Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling

Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian

doi:10.1016/j.energy.2014.04.023

Cited by 91 publications

(65 citation statements)

References 16 publications

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“…This problem might also be defined as nonlinear and solved using some appropriate method. It is also possible to use the moving-horizon short-term optimization approach [10,11]. If it is satisfactory for the user, operation regimes might be just assumed, without doing optimization at all, etc.…”

Section: Optimization Methodsmentioning

confidence: 99%

“…They are solved fast, using linear programming (LP) techniques. Lower bounds on component loads are not defined, due to the absence of the on/off variables, and this can lead to the results being infeasible in practice [11]. More complex problems are usually harder to solve, but often better represent an actual state.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the complexity of mathematical models is a matter of compromise. The importance of considering details and choosing the optimization methods is analyzed in [11,12].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

Stojiljković

Blagojević

2014

Energies

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In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings' energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. The main problem of synthesis and design optimization is combinatorial and solved with different metaheuristic methods. For each examined combination of the synthesis and design variables, when calculating the values of the objective functions, the inner, mixed integer linear programming operation optimization problem is solved with the branch-and-cut method. The applicability of the exploited metaheuristic methods is demonstrated. This approach is compared with the alternative, superstructure-based approach. The potential for combining them is also examined. The methodology is applied for multi-objective optimization of a trigeneration plant that could be used for the energy supply of a real residential settlement in Niš, Serbia. Here, two objectives are considered: annual total costs and primary energy consumption. Results are obtained in the form of a Pareto chart using the epsilon-constraint method.Energies 2014, 7 8555

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Section: Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

Stojiljković

Blagojević

2014

Energies

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“…A CHP plant is normally one of two distinct types of construction: a backpressure unit or extractiontype unit [10,16,22,23]. The former typically has a fixed ratio  of thermal power generation (Q) to electrical power generation (P), and operates by reclaiming heat from the steam exiting the turbine.…”

Section: Technology Overviewmentioning

confidence: 99%

Load forecasting and dispatch optimisation for decentralised co-generation plant with dual energy storage

et al. 2017

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“…Due to the complexity of the real world, a model is always a simplified representation of real systems. Linearised description of energy systems is one prominent example of necessary simplification applied in models that may have strong impact on results [51]. Structural uncertainty has special importance for long-term planning models as they may cannot be fully validated [52].…”

Section: Uncertaintymentioning

confidence: 99%

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Hilpert¹,

Günther²,

Kaldemeyer³

et al. 2017

Preprint

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These authors contributed equally to this work. AbstractThe process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult.In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities.Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

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Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling

Cited by 91 publications

References 16 publications

Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

Load forecasting and dispatch optimisation for decentralised co-generation plant with dual energy storage

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

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