179 research outputs found
A Method to Assess Value of Integrated Operations
Integrated operations in the petroleum industry adopt information technology, improve access to real-time data, integrate people and organizations, change work processes, and by doing so, enable better and faster decisions. Consequently, a set of associated business benefits is envisioned. However, the challenge is how to measure them. In this paper, we propose a pragmatic decision analytic method to assess monetary value of integrated operations. The proposed method builds on findings from contemporary literature that emphasizes the need to assess information technology in a broader context of organizational structures and work processes. The method therefore has a built in qualitative assessment of collaborative competence that provides indispensible insights to risks associated with a particular change management project. Yet, it allows for calculating monetary value by integrated formal decision analysis. Feasibility of the method is illustrated by an illustrative case from integrated and collaborative monitoring of offshore operations
Powering Europe with North Sea Offshore Wind: The Impact of Hydrogen Investments on Grid Infrastructure and Power Prices
Hydrogen will be a central cross-sectoral energy carrier in the
decarbonization of the European energy system. This paper investigates how a
large-scale deployment of green hydrogen production affects the investments in
transmission and generation towards 2060, analyzes the North Sea area with the
main offshore wind projects, and assesses the development of an offshore energy
hub. Results indicate that the hydrogen deployment has a tremendous impact on
the grid development in Europe and in the North Sea. Findings indicate that
total power generation capacity increases around 50%. The offshore energy hub
acts mainly as a power transmission asset, leads to a reduction in total
generation capacity, and is central to unlock the offshore wind potential in
the North Sea. The effect of hydrogen deployment on power prices is
multifaceted. In regions where power prices have typically been lower than
elsewhere in Europe, it is observed that hydrogen increases the power price
considerably. However, as hydrogen flexibility relieves stress in high-demand
periods for the grid, power prices decrease in average for some countries. This
suggests that while the deployment of green hydrogen will lead to a significant
increase in power demand, power prices will not necessarily experience a large
increase.Comment: Submitted to Energ
An optimization model for the planning of offshore plug and abandonment campaigns
Plug and abandonment (P&A) operations can be time-consuming and thus very costly, especially for subsea fields. P&A of subsea wells require dedicated vessels such as high cost semi-submersible drilling rigs or lower cost Riserless Light Well Intervention vessels. This paper describes an optimization model that can be used to plan multi-well P&A campaigns by finding cost-efficient vessel routes and allocation of P&A operations to different rigs and vessels. The model's functionality is demonstrated on ten different synthetic cases, generated from realistic data. Results show that significant cost savings can be made by adapting the optimal solutions from this model compared to planning strategies that are currently used by operators, as well as by cooperating across fields and licenses in a large campaign.publishedVersio
Stochastic Electricity Dispatch: A challenge for market design
We consider an electricity market with two sequential market clearings, for instance representing a day-ahead and a real-time market. When the first market is cleared, there is uncertainty with respect to generation and/or load, while this uncertainty is resolved when the second market is cleared. We compare the outcomes of a stochastic market clearing model, i.e. a market clearing model taking into account both markets and the uncertainty, to a myopic market model where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids
in the second market. While the stochastic market clearing gives a solution with a higher total social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the prices deviate from the bid curves in the first market. This can lead to incentives for selfscheduling, require producers to produce above marginal cost and consumers to pay above their marginal value in the first market. Our analysis show that the wind producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the total social
welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that the wind producer has an incentive to misreport the probability distribution for wind
An integrated analysis of carbon capture and storage strategies for power and industry in Europe
Industry is responsible for one-quarter of the global CO2 emissions. In this study, four different climate pathways are analyzed with a cost minimizing multihorizon stochastic optimization model, in order to analyze possible realizations of carbon capture and storage (CCS) in the power sector and main industrial sectors in Europe. In particular, we aim to achieve a deeper understanding of the distribution of capture by country and key sector (power, steel, cement and refinery), as well as the associated transport and storage infrastructure for CCS. Results point to the synergy effect of sharing common CCS infrastructres among power and major industrial sectors. The contribution of CCS is mainly found in three industrial sectors, particularly steel, cement and refineries) but also in the power sector to a lesser extent. It is worth noting that retrofitting of CCS in the power sector was not considered in this study. The geographical location for capture and storage, as well as timing and capacity needs are presented for different socio-economic pathways and corresponding emission targets. It has been shown that contributions of the three industry sectors in emissions reductions are neither geographically nor sector-wise homogeneous across the pathways.acceptedVersio
A goal programming methodology for multiobjective optimization of distributed energy hubs operation
This paper addresses the problem of optimal energy flow management in multicarrier energy networks
in the presence of interconnected energy hubs. The overall problem is here formalized by a nonlinear
constrained multiobjective optimization problem and solved by a goal attainment based methodology.
The application of this solution approach allows the analyst to identify the optimal operation state of the
distributed energy hubs which ensures an effective and reliable operation of the multicarrier energy
network in spite of large variations of load demands and energy prices. Simulation results obtained on
the 30 bus IEEE test network are presented and discussed in order to demonstrate the significance and
the validity of the proposed method
A stabilised Benders decomposition with adaptive oracles applied to investment planning of multi-region power systems with short-term and long-term uncertainty
Benders decomposition with adaptive oracles was proposed to solve large-scale
optimisation problems with a column bounded block-diagonal structure, where
subproblems differ on the right-hand side and cost coefficients. Adaptive
Benders reduces computational effort significantly by iteratively building
inexact cutting planes and valid upper and lower bounds. However, Adaptive
Benders and standard Benders may suffer severe oscillation when solving a
multi-region investment planning problem. Therefore, we propose stabilising
Adaptive Benders with the level set method and adaptively selecting the
subproblems to solve per iteration for more accurate information. Furthermore,
we propose a dynamic level set method to improve the robustness of stabilised
Adaptive Benders by adjusting the level set per iteration. We compare
stabilised Adaptive Benders with the unstabilised versions of Adaptive Benders
with one subproblem solved per iteration and standard Benders on a multi-region
long-term power system investment planning problem with short-term and
long-term uncertainty. The problem is formulated as multi-horizon stochastic
programming. Four algorithms were implemented to solve linear programming with
up to 1 billion variables and 4.5 billion constraints. The computational
results show that: a) for a 1.00% convergence tolerance, the proposed
stabilised method is up to 113.7 times faster than standard Benders and 2.14
times faster than unstabilised Adaptive Benders; b) for a 0.10% convergence
tolerance, the proposed stabilised method is up to 45.5 times faster than
standard Benders and unstabilised Adaptive Benders cannot solve the largest
instance to convergence tolerance due to severe oscillation and c) dynamic
level set method makes stabilisation more robust
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