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W-ECoMP – Web-based Economic Cogeneration Modular Program

Description

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 (currently 50 modules). Each component is described by three subroutines, which define mass and energy flows, off-design performance curves, variables, and capital costs. 

The determination of cost functions for the different modules has been performed thanks to the contribution of TPG’s industrial partners over the last few years and by reference to literature data. Cost functions are updated once a year. 

To increase the evaluation consistency, energy systems are simulated using 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 single components 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 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; key performance indicators such as Internal Rate of Return (IRR), Net Present Value (NPV), and Discounted Pay Back Period (DPBP) are calculated in the techno-economic analysis to evaluate and compare the profitability of different plants.

Fig.3: Low level optimisation flowchart
Fig.4: High level optimisation flowchart

Fields of Applications

  • Power plants: in the figure, a combined cycle in a co-generative configuration, including district heating and thermal storage.
  • Residential users: in the figure, a photovoltaic system is installed in a domestic application.
  • 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 an oxygen-blown biomass gasifier.
  • Polygenerative (electrical, thermal, cooling energy) smart grids, including renewable generators (PV panels, wind turbines, etc.): in the figure, a tri-generative plant for distributed generation includes hot thermal storage and a system of PV panels. Below a screenshot of some modules included in the library is reported.

Projects

  • EU FP7 European Research Project E-HUB (2010 – 2014), Grant Agreement N 260165
  • Bilateral research project “HIDROMETANO“, started in 2010, between the DistrettoTecnologico SIIT (University of Genoa is a partner of SIIT) and the ParqueTechnologico de Itaipu (PTI) – Paraguay
  • H2020 European Research Project MethCO2 (2014 – 2018), Grant Agreement N 637016

Publications

“Time-dependent optimization of a large hydrogen generation plant using “spilled” water at Itaipu14 GW hydraulic plant

Rivarolo M., Bogarin J., Magistri L., Massardo A. F

International Journal of Hydrogen Energy, 2012 (37), 5434-5443.

“Thermo-economic optimization of the impact of renewable generators on poly-generation smart-grids including hot thermal storage”

Rivarolo M., Greco A., Massardo A. F.

Energy Conversion and Management, 2013 (65), 75-83.

“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

“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

“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

“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

“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), 1737-174

“Feasibility study of methanol production from different renewable sources and thermo-economic analysis”

Rivarolo M., Bellotti D., Magistri L., Massardo A. F.

International Journal of Hydrogen Energy, 41 (2016), 2105-2116

“Design optimization of smart poly-generation energy districts through a model based approach”

Rivarolo M., Cuneo A., Traverso A., Massardo A. F

Applied Thermal Engineering, 99 (2016), 291-301.

“Thermo-economic analysis of the energy storage role in a real polygenerative district”

Barberis S., Rivarolo M., Traverso A., Massardo A. F

Journal of Energy Storage, 5 (2016), 187-202.

“Thermo-economic analysis of a hydrogen production system by sodium borohydride (NaBH4)”

Rivarolo M, Improta O., Magistri L., Panizza M., Barbucci A.

International Journal of Hydrogen Energy, 43 (2018), 1606-1614.

“Clean energy production by PEM fuel cells on tourist ships: a time-dependent analysis”

Rivarolo M., Rattazzi D., Lamberti T., Magistri L.

International Journal of Hydrogen Energy, 2020, 45, 25747-25757.

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