10 research outputs found
Stable optimisation-based scenario generation via game theoretic approach
Systematic scenario generation (SG) methods have emerged as an invaluable
tool to handle uncertainty towards the efficient solution of stochastic
programming (SP) problems. The quality of SG methods depends on their
consistency to generate scenario sets which guarantee stability on solving SPs
and lead to stochastic solutions of good quality. In this context, we delve
into the optimisation-based Distribution and Moment Matching Problem (DMP) for
scenario generation and propose a game-theoretic approach which is formulated
as a Mixed-Integer Linear Programming (MILP) model. Nash bargaining approach is
employed and the terms of the objective function regarding the statistical
matching of the DMP are considered as players. Results from a capacity planning
case study highlight the quality of the stochastic solutions obtained using
MILP DMP models for scenario generation. Furthermore, the proposed
game-theoretic extension of DMP enhances in-sample and out-of-sample stability
with respect to the challenging problem of user-defined parameters variability
Data-driven scenario generation for two-stage stochastic programming
Optimisation under uncertainty has always been a focal point within the Process Systems Engineering (PSE) research agenda. In particular, the efficient manipulation of large amount of data for the uncertain parameters constitutes a crucial condition for effectively tackling stochastic programming problems. In this context, this work proposes a new data-driven Mixed-Integer Linear Programming (MILP) model for the Distribution & Moment Matching Problem (DMP). For cases with multiple uncertain parameters a copula-based simulation of initial scenarios is employed as preliminary step. Moreover, the integration of clustering methods and DMP in the proposed model is shown to enhance computational performance. Finally, we compare the proposed approach with state-of-the-art scenario generation methodologies. Through a number of case studies we highlight the benefits regarding the quality of the generated scenario trees by evaluating the corresponding obtained stochastic solutions
The impact of 100% electrification of domestic heat in Great Britain
Britain has been a global leader in reducing emissions, but little progress has been made on heat, which accounts for almost one-third of UK emissions and the largest single share is domestic heat, which is responsible for 17% of the national total. Given the UK’s 2050 “Net-Zero” commitment, decarbonizing heat is becoming urgent and currently one of the main pathways involves its electrification. Here, we present a spatially explicit optimization model that investigates the implications of electrifying domestic heat on the operation of the power sector. Using hourly historical gas demand data, we conclude that the domestic peak heat demand is almost 50% lower than widely cited values. A 100% electrification pathway can be achieved with only a 1.3-fold increase in generation capacity compared to a power-only decarbonization scenario, but only by leveraging the role of thermal energy storage technologies without which a further 40% increase would be needed
A multi-period game-theoretic approach to market fairness in oligopolies
Contemporary process industries are constantly confronted with volatile
market conditions that jeopardise their financial sustainability. While mature
markets transition to oligopoly structures, the supply chain operation should
adapt to a more customer-centric focus. Key issues related to the modelling and
impact of the related contractual agreements between firms and customers remain
largely unexplored. In the present work, we examine the problem of fair
customer allocation in oligopolies under different contractual agreements
within a multi-period setting. We consider an ensemble of contract types that
vary in terms of pricing mechanisms and duration. The role of fairness is
examined following the social welfare and Nash bargaining scheme. In the latter
case, the overall problem is formulated as an MINLP. For its efficient solution
we employ a piecewise linearisation strategy based on special-ordered sets. The
impact of the different fairness schemes on the optimal customer allocation is
evaluated via two case studies from the industrial gases market
Investigating the Trade-Off between Design and Operational Flexibility in Continuous Manufacturing of Pharmaceutical Tablets: A Case Study of the Fluid Bed Dryer
Market globalisation, shortened patent lifetimes and the ongoing shift towards personalised medicines exert unprecedented pressure on the pharmaceutical industry. In the push for continuous pharmaceutical manufacturing, processes need to be shown to be agile and robust enough to handle variations with respect to product demands and operating conditions. In this paper we examine the use of operational envelopes to study the trade-off between the design and operational flexibility of the fluid bed dryer at the heart of a tablet manufacturing process. The operating flexibility of this unit is key to the flexibility of the full process and its supply chain. The methodology shows that for the fluid bed dryer case study there is significant effect on flexibility of the process at different drying times with the optimal obtained at 700 s. The flexibility is not affected by the change in volumetric flowrate, but only by the change in temperature. Here the method used a black box model to show how it could be done without access to the full model equation set, as this often needs to be the case in commercial settings
Recommended from our members
A game-theoretic optimisation approach to fair customer allocation in oligopolies
AbstractUnder the ever-increasing capital intensive environment that contemporary process industries face, oligopolies begin to form in mature markets where a small number of companies regulate and serve the customer base. Strategic and operational decisions are highly dependent on the firms’ customer portfolio and conventional modelling approaches neglect the rational behaviour of the decision makers, with regards to the problem of customer allocation, by assuming either static competition or a leader-follower structure. In this article, we address the fair customer allocation within oligopolies by employing the Nash bargaining approach. The overall problem is formulated as mixed integer program with linear constraints and a nonlinear objective function which is further linearised following a separable programming approach. Case studies from the industrial liquid market highlight the importance and benefits of the proposed game theoretic approach.</jats:p
Multi Set-Point Explicit Model Predictive Control for Nonlinear Process Systems
In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state of the dynamical system at each sampling instance. To this end, an algorithm for a special class of multi-parametric nonlinear programming problems with uncertain parameters on the right-hand side of the constraints and the cost coefficients of the objective function is presented. The algorithm is based on computed algebra methods for symbolic manipulation that enable an analytical solution of the optimality conditions of the underlying multi-parametric nonlinear program. A notable property of the presented algorithm is the computation of exact, in general nonconvex, critical regions that results in potentially great computational savings through a reduction in the number of convex approximate critical regions
Traveling Salesman Problem-Based Integration of Planning, Scheduling, and Optimal Control for Continuous Processes
Advanced
decision making in the process industries requires efficient
use of information available at different decision levels. Traditionally,
planning, scheduling, and optimal control problems are solved in a
decoupled way, neglecting their strong interdependence. Integrated
planning, scheduling and optimal control (iPSC) aims to address this
issue. Formulating the iPSC, results in a large scale nonconvex mixed
integer nonlinear programming problem. In the present work, we propose
a new approach for the iPSC of continuous processes aiming to reduce
model and computational complexity. For the planning and scheduling,
a Traveling Salesman Problem-based formulation is employed, where
the planning periods are modeled in discrete time while the scheduling
within each week is in continuous time. Another feature of the proposed
iPSC framework is that backlog, idle production time, and multiple
customers are introduced. The resulting problem is a mixed integer
programming problem and different solution strategies are employed
and analyzed
Investigating the Trade-Off between Design and Operational Flexibility in Continuous Manufacturing of Pharmaceutical Tablets: A Case Study of the Fluid Bed Dryer
Market globalisation, shortened patent lifetimes and the ongoing shift towards personalised medicines exert unprecedented pressure on the pharmaceutical industry. In the push for continuous pharmaceutical manufacturing, processes need to be shown to be agile and robust enough to handle variations with respect to product demands and operating conditions. In this paper we examine the use of operational envelopes to study the trade-off between the design and operational flexibility of the fluid bed dryer at the heart of a tablet manufacturing process. The operating flexibility of this unit is key to the flexibility of the full process and its supply chain. The methodology shows that for the fluid bed dryer case study there is significant effect on flexibility of the process at different drying times with the optimal obtained at 700 s. The flexibility is not affected by the change in volumetric flowrate, but only by the change in temperature. Here the method used a black box model to show how it could be done without access to the full model equation set, as this often needs to be the case in commercial settings