A review of renewable energy based cogeneration technologies

Raj, N. Thilak; Iniyan, S.; Goić, Ranko

doi:10.1016/j.rser.2011.06.003

Cited by 161 publications

(68 citation statements)

References 103 publications

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“…The fuel cost is 33 €/ MWh for the biomass (wood pellets) and 36.55€/ MWh for the natural gas. For the test case 1 where the heat is produced locally, the natural gas costs 55.9 €/MWh [3] 4 . The electricity produced by the CHP plant is used by the University and accounted at the value of 112.7 €/MWhe.…”

Section: Cost Of Heatmentioning

confidence: 99%

“…The part coming from the investment of the DH network is also mentioned. For test case 3, the costs related to the backup boilers and CHP and mentioned and the average is assessed through relation (4).…”

Section: Cost Of Heatmentioning

confidence: 99%

“…The high level of conversion efficiencies (in the range 70-90% [4]) combined to the allocation of subsidies enables a significant decrease of the heat cost. However, at the level of feasibility studies, rule of thumbs based on existing installations are often used which does not guarantee a competitive cost of heat.…”

Section: Introductionmentioning

confidence: 99%

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Simulation and optimization of a CHP biomass plant and district heating network

2014

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Biomass Combined Heat and Power (CHP) plants connected to district heating (DH) networks are recognized nowadays as a very good opportunity to increase the share of renewable sources into energy systems. However, as CHP plants are not optimized for electricity production, their operation is profitable only if a sufficient heat demand is available throughout the year. Most of the time, pre-feasibility studies are based on peak power demand and business plans only assume monthly or yearly consumption data. This approach usually turns out to overestimate the number of operating hours or oversize the plant capacity.This contribution presents a methodology intended to be simple and effective that provides accurate estimations of economical, environmental and energetic performances of CHP plants connected to district heating networks. A quasi-steady state simulation model of a CHP plant combined with a simulation model of the district heating network installed on the Campus of the University in Liège (Belgium) is used as an application framework to demonstrate the effectiveness of the selected approach. Based on the developed model and actual consumption data, several scenarios for energy savings are considered and ranked. The potential energy savings and resulting energy costs are estimated enabling more general conclusions to be drawn on the opportunity of using district heating networks in urban districts for Western Europe countries.

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Section: Cost Of Heatmentioning

confidence: 99%

Section: Cost Of Heatmentioning

confidence: 99%

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Simulation and optimization of a CHP biomass plant and district heating network

2014

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“…The most developed CHP technologies used for industrial and domestic applications are internal combustion engines (ICE) (Onovwiona et al 2007), fuel cells (FC) (Stafell and Green 2013), microturbines (MT) (Meybodi and Behnia 2012) and Stirling engines (Conroy et al 2013). Due to the differences in design and operation of these technologies, all of them are different considering capital and maintenance costs, thermal and electric efficiencies and size available in the market (Raj et al 2011). The use of cogeneration for embedded generation helps to minimize losses of electric energy associated with its transmission from centralized power plants; the construction of central electric power plants and reliable utility grids led to the reduction in the cost of electricity (Lasseter 2011).…”

Section: Introductionmentioning

confidence: 99%

Involving Environmental Assessment in the Optimal Design of Domestic Cogeneration Systems

Morales-Durán

Fuentes-Cortés

González-Brambila

et al. 2017

Process Integr Optim Sustain

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This paper presents a multi-objective optimization formulation for designing domestic cogeneration systems to satisfy thermal and electric energy demands. The proposed model is formulated as a multi-objective mixed-integer nonlinear programming model, which incorporates as economic objective function the minimization of the total annual cost, which includes the capital costs for the new units and the thermal storage system as well as the operating and maintenance costs. The model also incorporates an environmental objective function, which accounts for the life cycle assessment through the Eco-indicator 99 method to account for the damages to the resources, human health, and ecosystem quality. The proposed model allows considering the interaction with the external users and the external electric grid. The optimization formulation is solved to generate design alternatives to establish tradeoffs among the considered objectives.

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“…It is referred to D. Connolly [2010] for a detailed review. Besides, simulation and modeling of biomass based cogeneration systems are reviewed in Raj et al [2011]. Most of these publications carried out only simulations, while system design optimization is neglected.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objectives, Multi-Period Optimization of district heating networks Using Evolutionary Algorithms and Mixed Integer Linear Programming (MILP)

Fazlollahi¹,

Bungener²,

Becker³

et al. 2012

Computer Aided Chemical Engineering

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A systematic procedure, including process design and integration techniques for sizing and operation optimization of a poly-generation plant and design of a district heating network is presented in this paper. In the developed model a simultaneous multi objectives and multi-period optimization are principally investigated. The goal is to simultaneously minimize costs and CO 2 emission using multi-objective evolutionary algorithms (EMOO) and Mixed Integer Linear Programming (MILP). Typical days definition and the extension of the post processing phase are the novelty of this work. The proposed method helps the decision maker to know; which type and configuration of poly-generation technologies (centralized and decentralized) are best suited for the district? Is it viable to combine these technologies with other technologies (like heat pumps, solar PV)? Where in the district shall these technologies be implemented (geographically)? what are the optimal flow, supply and return temperatures of the distribution networks (heating and cooling) considering the requirements of the district and the technical limitations of the technologies?

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A review of renewable energy based cogeneration technologies

Cited by 161 publications

References 103 publications

Simulation and optimization of a CHP biomass plant and district heating network

Simulation and optimization of a CHP biomass plant and district heating network

Involving Environmental Assessment in the Optimal Design of Domestic Cogeneration Systems

Multi-Objectives, Multi-Period Optimization of district heating networks Using Evolutionary Algorithms and Mixed Integer Linear Programming (MILP)

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