Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems

Mavromatidis, Georgios; Orehounig, Kristina; Carmeliet, Jan

doi:10.1016/j.apenergy.2018.01.062

Cited by 200 publications

(99 citation statements)

References 71 publications

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“…This variance-based method quantifies the contribution of each input variable to the output's variance. It has been used regularly on energy related matters [39,40,41,42,43] and shows significant advantages over other sensitivity analysis methods: it makes no assumption on the model's behaviour (e.g. linearity), provides straightforward interpretation through quantitative ranking of variable importance and is capable of evaluating interactions effects between variables [44].…”

Section: Global Sensitivity Analysismentioning

confidence: 99%

Multi-temporal assessment of power system flexibility requirement

Heggarty

Bourmaud²,

Girard

et al. 2019

Applied Energy

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In power systems, flexibility can be defined as the ability to adapt to variability and uncertainty in demand and generation. Various ongoing changes in the power system are impacting the need for flexibility. We propose a novel methodology to (i) evaluate annual, weekly and daily flexibility requirements through a set of frequency spectrum analysis based metrics, (ii) examine the sensitivity of these flexibility requirements to five variables: the degree of network interconnection and the penetration of wind power, solar power, electric heating and cooling. The proposed methodology is validated on a case study focusing on the French power system, while accounting for its electrically connected neighbours. We provide an estimation of how flexibility requirements are likely to evolve in years to come; the use of global sensitivity analysis allows the identification of the variables responsible for these evolutions. The presented methodology and results can be used to identify future challenges, to evaluate the market potential of flexibility solutions and to assess the implications of policy decisions.

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Section: Global Sensitivity Analysismentioning

confidence: 99%

Multi-temporal assessment of power system flexibility requirement

Heggarty

Bourmaud²,

Girard

et al. 2019

Applied Energy

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“…The equipment capacity must be identified at the design stage, and the mode of operation should lead to an economic optimum. In the stage after the sensitivity analysis research, a multitude of uncertainties were taken into consideration for the design of the DES [7], including the instability of the renewable energy output caused by ambient conditions and the fluctuation of energy demand. Pang et al [8] optimized the configurations and control parameters of the gas-fired domestic hot water supply systems in commercial buildings by applying uncertainty and sensitivity analysis.…”

Section: Introductionmentioning

confidence: 99%

Three-stage optimization method for distributed energy system design under uncertainty

Wang

Peng

et al. 2021

Therm sci

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Reasonable capacity configurations of distributed energy system are issues which need to be discussed. Determinate design without considering variations in energy load and energy prices can result in non-achievement of project targets during its service life. Therefore, a design method that takes into account uncertain factors takes precedence over other methods. In this paper, a three-stage optimization method is proposed to provide theoretical guidance on the optimization of combined cooling, heating and power (CCHP) system configurations. The first two stages link the optimization of the operation strategy and equipment capacities simultaneously under current load and energy prices. The Monte-Carlo Simulation is applied in the third stage to fully consider the effects of various possible scenarios, and the Tabu search algorithm (TS) was introduced for system optimization. The comprehensive benefits include energy consumption, economy, and emission level. These were taken into consideration in the objective function. Moreover, a detailed design process was presented to illustrate the application of the proposed method. In conclusion, the proposed method is not only suitable for the design of CCHP system, but could easily extend to other energy system easily.

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“…Each of these parameters can only be specified within a certain range of uncertainty. Although recommended by DeCarolis et al [38], these uncertainties are, however, only rarely addressed in current power system models [39]. A possible way to characterize them has for instance been described by Moret et al [40].…”

Section: Introductionmentioning

confidence: 99%

How regional differences in cost of capital influence the optimal design of power systems

Schyska¹,

Kies

2020

Applied Energy

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In order to reduce greenhouse gas emissions of the power sector, high shares of renewable power sources need to be integrated into existing systems. This will require vast amounts of investments. Cost of the capital needed for these investments are unevenly distributed among European regions. They show a clear North-South and West-East divide, which has not exhibited significant signs of narrowing in recent years. Power system studies investigating a continent-wide European power system, however, usually assume homogeneous cost of capital.The objective of this paper is to investigate how regional differences in cost of capital affect the result of these studies with respect to the optimal power system design. Our analysis is based on power system optimization with inhomogeneous cost of capital in Europe. We find that assuming homogeneous cost of capital leads to estimates on the levelized costs of electricity in a highly renewable European power system, which are too conservative. The optimal system design is significantly affected compared to an inhomogeneous scenario. In particular, we show that inhomogeneous cost of capital favors overall wind power deployment in the case of Europe, while the investment in solar power decreases.

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Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems

Cited by 200 publications

References 71 publications

Multi-temporal assessment of power system flexibility requirement

Multi-temporal assessment of power system flexibility requirement

Three-stage optimization method for distributed energy system design under uncertainty

How regional differences in cost of capital influence the optimal design of power systems

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