We study a hydropower producer’s potential for value-creation from multi-market trading given the price variations in the markets and the flexibility provided through access to hydro reservoirs. We use a perfect foresight optimization model for a price-taking hydropower producer co-optimizing his trades in the day-ahead, intra-day and balancing markets. The model is used on real market data from Norway, Sweden and Germany. The study shows a theoretical potential for added value when selling energy in multiple markets relative to optimal day-ahead sale. Most of this value is achievable also when the perfect foresight is limited to the period from day-ahead bidding until operation. Flexible production plants achieve the largest relative added values for multi-market sales, and has the largest benefit from a long horizon with perfect foresight.
Plug and abandonment (P&A) of subsea wells is very costly and usually requires semi-submersible drilling rigs (SSR). To reduce total costs of the subsea P&A campaigns, it is beneficial to perform P&A operations with riserless light well intervention (RLWI) vessels instead of rigs. Currently, a drilling rig is required for performing P&A operations in the reservoir section and overburden, whereas intervention vessels can be used for preparatory work and wellhead removal. This paper discusses how it can be technologically feasible to perform full P&A of subsea wells with RLWI vessels. It is shown that, for wells of simple and medium complexity, innovate approaches with use of existing technologies can enable full P&A of the entire well with RLWI vessels. This is demonstrated by thorough analyses of operational procedures using available technologies, where RLWI operations are compared to rig operations for different well scenarios. Furthermore, to quantify the cost benefits of the innovative approaches, a cost-optimization tool has been used to estimate the resulting cost and time durations of the different approaches and scenarios.
The purpose of this study is to explore the antecedents of high-performance work systems (HPWS). HPWS promise workplaces that are both highly productive and offer employees high levels of job satisfaction. The existing literature tends to see HPWS as outcomes of planned change initiated by management as part of an human resource management (HRM) strategy. We question this assumption and show that under favourable conditions, HPWS may emerge from workers' selforganization. Design/methodology/approach: A qualitative case study was conducted of a department producing automotive components. Empirical material was collected through participant observation. The material was coded for recurring themes and used to construct an explanatory model. Findings: HPWS may emerge in the absence of managerial or HRM interventions. The emergence and reproduction of HPWS can be explained by a shop-floor culture of craftsmanship, worker solidarity and jobs with high levels of task significance and task identity. Research limitations/implications: We encourage future research to explore and more carefully theorize the antecedents of HPWS. Of particular interest is the relationship between planned HPWS initiatives and elements of the informal work organization, which may also promote autonomy, flexibility and commitment. Practical implications: Planned implementations of HPWS would benefit from appreciating and building on existing norms of craftsmanship and solidarity. Reinforcing and officially endorsing these norms may be preferable to introduce novel normative ideals of "teamwork", "empowerment" or "quality". Originality/value: Few studies have systematically explored the antecedents of HPWS. The proposed concept, "emergent HPWS", captures largely unacknowledged organizational dynamics.
When a petroleum well no longer serves its purpose, the operator is required to plug and abandon (P&A) the well to avoid contamination of reservoir fluids. An increasing number of offshore wells needs to be P&A'd in the near future, and the costs of these operations are substantial. Research on planning methods in order to allocate vessels that are required to perform these operations in a cost-efficient manner is therefore essential. We use an optimization approach and propose a mixed integer linear programming model based on a variant of the uncapacitated vehicle routing problem that includes precedence and non-concurrence constraints to plan a plugging campaign. P&A costs are minimized by creating optimal routes for a set of vessels, such that all operations that are needed to P&A a set of development wells are executed. In a case study, we show that our proposed optimization approach may lead to significant cost savings compared to traditional planning methods and is well suited for P&A planning purposes on a tactical level.
This paper considers a tactical block scheduling problem at a major Norwegian hospital. Here, specific patient groups are reserved time blocks for scanning at a heterogeneous set of Magnetic Resonance Imaging (MRI) labs. The time blocks consist of several time slots, and one or more patients from the same group are scanned in a block. A total weekly number of time slots for each specific patient group is given through demand forecast and negotiations, and several restrictions apply to the allocation of time blocks. Only part of the week is allocated to blocks for the specific patient groups. The rest is classified as open time. Thus, the MRI block scheduling problem consists of finding a cyclic weekly plan where one or more time blocks are to be allocated to each specific patient group, by deciding the day, start time and length, to minimise unfavourable patient group allocations, as well as allocations of open time. For the problem, we propose an integer programming model with an objective function that combines penalties for allocating time blocks to patient groups at unfavourable time slots and labs, and rewards for advantageous positioning of open time slots. The aim of the optimisation model is to facilitate the coordination of the MRI resources between the hospital departments, that are responsible for the specific patient groups, to achieve a fair distribution of time slots to the specific patient groups and open time blocks. The computational study is based on the real problem as well as artificially generated instances. Real-sized instances for our case hospital can be solved in short time. We illustrate how the model can be used to produce Pareto optimal solutions, and how these solutions can provide the decision makers with managerial insight.
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