Decision support for strategic energy planning: A robust optimization framework

Optimization models for long-term energy planning often feature many uncertain inputs, which can be handled using robust optimization. However, uncertainty is seldom accounted for in the energy planning practice, and robust optimization applications in this field normally consider only a few uncertain parameters. A reason for this gap between energy practice and stochastic modeling is that large-scale energy models often present features—such as multiplied uncertain parameters in the objective and many uncertainties in the constraints—which make it difficult to develop generalized and tractable robust formulations. In this paper, we address these limiting features to provide a complete robust optimization framework allowing the consideration of all uncertain parameters in energy models. We also introduce an original approach to make use of the obtained robust formulations for decision support and provide a case study of a national energy system for validation.     

Robustness and Optimality as Criteria for Strategic Decisions

The use of "optimality" as an operational research criterion is insufficiently discriminating. Ample evidence exists that for many problems simple optimization (particularly profit maximization) does not represent the aims of management. In this paper we discuss the nature of the problem situations for which alternative decision criteria are more appropriate. In particular the structure of strategic planning problems is analysed. The provisional commitment involved in a plan (in contrast to the irrevocable commitment of a decision) leads to the development of a particular criterion, robustness—a measure of the flexibility which an initial decision of a plan maintains for achieving near-optimal states in conditions of uncertainty. The robustness concept is developed through the case study of a sequential factory location problem.     

Multiple objective forest land management planning: An illustration

Multiple Objective Programming (MOP) has undergone a rapid period of development during the last decade. Concurrently, increased land-use pressures have stimulated forest land management analysts to develop and utilize more sophisticated planning aids to address complex multi-resource issues involving multiple objectives and decision makers.To illustrate the potential use of MOP in land management planning, a demonstrative example is examined using an interactive technique—the Stem method. This method was chosen because of its promise as a rational, practical and systematic means of exploring feasible alternative solutions to multiple objective forest land management problems.     

A comprehensive energy model in the municipal energy planning process

Based on several years of experience, the procedural aspects of the use of a comprehensive LP-model for community energy planning is discussed. The community energy system is seen as a technically complex, open system which is managed by a network of organizations (esoteric boxes). Technical complexity, closure and lack of unique management raises specific procedural problems for which solutions are suggested. The network management gives the comprehensive model a special rôle in the planning process in providing for improved information flows and conflict resolution. The viability of the paradigm of learning is noted. A methodology to merge substantive and procedural aspects is proposed.     

Conservation of energy,momentum and actions in numerical discretizations of non-linear wave equations

For classes of symplectic and symmetric time-stepping methods— trigonometric integrators and the Störmer–Verlet or leapfrog method—applied to spectral semi-discretizations of semilinear wave equations in a weakly non-linear setting, it is shown that energy, momentum, and all harmonic actions are approximately preserved over long times. For the case of interest where the CFL number is not a small parameter, such results are outside the reach of standard backward error analysis. Here, they are instead obtained via a modulated Fourier expansion in time.     

Simultaneous Posterior Probability Statements From Monte Carlo Output

This article considers the problem of making simultaneous probability statements in multivariate inferential problems based on samples from a posterior distribution. The calculation of simultaneous credible bands is reviewed and—as an alternative—contour probabilities are proposed. These are defined as 1 minus the content of the highest posterior density region which just covers a certain point of interest. We discuss a Monte Carlo method to estimate contour probabilities and distinguish whether or not the functional form of the posterior density is available. In the latter case, an approach based on Rao-Blackwellization is proposed. We highlight that this new estimate has an important invariance property. We illustrate the performance of the different methods in three applications.     

OR and energy: Problems of modelling

Attention is focused on three problem areas in energy modelling: (1) identifying the essential elements of the system, (2) coping with multiple criteria, (3) incorporating learning in the system. These aspects are illustrated through examples in current energy systems research, involving the oil market, power systems planning, and the role of nuclear energy.In modelling the word oil market, too heavy emphasis is placed on economic forces, but practically non on the political forces. However, certain economics-oriented studies indicate that financial gains of OPEC may actually be intensitive to the oil pricing policy followed. If that is indeed the case, the significant (political) elements and their motives have to be captured in the model in order to arrive at consistent results.Modelling the different objectives in power systems planning is an area where advances are urgently needed. A method is proposed, where decision alternatives are generated a posteriori, in contrast to recent approaches involving a priori articulation of preferences, or interactive methods. A multicriterion dynamic linear programming model and a fast algorithm are used in generating efficient solutions, which are then grouped, based on the clustering in objective values.The problem associated with changing system objectives is discussed and the nuclear programme is given as an example of how the system objectives move from costs to perceived risks. In line with the real system that ‘learns’ from its experience, we need models that change their objective functions as a result of their own outputs at prior times.     

On solving stochastic production planning problems via scenario modelling

Summary Linear Porgramming models for stochastic planning problems and a methodology for solving them are proposed. A production planning problem with uncertainty in demand is used as a test case, but the methodology presented here is applicable to other types of problems as well. In these models, uncertainty in demand is characterized via scenarios. Solutions are obtained for each scenario and then these individual scenario solutions are aggregated to yield an implementable non-anticipative policy. Such an approach makes it possible to model correlated and nonstationary demand as well as a variety of recourse decision types. For computational purposes, two alternative representations are proposed. A compact approach that is suitable for the Simplex method and a splitting variable approach that is suitable for the Interior Point Methods. A crash procedure that generates an advanced starting solution for the Simplex method is developed. Computational results are reported with both the representations. Although some of the models presented here are very large (over 25000 constraints and 75000 variables), our computational experience with these problems is quite encouraging.     

Broadening the boundaries: an application of critical systems thinking to IS planning in Colombia

Most current information systems (IS) planning methodologies are focused on achieving plans that provide competitive advantage to business and solve the problems of information needs by using the latest technologies available. This paper presents an alternative approach to IS planning based on critical systems thinking—a research perspective that encourages the analysis of stakeholders' understandings of social contexts prior to the selection and/or design of planning methods. The approach is underpinned by a combination of the systems theories of autopoiesis and boundary critique, and it enables participants to reflect on different concerns and values during IS planning. This approach was applied in a project with a Colombian University, and it helped participants to uncover and address important human issues not usually seen as relevant by traditional approaches to IS planning. In addition, it led the authors to undertake further research on ethics after the project had been concluded.     

Criterion function for accessibility,uncertainty problems in regional land-use planning

One objective in regional planning is the creation of communities with great accessibility. Thus we should plan the locations of inhabitants and the activities of the region so that the total accessibility will be maximized subject to some restrictions. This is a quadratic programming problem, which can be solved by quadratic programming techniques, but we cannot then take into account the uncertainties of the problem.In this paper a new criterion function is proposed for accessibility, uncertainty problems in regional land-use planning. It is derived from Hurwicz's generalized maximin principle. Many advantages are gained, for the planning problem is separated into linear programming problems, the uncertainties are taken into consideration as in game theory and the methods of parametric programming are available.A simplified problem of the populations of three town areas is studied and the method is generalized for problems of many activities and areas.     

Computer-based models and the problem of investment in water resources: A case study

In this paper, a case study in regional water resources planning is presented in which the process of design and use of computer-based models and man-computer interaction is considered, especially with respect to the roles of designers and potential users. Key decisions in the design process are recognized and analyzed. It is concluded that integration of normative models in decision processes with conflicts shows limits that partly may be overcome by emphasis on the planning stage of the design process, and on development of planning and decision models that allow flexibility. Interactive procedures should be developed that distribute flexibility over decision levels and also deal with the problems of asymmetrical distributed information. It is concluded further that there is a need for a more systematical investigation of design processes and decision behavior related to characteristics of decision problems and environments.     

On linear problems with surface dissipation of energy

The first part of this work is devoted to applications of functional analysis methods to a linear initial-boundary value problem of mathematical physics with a surface dissipation of the energy. Its abstract analog is studied as well. The abstract Green formula for a triple of Hilbert spaces is used. In the second part, spectral problems generated by linear initial-boundary value problems with a surface dissipation of the energy are studied. First we formulate the spectral problem of mathematical physics and the corresponding abstract problem. Further, we consider basic properties of the spectrum and show that it is rather specific in the case of considered problems; particular examples (one-dimensional and two-dimensional ones as well as an example of a cylindrical domain) are used for that. It turns out that the spectrum migrates in the complex plane, while the dissipation parameter changes from zero to infinity. Examples of numerical computations of the spectrum by means of the iteration method are provided. Further, we investigate the general setting of the spectral problem. Using a general result of Azizov, we prove that the spectrum of the generic problem is discrete and has a limiting point at infinity.     

Normative agent-based simulation for supply chain planning

This paper presents an agent-based simulation framework for supply chain (SC) planning, introducing the notion of normative agent. The analysis of the relevant literature shows that most research works carried out in this area aim to handle specific problems and contexts. Although some methodologies and more generic solutions have been proposed, they are not able to cope with SCs in which regulation plays an important role, whether issued by a government agent or by an international institution. Several SCs, such as in the energy, food, chemical, and forestry areas, are highly regulated. Explicitly modelling the actors involved in the regulation of SCs using normative agents allowed us to evaluate the potential benefits of alternative strategies for planning of regulated SCs. The modelling of a biodiesel SC is presented as a case study.     

On the acceleration of shock waves and concentration of energy

By a series of simple examples related to exact solutions of problems in gas dynamics and magnetohydrodynamics, possible mechanisms of acceleration of shock waves and concentration of energy are elucidated. The acceleration of a shock wave is investigated in the problem of motion of a plane piston at a constant velocity in the case when the initial density of the medium drops in the presence of constant counterpressure. It is shown that in this situation a “blow-up” regime is induced by a shock wave going to infinity in finite time even for limited work of the piston. A simple spherically symmetric solution with a converging shock wave is constructed and shown to lead to the concentration of energy. A general method for solving one-dimensional non-self-similar problems related to matching the equilibrium state to a motion with homogeneous deformation on a shock wave is discussed; this method leads to a solution in quadratures.     

Planning Under Uncertainty: 1. The Inflexibility of Methodologies

The inflexibility of plans and planning has been much criticised. While there are certain material factors in the structures of developed societies which promote such inflexibility, the criticism, if substantiated, clearly represents a major failing of planning methodology. In this paper the two most prominent planning methodologies—rational comprehensive and incrementalist—are reviewed, and found to incorporate inflexibility in distinctive ways into their procedures. Other approaches to planning which stress the importance of flexibility and attempt to make it operational are then critically surveyed; from these certain desirable characteristics of a methodology for flexible planning are distilled. Finally, the urgency of the problem is illustrated with examples both from theorists of planning and from the practice of planning in a wide range of application areas. (An alternative methodology is proposed in a companion paper.)     

基于SPA-TOPSIS方法的能源结构优化程度评价

以能源低碳化发展为基础,从社会经济发展程度、能源规划合理程度、环境和谐程度三个准则层入手,构建能源结构优化程度评价指标体系。运用改进惯性权重的PSO算法确定评价体系权重,并基于SPA-TOPSIS法构建能源结构优化程度评价模型,对30个省、自治区、直辖市的区域能源结构优化程度进行实证研究。实证结果表明:区域社会经济发展水平对能源结构优化程度有直接影响,且各区域能源结构优化程度差异较大,总体呈现“东高西低”的格局;清洁能源消费占比、原煤消费占比、烟尘排放等因素对能源结构优化程度影响显著。     

Operational research in health services planning

Some of the characteristics which distinguish social planning from planning in the private sector, or in publicly owned industry, are identified. A survey of OR investigations (both tactical and strategic) in the area of health services planning supports the case that the mainstream OR contribution does violence to the nature of the system under study. In particular, problems are formulated in terms of (or transformed into) single objectives, to be optimized; aspects of the social world are subject to wholesale quantification, with resulting distortion; models make implausible data demands; project definition and execution reinforce the ‘scientisation’ of political debate; problems are formulated on the assumption of a single hierarchically powerful decision-maker; and problems are formulated as if they must be solved in toto at one point in time. It is suggested that we should look to the converse of these qualities for new directions in the application of operational research in social planning. Some examples are given of techniques and approaches, drawn both from within health services planning and from other areas, which exhibit these alternative characteristics.     

A note on “A mixed integer programming model for advanced planning and scheduling (APS)”

In a recent paper, Chen and Ji [Chen, K., Ji, P., 2007. A mixed integer programming model for advanced planning and scheduling (APS). European Journal of Operational Research 181, 515–522] develop a mixed integer programming model for advanced planning and scheduling problem that considers capacity constraints and precedence relations between the operations. The orders require processing of several operations on eligible machines. The model presented in the above paper works for the case where each operation can be processed on only one machine. However, machine eligibility means that only a subset of machines are capable of processing a job and this subset may include more than one machine. We provide a general model for advanced planning and scheduling problems with machine eligibility. Our model can be used for problems where there are alternative machines that an operation can be assigned to.     

A modelling framework for comparative testing of energy forecasts

A project is described in which a methodology was developed for the comparative testing of medium-term national energy forecasts. The basis of the approach is a computer modelling system which can be used flexibly to investigate the dynamics of alternative assumptions about energy futures. The application of the methodology to the forecasts produced by a particular research group is discussed and the educative value of a modelling approach for the users in this case is explained. The study is intended as a contribution to the U.K. national debate on energy policy.     

Capacitated facility location/network design problems

We introduce a combined facility location/network design problem in which facilities have constraining capacities on the amount of demand they can serve. This model has a number of applications in regional planning, distribution, telecommunications, energy management, and other areas. Our model includes the classical capacitated facility location problem (CFLP) on a network as a special case. We present a mixed integer programming formulation of the problem, and several classes of valid inequalities are derived to strengthen its LP relaxation. Computational experience with problems with up to 40 nodes and 160 candidate links is reported, and a sensitivity analysis provides insight into the behavior of the model in response to changes in key problem parameters.