados no processo de produção. Essa reestruturação está baseada em uma otimização centralizada e nas seguintes premissas: Geradores ofertam sua produção em um Mercado Atacadista de Energia - MAE . Os agentes privados são livres para decidir sobre a construção de novas usinas e para competir por contratos de energia vendas com empresas distribuidoras e clientes individuais.O novo ambiente competitivo permite, no entanto, que em cenários de preços spots elevados as empresas Distribuidoras de energia elétrica possam vender as diferenças entre os valores de demanda contratados e consumidos. A possibilidade de retração de carga por meio de negociações com clientes pode resultar em sobras de energia que poderão ser vendidas diretamente no Mercado Spot. Por outro lado, a reação dos Geradores através de instrumentos financeiros adequados (como contratos bilaterais, contratos futuros e de opção) ou de políticas operacionais (via Operador do Sistema) podem resultar em um -jogo- de estratégias no MAE. Esta tese investiga alguns conceitos, metodologias e ferramentas computacionais desenvolvidas para a operação e comercialização da energia elétrica envolvendo análise de riscos e instrumentos financeiros. O problema de gerenciamento e retração forçada da demanda (elasticidade forçada) é decomposto em dois subproblemas:Subproblema de operação: usando programação dinâmica dual estocástica . Subproblema de análise de riscos: usando a teoria da utilidade O modelo proposto é avaliado através de um estudo de caso considerando os dados do sistema interligado Sul-Sudeste, para o qual são simuladas ações de retração da demanda. / [en] Electricity utilities all over the world have been undergoing radical changes in their market and its regulatory structure. A basic trend in this restructuring process has been to promote competition in generation, distribution/retailing segments and participation of private agents in the energy production process. This restructuring is based on centralized optimization, by market-oriented approaches: Generators bid prices for their energy in a Wholesale Energy Market - WEM. Instead of following an expansion schedule produced by a central planning agency, private agents are free to decide about the construction of generator units and to compete for energy sales contracts with utilities and individual customers.The competitive environment permits, however, which in high spot prices scenarios the electric utilities sell some differences between bilateral contract and real consumption. The possibility of load retraction by means of negotiations with clients would result in surplus generation which could be sold directly to the spot market. On the other hand, the reaction of the Generators via financial means (such as bilateral contracts, forward contracts and option prices) or operational policies from System Operator can result in a WEM -gaming-. This thesis investigates some conceptual issues, methodologies and computational tools developed to operation and commercialization of the electrical energy considering risk analysis and financial instruments. The demand side and retraction management problem is decomposed in two sub-problems: Operation sub-problem: uses stochastic dual dynamic programming (SDDP)tools Risk analysis sub-problem: uses utility theoryThe approach will be illustrated with a case study with data taken from the Brazilian system, where the demand side management is simulated and the numerical results are presented.