Multi criteria dynamic design optimization of a small scale distributed energy system

Rieder, Andreas; Christidis, Andreas; Tsatsaronis, George

doi:10.1016/j.energy.2014.06.007

Cited by 51 publications

(35 citation statements)

References 14 publications

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“…Kim & Edgar, 2014;Rieder, Christidis & Tsatsaronis, 2014 and Section 5). However, our units are equipped neither with powerful computers nor with sophisticated solver soft-ware.…”

Section: Methodological Approach Of the Case Studymentioning

confidence: 99%

An efficient two-stage algorithm for decentralized scheduling of micro-CHP units

Jochem

Schönfelder

Fïchtner

2015

European Journal of Operational Research

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In this paper we present an efficient two-stage hierarchical decomposition algorithm aiming at determining economically improved operation schedules for residential proton exchange membrane fuel cell microcombined heat and power (PEMFC micro-CHP) units and optimizing local charging of electric vehicles (EV) in the same household. Based on an individual short-term load forecasting (STLF) approach (imperfect forecast) for households implemented as an adaptive network-based fuzzy inference system (ANFIS), a mixed-integer linear program (MILP) and a two-stage greedy algorithm are used for determining optimized schedules based on a rolling-window approach. The results of the case study performed for eight variants in exemplary German households reveal that with both the MILP and the algorithmic approach, significant economic savings can be achieved compared to the standard heat-led strategy. Compared to the MILP, however, the two-stage algorithm has the additional advantage of a reduced computing time of only about 151 . Deviations from the MILP solutions are mostly smaller than 3 percent regarding the annual supply costs. Moreover, the comparison between the use of perfect and imperfect demand forecasts quantifies additional average losses due to forecasting errors of 2 percent and 3.3 percent at the maximum. Altogether, the algorithmic approach Postprint of the article "An efficient two-stage algorithm for decentralized scheduling of micro-CHP units" In European Journal of Operational Research, Volume 245, Issue 3, Pages 862-874, https://doi.org/10.1016/j.ejor.2015 3 seems to be convincing for real applications in households due to its good results, high reliability, easy implementation, and short computing times. The combination of a micro-CHP unit and an EV is highly synergetic.

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“…Kim & Edgar, 2014;Rieder, Christidis & Tsatsaronis, 2014 and Section 5). However, our units are equipped neither with powerful computers nor with sophisticated solver soft-ware.…”

Section: Methodological Approach Of the Case Studymentioning

confidence: 99%

An efficient two-stage algorithm for decentralized scheduling of micro-CHP units

Jochem

Schönfelder

Fïchtner

2015

European Journal of Operational Research

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“…Although an hourly time step is generally implemented, various step sizes have also been used in the literature. For example, Rieder et al considered a 4 h time interval in their optimisation study due to a compromise between computational cost and the ability to capture the behaviour of the considered storage technology [7], while Tveit et al captured the behaviour of seasonal storage with 13 periods per year [13].…”

Section: Multiple Time Gridsmentioning

confidence: 99%

“…For example, the size and charge/discharge behaviour of a storage equipment will influence the trade-off between the capital and operational costs of the overall system. This is typically included in the optimisation study of an energy system, for example in the case of building energy systems [5], microgrids [6], district heating networks [7], and urban energy systems [8].…”

Section: Introductionmentioning

confidence: 99%

Multiple time grids in operational optimisation of energy systems with short- and long-term thermal energy storage

Renaldi

Friedrich

2017

Energy

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As a vital part of future low carbon energy systems, storage technologies need to be included in the overall optimisation of energy systems. However, this comes with a price of increasing complexity and computational cost. The increase in complexity can be limited by using simplified time series formulations in the optimisation process, e.g. typical days or multiple time grids. This in turn will affect the computational cost and quality of the optimisation results. The trade-off between these two aspects has to be quantified in order to appropriately use the simplification method. This paper investigates the implementation of the multiple time grids approach in the optimisation of a solar district heating system with short-and long-term thermal energy storage. The multiple time grids can improve the optimisation computational time by over an order of magnitude. Nevertheless, this is not a general rule since it is shown that there is a possibility for the computational time to increase with time step size. Furthermore, the benefits of multiple time grids become more evident in optimisation with a longer time horizon, reaching almost two order of magnitude improvement in computational time for the case with 6 years time horizon and 5% MIP gap.

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“…In [7,8], the methodologies for choosing typical days i.e., periods, are suggested. In contrast, in [9], a full year is analyzed, although with a somewhat longer time step of 4 h. In [10], the consideration of a whole observed period is suggested based on moving-horizon short-term operation optimization.…”

Section: Introductionmentioning

confidence: 99%

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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Multi criteria dynamic design optimization of a small scale distributed energy system

Cited by 51 publications

References 14 publications

An efficient two-stage algorithm for decentralized scheduling of micro-CHP units

An efficient two-stage algorithm for decentralized scheduling of micro-CHP units

Multiple time grids in operational optimisation of energy systems with short- and long-term thermal energy storage

Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

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