A general MILP based optimization framework to design Energy Hubs

Gotze, Jens; Dancker, Jonte; Wolter, Martin

doi:10.1515/auto-2019-0059

Cited by 12 publications

(4 citation statements)

References 33 publications

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“…In this case, c sto inv ,var ,a (Eur/kWh/a) and c sto op,fix,a (Eur/kWh/a) refer to the maximum usable energy capacity E sto max (kWh). Furthermore, the annual costs of importing electricity and gas from their respective grids are taken into account according to (8), where c EG imp,t and c GG imp,t (Eur/kWh) are the prices of electricity and gas, respectively, while P EG imp,t and P GG imp,t is the corresponding imported powers at a time step t.…”

Section: Cost-minimization Functionmentioning

confidence: 99%

“…A remuneration of 0.0305 Eur/kWh is additionally awarded for the own consumption of CHP electricity [13]. Concerning the costs of technologies, linear investment functions and operating costs have been extracted from several studies and market data for PV [22], battery [9], gas CHP, gas boiler, heat pumps, heat storage [23], FC-CHP [24], electrolyzer [25], hydrogen compressor [26] and hydrogen storage [8] units. Furthermore, only emissions from importing electricity and gas from respective grids are taken into account in this study.…”

Section: Input Datamentioning

confidence: 99%

“…It has been found that gas-based fuel cells were not optimally selected. Another optimization model to design energy hubs was introduced in [8]. It involved a fuel cell, an electrolyzer, a compressor and a refueling station.…”

Section: Introductionmentioning

confidence: 99%

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Economic and Environmental Impacts of Integrating Hydrogen-Based Technologies in the Design Optimization of Sector-Coupling Energy Systems in Residential Districts

Eldakadosi

Schneeloch

2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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Recent policies which promote climate-neutral energy systems and rising energy prices overburden the planners of energy supply systems. This leads to an increasing need for cost-effective, yet environmental-friendly, solutions. One interest-arousing approach is utilizing hydrogen-based technologies within cross-sectoral, residential energy systems. However, the economic and environmental potentials of this approach have not yet been fully uncovered. Hence, the aim of this work is to investigate the impacts of considering hydrogen-based technologies on the total costs and CO 2 emissions when designing a residential energy system. For this purpose, we developed a design optimization model using mixed-integer linear programming, whose main objective function is the minimization of total costs. The minimization of total CO 2 emissions is implemented as an epsilon constraint, where a Pareto front is created to represent optimal solutions under both objectives and their trade-off. Consequently, the optimal sizing and operation plan of the considered technologies to fulfill the energy demands of the residents are determined. Besides hydrogen-based fuel cells, electrolyzers, compressors and storage systems, the model includes photovoltaics, batteries, gas-based combined heat and power units, heat pumps, gas boilers and heat storage. For a case study of an exemplary German residential district, we carried out the design optimization for three energy systems, where two involved typical sector-coupling generation units and one included hydrogen technologies. Through the resulting Pareto fronts, we found that the energy system with hydrogen had a comparable, yet limited performance in terms of emissions reduction. However, the hydrogen system showed a poor economic competitiveness.

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Section: Cost-minimization Functionmentioning

confidence: 99%

Section: Input Datamentioning

confidence: 99%

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Economic and Environmental Impacts of Integrating Hydrogen-Based Technologies in the Design Optimization of Sector-Coupling Energy Systems in Residential Districts

Eldakadosi

Schneeloch

2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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“…In recent literature, numerous optimization models and frameworks have been presented [2,10], for example the oemof framework [12], Ehub Modeling Tool by EMPA (Switzerland) [4], or the DER‐CAM model by Lawrence Berkeley National Laboratory [21]. In addition, user‐friendly applications for designing energy systems have been developed: The National Renewable Energy Laboratory, developed the free and open‐source webtool REopt for designing electrical systems (microgrids with photovoltaics [PV], wind turbines, and batteries), which uses an MILP in the calculation [17].…”

Section: Introductionmentioning

confidence: 99%

EHDO: A free and open‐source webtool for designing and optimizing multi‐energy systems based on MILP

Wirtz

Remmen

Müller

2020

Comp Applic In Engineering

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This paper presents a novel webtool, called Energy Hub Design Optimization tool, for designing and optimizing complex multi‐energy systems. The tool determines the optimal technology selection and sizing of all energy conversion units of a supply system while satisfying heat, cold, electricity, and hydrogen demands. A large variety of different technologies including renewable energies (wind power, photovoltaic, solar thermal, and hydroelectricity) and energy carriers like natural gas, hydrogen, biomass, and waste can be considered. Energy demands are provided by the user with an hourly resolution and all technical and economic model parameters can be tailored to specific use cases. The objective functions of the design optimization are total annualized costs, CO2 emissions, or trade‐offs between both objectives (multi‐objective optimization). The calculation is based on mathematical optimization and uses a mixed‐integer linear program. The webtool is accessible online for free and the optimization model is open‐source. The webtool has been developed to support academic teaching in energy engineering courses. With the tool, students understand how energy supply systems with intermittent renewable energies and cross‐sectoral conversion and storage technologies can be designed with innovative planning approaches.

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Operational planning of distributed energy generation for a semiconductor fabrication plant

Poemsl

Siddiqui

2022

Elektrotech. Inftech.

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The semiconductor industry is well known for its high resource consumption due to its clean room usage and power-intensive manufacturing technology. This is a significant financial burden for semiconductor fabrication plant owners who wish to minimize the cost needed to cover the electricity and gas loads for their daily operations. From a historical perspective, those electricity and gas cost reductions have been enabled by more energy-efficient manufacturing technologies. Due to the complexity of factors influencing the energy system of a semiconductor plant, other aspects have often been neglected and also not been studied intensively in the academic literature so far. One possibility for reducing energy costs is the integration of a microgrid as on-site distributed energy resources (DER) may offer a less cost-intensive way to supply the energy needed. Therefore, this paper seeks to answer the following research question: How much expected cost can be saved and risk mitigated at a semiconductor fabrication plant via DER? More precisely, in this paper, a microgrid at a semiconductor fabrication plant that has installed DER with combined heat and power (CHP) applications and demand response (DR) is used to simulate the expected annual energy costs under given uncertain electricity and gas prices at different installed capacity levels. A simulation-based approach is used to evaluate several DER capacity sizes. The results of the simulation show that installations of DER at a semiconductor microgrid can dominate the base case of doing nothing, considering the expected minimized cost, the expected CO2 emissions, and conditional value-at-risk (CVaR). In fact, DER can reduce the expected annual energy bill by up to 6%, whereas annual expected CO2 emissions can even be reduced by up to 22%. Moreover, with DER, a microgrid’s risk is reduced as it can react to market conditions and local demand. Additionally, the true potential of microgrid cost savings can only be enabled when DR is allowed and proves particularly effective when energy prices are more volatile.

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A general MILP based optimization framework to design Energy Hubs

Cited by 12 publications

References 33 publications

Economic and Environmental Impacts of Integrating Hydrogen-Based Technologies in the Design Optimization of Sector-Coupling Energy Systems in Residential Districts

Economic and Environmental Impacts of Integrating Hydrogen-Based Technologies in the Design Optimization of Sector-Coupling Energy Systems in Residential Districts

EHDO: A free and open‐source webtool for designing and optimizing multi‐energy systems based on MILP

Operational planning of distributed energy generation for a semiconductor fabrication plant

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