Dynamic model development of adiabatic compressed air energy storage

The share of variable renewable energy in electricity generation has seen exponential growth during the recent decades, and due to the heightened pursuit of environmental targets, the trend is to continue with increased pace. The two most important resources, wind and insolation both bear the burden of intermittency, creating a need for regulation and posing a threat to grid stability. One possibility to deal with the imbalance between demand and generation is to store electricity temporarily, which was addressed in this thesis by implementing a dynamic model of adiabatic compressed air energy storage (CAES) with Apros dynamic simulation software. Based on literature review, the existing models due to their simplifications were found insufficient for studying transient situations, and despite of its importance, the investigation of part load operation has not yet been possible with satisfactory precision. As a key result of the thesis, the cycle efficiency at design point was simulated to be 58.7%, which correlated well with literature information, and was validated through analytical calculations. The performance at part load was validated against models shown in literature, showing good correlation. By introducing wind resource and electricity demand data to the model, grid operation of CAES was studied. In order to enable the dynamic operation, start-up and shutdown sequences were approximated in dynamic environment, as far as is known, the first time, and a user component for compressor variable guide vanes (VGV) was implemented. Even in the current state, the modularly designed model offers a framework for numerous studies. The validity of the model is limited by the accuracy of VGV correlations at part load, and in addition the implementation of heat losses to the thermal energy storage is necessary to enable longer simulations. More extended use of forecasts is one of the important targets of development, if the system operation is to be optimised in future.

Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.