Unified Concept of Bottleneck

The term `bottleneck` has been extensively used in operations management literature. Management paradigms like the Theory of Constraints focus on the identification and exploitation of bottlenecks. Yet, we show that the term has not been rigorously defined. We provide a classification of bottleneck definitions available in literature and discuss several myths associated with the concept of bottleneck. The apparent diversity of definitions raises the question whether it is possible to have a single bottleneck definition which has as much applicability in high variety job shops as in mass production environments. The key to the formulation of an unified concept of bottleneck lies in relating the concept of bottleneck to the concept of shadow price of resources. We propose an universally applicable bottleneck definition based on the concept of average shadow price. We discuss the procedure for determination of bottleneck values for diverse production environments. The Law of Diminishing Returns is shown to be a sufficient but not necessary condition for the equivalence of the average and the marginal shadow price. The equivalence of these two prices is proved for several environments. Bottleneck identification is the first step in resource acquisition decisions faced by managers. The definition of bottleneck presented in the paper has the potential to not only reduce ambiguity regarding the meaning of the term but also open a new window to the formulation and analysis of a rich set of problems faced by managers.

Assessing the impact of future CAP reforms on the demand of production factors

The CAP reform process has been a central issue for agricultural economics research in recent years, and is gaining further attention in view of the post-2013 perspectives. The objective of this paper is to assess ex-ante the effect of different post-2013 CAP and market scenarios on the demand of productions factors. The paper is based on the use of farm household dynamic programming models maximising the net present value with a time horizon until 2030. A representative model has been implemented for 18 different farming systems in 8 EU countries. Changes in marginal values of selected resource constraints (land, labour and capital) are used to assess the potential effect of different scenarios on farm-household demand of production factors. Results highlight that both policy and market conditions change strongly the demand of productive factors.CAP reform, Investment behaviour, Farm Household model, Factor markets, Agricultural and Food Policy, Q12,

Assessing the impact of future CAP reforms on the demand of production factors

The CAP reform process has been a central issue for agricultural economics research in recent years, and is gaining further attention in view of the post-2013 perspectives. The objective of this paper is to assess ex-ante the effect of different post-2013 CAP and market scenarios on the demand of productions factors. The paper is based on the use of farm household dynamic programming models maximising the net present value with a time horizon until 2030. A representative model has been implemented for 18 different farming systems in 8 EU countries. Changes in marginal values of selected resource constraints (land, labour and capital) are used to assess the potential effect of different scenarios on farm-household demand of production factors. Results highlight that both policy and market conditions change strongly the demand of productive factors.JRC.J.4-Agriculture and Life Sciences in the Econom

Assessing the impact of future CAP reforms on the demand of production factors

The CAP reform process has been a central issue for agricultural economics research in recent years, and is gaining further attention in view of the post-2013 perspectives. The objective of this paper is to assess ex-ante the effect of different post-2013 CAP and market scenarios on the demand of productions factors. The paper is based on the use of farm household dynamic programming models maximising the net present value with a time horizon until 2030. A representative model has been implemented for 18 different farming systems in 8 EU countries. Changes in marginal values of selected resource constraints (land, labour and capital) are used to assess the potential effect of different scenarios on farm-household demand of production factors. Results highlight that both policy and market conditions change strongly the demand of productive factors

Computational and Near-Optimal Trade-Offs in Renewable Electricity System Modelling

In the decades to come, the European electricity system must undergo an unprecedented transformation to avert the devastating impacts of climate change. To devise various possibilities for achieving a sustainable yet cost-efficient system, in the thesis at hand, we solve large optimisation problems that coordinate the siting of generation, storage and transmission capacities. Thereby, it is critical to capture the weather-dependent variability of wind and solar power as well as transmission bottlenecks. In addition to modelling at high spatial and temporal resolution, this requires a detailed representation of the electricity grid. However, since the resulting computational challenges limit what can be investigated, compromises on model accuracy must be made, and methods from informatics become increasingly relevant to formulate models efficiently and to compute many scenarios. The first part of the thesis is concerned with justifying such trade-offs between model detail and solving times. The main research question is how to circumvent some of the challenging non-convexities introduced by transmission network representations in joint capacity expansion models while still capturing the core grid physics. We first examine tractable linear approximations of power flow and transmission losses. Subsequently, we develop an efficient reformulation of the discrete transmission expansion planning (TEP) problem based on a cycle decomposition of the network graph, which conveniently also accommodates grid synchronisation options. Because discrete investment decisions aggravate the problem\u27s complexity, we also cover simplifying heuristics that make use of sequential linear programming (SLP) and retrospective discretisation techniques. In the second half, we investigate other trade-offs, namely between least-cost and near-optimal solutions. We systematically explore broad ranges of technologically diverse system configurations that are viable without compromising the system\u27s overall cost-effectiveness. For example, we present solutions that avoid installing onshore wind turbines, bypass new overhead transmission lines, or feature a more regionally balanced distribution of generation capacities. Such alternative designs may be more widely socially accepted, and, thus, knowing about these degrees of freedom is highly policy-relevant. The method we employ to span the space of near-optimal solutions is related to modelling-to-generate-alternatives, a variant of multi-objective optimisation. The robustness of our results is further strengthened by considering technology cost uncertainties. To efficiently sweep the cost parameter space, we leverage multi-fidelity surrogate modelling techniques using sparse polynomial chaos expansion in combination with low-discrepancy sampling and extensive parallelisation on high-performance computing infrastructure

Optimization Modeling to Address the Impacts of Electric Power Market Design on Operations and Policy

The electric power system is affected by numerous inefficiencies. Operation of the power grid uses intricate mathematical models to schedule supply and demand instantaneously, and complex settlement mechanisms to charge and pay participants. This dissertation focuses on four aspects of electric market design and operation endeavoring to improve economic and operational efficiency. Each chapter utilizes bottom-up engineering-economic models to simulate power grid operations. The overall goal of the dissertation is to analyze electric market inefficiencies and examine proposed alternative designs and policies. The dissertation begins with characterizing the electric system and the role and challenges of renewable energy in Chapter 1. Then Chapter 2 proposes a new method for pricing electricity in organized wholesale markets, called the Dual Pricing Algorithm. The current pricing method is non-confiscatory but does not capture the full cost of operation in marginal prices. The proposed method achieves these two aims while also providing further transparency. Chapter 3 examines potential benefits of three adjustments in reserve procurement procedures, and estimates economic efficiency using a European test system. Each adjustment improves current practice, either in the quantity of reserves needed, the procurement method, or the degree of coordination with neighboring countries. The results demonstrate coordination among countries shows greatest consistent benefits among the three adjustments. Chapter 4 examines integration of carbon policies into real-time markets when the emissions system encompasses a sub-region of the larger electricity market, comparing five alternative models. Findings suggest that there is a trade-off between emissions and cost, with no one dominant method to identify and manage leakage from the regulated system. Chapter 5 analyzes degrees of coordination between neighboring systems for both day-ahead and real-time energy markets. The simulations for a test case find that coordinating in real-time without coordination in the day-ahead market results in higher costs compared to not coordinating at all. These chapters examine trade-offs, whether they are between ease of implementation, economic efficiency, renewable integration, or emissions reductions. Overall, the dissertation contributes a framework for assessing market design improvements, and demonstrates to system operators and decisions makers that coordination between neighboring regions can increase economic efficiency