Design optimization of multi-energy systems using mixed-integer linear programming: Which model complexity and level of detail is sufficient?

Wirtz, Marco; Hahn, Maria A.; Schreiber, Thomas; Müller, Dirk

doi:10.1016/j.enconman.2021.114249

Cited by 50 publications

(18 citation statements)

References 57 publications

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“…Leuthold et al 54 developed a nonlinear mixed-integer programming model to design an electricity market such that public welfare is maximized, with an application to the European electricity market. Wirtz et al 55 proposed a sustainable multicommodity system design model with the power grid attached to the system using mixed integer linear programming. Electric power networks are critical sources of energy that enable the function of other infrastructures, and developing flow balance optimization models for electric power grids has become important for researchers 56 , as have several network flow optimization representations of interdependent infrastructure networks that include electric power 57 – 60 .…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Protecting infrastructure performance from disinformation attacks

Jamalzadeh

Barker

González

et al. 2022

Sci Rep

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Disinformation campaigns are prevalent, affecting vaccination coverage, creating uncertainty in election results, and causing supply chain disruptions, among others. Unfortunately, the problems of misinformation and disinformation are exacerbated due to the wide availability of online platforms and social networks. Naturally, these emerging disinformation networks could lead users to engage with critical infrastructure systems in harmful ways, leading to broader adverse impacts. One such example involves the spread of false pricing information, which causes drastic and sudden changes in user commodity consumption behavior, leading to shortages. Given this, it is critical to address the following related questions: (i) How can we monitor the evolution of disinformation dissemination and its projected impacts on commodity consumption? (ii) What effects do the mitigation efforts of human intermediaries have on the performance of the infrastructure network subject to disinformation campaigns? (iii) How can we manage infrastructure network operations and counter disinformation in concert to avoid shortages and satisfy user demands? To answer these questions, we develop a hybrid approach that integrates an epidemiological model of disinformation spread (based on a susceptible-infectious-recovered model, or SIR) with an efficient mixed-integer programming optimization model for infrastructure network performance. The goal of the optimization model is to determine the best protection and response actions against disinformation to minimize the general shortage of commodities at different nodes over time. The proposed model is illustrated with a case study involving a subset of the western US interconnection grid located in Los Angeles County in California.

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Section: Background and Literature Reviewmentioning

confidence: 99%

Protecting infrastructure performance from disinformation attacks

Jamalzadeh

Barker

González

et al. 2022

Sci Rep

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“…EC-based CHP can be operated in a flexible way, since steam can usually be extracted from more than one pressure stage, and power may vary with same heat production. In this study, the total energy efficiency of the CHP plant is considered as constant, as suggested in [17,19].…”

Section: Minimum Uptime and Downtimementioning

confidence: 99%

“…The part load efficiency of the gas-fired Heat Only Boiler (HOB) is considered according to the model proposed by [19]. Equation ( 24) provides an expression for the consumption of the HOB boiler, which leads to the non-linear evolution of its efficiency, as shown in Figure 4.…”

Section: Minimum Uptime and Downtimementioning

confidence: 99%

“…First, the modelling of the CHP systems could be more accurate. An increased accuracy of the techno-economic models for the following aspects could lead to more accurate results [19]: Piece-wise Linear Investment functions allowing for a non-linear evolution of the investment costs, and account for part-load efficiencies, start-up costs, CHP acceptable operation ranges and maximum ramp rates, which significantly affect technical and economic performances. Secondly, few recent works [15,16] integrated multi-objective optimization models with decision making methods to optimize the capacity and the operation strategy of TES and RES integrated to existing CHP systems.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimal Integration of Solar Heating and Heat Storage into Existing Fossil Fuel-Based Heat and Power Production Systems

Wang

Blondeau

2022

Energies

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Increasing the share of Renewable energy sources in District Heating (DH) systems is of great importance to mitigate their CO2 emissions. The combined integration of Solar Thermal Collectors (STC) and Thermal Energy Storage (TES) into existing Combined Heat and Power (CHP) systems can be a very cost-effective way to do so. This paper aims at finding the optimal design of STC and TES systems integrated in existing CHP’s considering two distinct objectives: economic profitability and environmental impact. To do so, we developed a three-stage framework based on Pareto-optimal solutions generated by multi-objective optimization, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-entropy method to select the optimal solution, followed by the definition of final Operation strategy. We proposed relevant improvement of the state-of-the-art models used in similar analysis. We also applied the proposed methodology to the case of a representative, 12 MWth CHP plant. Our results show that, while the addition of TES or STC alone results in limited performances and/or higher costs, both the cost and the CO2 emissions can be reduced by integrating the optimal combination of STC and TES. For the selected, optimal solution, carbon emissions are reduced by 10%, while the Annual Total Cost (ATC) is reduced by 3%. It also improves the operational flexibility and the efficiency by peak load shaving, load valley filling and thus by decreasing the peak load boiler operation. Compared to the addition of STC alone, the use of TES results in an increased efficiency, from 88% to 92%. The optimal share of STC is then increased from 7% to 10%.

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“…Kotzur et al 's two-time layers enable seasonal storage calculation while deploying typical days. In (Beck et al 2022;Göke and Kendziorski 2022;Wirtz et al 2021;Neumann et al 2022;von Wald et al 2022;Hoffmann et al 2020) the storage formulation of Kotzur et al was applied to calculate seasonal storages. Gabrielli et al (2018) developed a different approach to calculate seasonal storage with fewer constraints but more variables.…”

Section: Introductionmentioning

confidence: 99%

Time series aggregation for energy system design: review and extension of modelling seasonal storages

et al. 2022

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Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results.

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Design optimization of multi-energy systems using mixed-integer linear programming: Which model complexity and level of detail is sufficient?

Cited by 50 publications

References 57 publications

Protecting infrastructure performance from disinformation attacks

Protecting infrastructure performance from disinformation attacks

Multi-Objective Optimal Integration of Solar Heating and Heat Storage into Existing Fossil Fuel-Based Heat and Power Production Systems

Time series aggregation for energy system design: review and extension of modelling seasonal storages

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