W-ECoMP is a modular and flexible software tool, which aims at the thermo-economic, time-dependent analysis and optimization of energy systems, including off-design conditions.
W-ECoMP is characterized by a modular approach and a standard component interface, which allows the user to build complex cycle configurations in a short time. This approach maintains the flexibility and the extendibility of library components (48 modules at the moment). Each component is described by three subroutines, which define mass and energy flows, off-design performance curves, variable and capital costs.
The determination of cost functions for the different modules has been performed thanks to the contribution by TPG’s industrial partners over the last few years and by reference to literature data. Cost functions are updated once a year.
In order to increase the evaluation consistency, energy systems are simulated by means of specific performance curves that fit experimental/calculated data describing the off-design behavior of each component in the library.
Concept and Approach
The modular structure of the software allows users for combining the single components in order to analyze a wide typology of plants. In addition, the analysis of the same plant can be performed considering different economic scenarios, investigating the influence of one or more parameters variation on the global performances of the energy system.
One of the most important features of W-ECoMP is the possibility of performing the thermo-economic analysis at two different hierarchical levels, to optimize respectively:
- the operating strategy for existing energy systems (low level)
- the size of one or more components during the plant design (high level)
Capital and variable costs are considered for the system size optimization, while only variable costs are considered to optimize the operating strategy of existing energy systems. In the design optimization, the size of each component is evaluated together with its capital cost. The evaluation of the optimal operating strategy is then carried out at the lower level of optimization according to the actual energy load demands (i.e. electricity, heating and cooling energy).
The objective function is usually selected as the total costs/revenues balance within the plant operating life; parameters such as Internal Rate of Return (IRR), Net Present Value (NPV) and Discounted Pay Back Period (DPBP) are calculated in the economic analysis in order to evaluate and compare the profitability of different plants.
Fields of Application
- Power plants: in the figure, a combined cycle in a co-generative configuration, including district heating.
- Residential users: in the figure, a photovoltaic system installed in a domestic application.
- Poly-generative (electrical, thermal, cooling energy) smart grids, including renewable generators (PV panels, wind turbines, etc.): in the figure, a tri-generative plant for distributed generation including a hot thermal storage and a system of PV panels as well.
- Innovative energy storage plants and chemical production: in the figure a plant for bio-methane production from renewable sources integrating hydrogen by water electrolysis and syngas from oxygen-blown biomass gasifier.
EU FP7 European Research Project E-HUB (2010 – 2014), Grant Agreement N 260165, aimed at the optimization of an Energy-Hub for residential and commercial districts, including interaction with the transportation system. Inside the project W-ECoMP software was employed, principally, for the thermo-economic analysis of the poly-generative smart grid installed in the University Campus of Savona (Italy): in particular, a model able to determine the best operational strategy throughout the year of all the generators (mGTs, ICEs, boilers, PV panels) installed in the Energy-Hub was developed, taking into proper account the performances of the generators in off-design conditions and the time-dependent nature of electrical, thermal and cooling demands of the Campus. In a second step the software was also utilized to simulate one of the case studies included in the project, precisely Tweewaters district in Leuven, Belgium.
Bilateral research project “HIDROMETANO“,started in 2010, between the DistrettoTecnologico SIIT (University of Genoa is a partner of SIIT) and the ParqueTechnologico deItaipu (PTI) – Paraguay. The study involves large size hydrogen and hydro-methane (a blend of methane and hydrogen) production in the specific Paraguay environment, where electricity surplus exists, thanks to theItaipu dam. Itaipurepresents the largest hydroelectric facility in the world in terms of energy production (more than 98,000 GWh/year).W-ECoMPsoftware was employed for the thermo-economic analysis in order to take into proper account the strong time-dependent nature of the water available to the hydraulic turbines and the electric demands of the two countries (Brazil and Paraguay),co-owners of the dam. The final aim of the investigation was the best size and management of the hydrogen and hydro-methane production plants.
H2020 European Research Project MethCO2 (2014 – 2018), Grant Agreement N 637016, aimed at the synthesis of Methanol from captured carbon dioxide using surpluselectricity. Methanol is synthesized by CO2 and by H2 produced by alkaline electrolysers fed by renewable electricity (PV panels). W-ECoMP software is employed for the thermo-economic analysis of the whole system, comparing different energetic and economic scenarios. In particular, a model able to determine the optimalsize for thecomponents of the plant (PV panels, electrolysers, methanol reactor) is developed, taking into proper account the performances of the generators in off-design conditions and the time-dependent nature of the solar irradiation curves at different locations.
“Thermo-economic optimization of the impact of renewable generators on poly-generation smart-grids including hot thermal storage”
M. Rivarolo, A. Greco, A.F. Massardo
Energy Conversion and Management 65 (2013) pp. 75–83.
In this paper, the impact of not controllable renewable energy generators (wind turbines and solar photovoltaic panels) on the thermo-economic optimum performance of poly-generation smart grids is investigated using an original time dependent hierarchical approach. The grid used for the analysis is the one installed at the University of Genoa for research activities. It is based on different prime movers: (i) 100 kWe micro gas turbine, (ii) 20 kWe internal combustion engine powered by gases to produce both electrical and thermal (hot water) energy and (iii) a 100 kWth adsorption chiller to produce cooling (cold water) energy. The grid includes thermal storage tanks to manage the thermal demand load during the year. The plant under analysis is also equipped with two renewable non controllable generators: a small size wind turbine and photovoltaic solar panels. The size and the management of the system studied in this work have been optimized, in order to minimize both capital and variable costs. A time-dependent thermo-economic hierarchical approach developed by the authors has been used, considering the time-dependent electrical, thermal and cooling load demands during the year as problem constraints. The results are presented and discussed in depth and show the strong interaction between fossil and renewable resources, and the importance of an appropriate storage system to optimize the RES impact taking into account the multiproduct character of the grid under investigation.
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“Hydrogen and methane generation from large hydraulic plant: Thermo-economic multi-level time-dependent optimization”
M. Rivarolo, L. Magistri , A.F. Massardo
Applied Energy, 2014 (113), 1737-1745
This paper investigates hydrogen and methane generation from large hydraulic plant, using an original multilevel thermo-economic optimization approach developed by the authors.Hydrogen is produced by water electrolysis employing time-dependent hydraulic energy related to the water which is not normally used by the plant, known as ‘‘spilled water electricity’’. Both the demand for spilled energy and the electrical grid load vary widely by time of year, therefore a time-dependent hour-by-hour one complete year analysis has been carried out, in order to define the optimal plant size. This time period analysis is necessary to take into account spilled energy and electrical load profiles variability during the year.The hydrogen generation plant is based on 1 MWe water electrolysers fuelled with the ‘‘spilled waterelectricity’’, when available; in the remaining periods, in order to assure a regular H2 production, the energy is taken from the electrical grid, at higher cost. To perform the production plant size optimization,two hierarchical levels have been considered over a one year time period, in order to minimize capital and variable costs.After the optimization of the hydrogen production plant size, a further analysis is carried out, with aview to converting the produced H2 into methane in a chemical reactor, starting from H2 and CO2 whichis obtained with CCS plants and/or carried by ships. For this plant, the optimal electrolysers and chemical reactors system size is defined.For both of the two solutions, thermo-economic optimization results are discussed and compared with particular emphasis to energy scenario, economic aspects, system size, capital costs and related investments.It is worth noting that the results reported here for this particular large H2 plant case representsa general methodology, since it can vary according to their different sizes, primary renewable energy,plant location, and different H2 utilization.
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“Thermo-economic optimization of CSP hybrid power plants with thermal storage”
S. Barberis, M. Rivarolo, A. Traverso
Proceedings of ASME Turbo Expo 2014: Turbine Technical Conference and Exposition GT2014, June 16-20, 2014, Dusseldorf, Germany GT2014-25137
Starting from a state of the art of CSP plants, the paper investigates alternative plant configurations, assessed and compared with a through-life thermo-economic analysis. Plant layouts include thermal storage to manage the load demand ofthe plant throughout the day, considering both variable solar input and variable power demand. Focus is on the impact of thermal storage devices on optimal layouts.The hybrid combined CSP plants are analyzed using original software tools, WTEMP for the design point analysis and W-ECoMP for the time-dependent thermo-economic optimization, to take into proper account the time-dependent nature of both the electrical load demand and the hour-by-hour irradiation during the year.The analysis shows that combining CSP technology with existing combined cycles a significant reduction of fuel consumption and greenhouse gas emissions is obtained, with an optimal solar share factor of about 20%, providing the grid with fully dispatchable power generation.
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Optimization of large scale bio-methane generation integrating “spilled” hydraulic energy and pressurized oxygen blown biomass gasification
M. Rivarolo, A.F. Massardo
International Journal of Hydrogen Energy, 2013 (38), 4986-4996
This paper investigates large-scale bio-methane generation from renewable sources, mixing hydrogen produced by water electrolysis and syngas obtained by pressurized oxygen blown biomass gasification.Hydrogen is produced by water electrolysis employing time-dependent hydraulic energy related to the water which is not normally used by the plant, named “spilled water electricity”. The oxygen, also obtained in the electrolysis process, is employed for biomass gasification to produce syngas: after purification treatments, the syngas is mixed with hydrogen in a chemical reactor to obtain bio-methane.The whole process is optimized here using two different thermo-economic approaches: (i) for the design point analysis of the chemical and thermodynamic significant parameters in electrolysis, gasification, syngas purification and methanation processes; (ii) for an entire one-year time-dependent analysis in order to define the optimal plant size, since the spilled energy and the electrical grid load vary widely throughout the day and the year. The hydrogen generation plant is based on 1 MWe water electrolysers using the “spilled waterelectricity”, when available; in the remaining periods, in order to assure a regular H2 production, the energy is taken from the electrical grid, but at a higher cost.It is worth noting that the methane produced, named bio-methane, is totally “CO2 free”, since it is produced from renewable sources only. Moreover, the optimization method presented here has a general value, thus it can be easily applied to different sizes, economic scenarios and plant locations.
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“Hydro-methane and methanol combined production from hydroelectricity and biomass: thermo-economic analysis in Paraguay”
M. Rivarolo, D. Bellotti, A. Mendieta, A.F. Massardo
Energy Conversion and Management, 2014 (79), 74-84
A thermo-economic analysis regarding large scale hydro-methane and methanol production from renewable sources (biomass and renewable electricity) is performed. The study is carried out investigating hydrogen and oxygen generation by water electrolysis, mainly employing the hydraulic energy produced from the 14 GW Itaipu Binacional Plant, owned by Paraguay and Brazil. Oxygen is employed in biomass gasification to synthesize methanol; the significant amount of CO2 separated in the process is mixed with hydrogen produced by electrolysis in chemical reactors to produce hydro-methane.Hydro-methane is employed to supply natural gas vehicles in Paraguay, methanol is sold to Brazil, that is the largest consumer in South America. The analysis is performed employing time-dependent hydraulic energy related to the water that would normally not be used by the plant, named “spilled energy”, when available; in the remaining periods, electricity is acquired at higher cost by the national grid. For the different plant lay-outs, a thermo-economic analysis has been performed employing two different software, one for the design point and one for the time-dependent one entire year optimization, since spilled energy is strongly variable throughout the year. Optimal sizes for the generation plants have been determined, investigating the influence of electricity cost, size and plant configuration.
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“Design optimization of smart poly-generation grids through a model based approach”
A. Cuneo, A. Greco, M. Rivarolo and A. F. Massardo
Proceedings of ECOS 2014, June 15-19, Turku, Finland
This paper presents a time-dependent thermo-economic hierarchical approach to the investigation of smart poly-generation grids determining the optimal size of different prime movers in order to meet the energy (electrical, thermal, cooling) demands of a generic user. A specific case study was developed around the smart poly-generation grid at the University of Genoa, Savona Campus (Italy), operational since 2013. In an initial configuration, the grid included different co-generative prime movers, renewable generators and a thermal storage system to manage the thermal load demand over the year. A second layout used a tri-generative plant including an absorption chiller to also meet campus cooling demand. The simulation method considered the time-dependent energy load demands as problem constraints. This approach enabled both the optimal size and management for each component of the poly-generation grid to be determined for the entire year by giving due consideration to both energy and economic features.The results enabled the identification of the best configuration from the thermo-economic standpoint for the considered scenario. The proposed method is easily replicated for different applications and configurations of smart poly-generation grids.
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