Efficiency and cost optimization of a regenerative Organic Rankine Cycle power plant through the multi-objective approach

Gimelli, Alfredo; Luongo, A.; Muccillo, Massimiliano

doi:10.1016/j.applthermaleng.2016.12.009

Cited by 46 publications

(19 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Wang et al [242,269] Thermal power plant Thermal efficiency and cost of electricity MOEA Chen et al [270] Nuclear power plant Primary flow rate, weight Hybrid NSGA-II Gimelli et al [271] Organic Rankine cycle power plant Electric efficiency, overall heat exchangers area MOGA-II Boyaghchi and Molaie [272] Combined cycle power plant Total avoidable exergy destruction rate, CO 2 emission NSGA-II…”

Section: 2016mentioning

confidence: 99%

A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants

et al. 2018

View full text Add to dashboard Cite

To reach optimal/better conceptual designs of energy systems, key design variables should be optimized/adapted with system layouts, which may contribute significantly to system improvement. Layout improvement can be proposed by combining system analysis with engineers’ judgments; however, optimal flowsheet synthesis is not trivial and can be best addressed by mathematical programming. In addition, multiple objectives are always involved for decision makers. Therefore, this paper reviews progressively the methodologies of system evaluation, optimization, and synthesis for the conceptual design of energy systems, and highlights the applications to thermal power plants, which are still supposed to play a significant role in the near future. For system evaluation, both conventional and advanced exergy-based analysis methods, including (advanced) exergoeconomics are deeply discussed and compared methodologically with recent developments. The advanced analysis is highlighted for further revealing the source, avoidability, and interactions among exergy destruction or cost of different components. For optimization and layout synthesis, after a general description of typical optimization problems and the solving methods, the superstructure-based and -free concepts are introduced and intensively compared by emphasizing the automatic generation and identification of structural alternatives. The theoretical basis of the most commonly-used multi-objective techniques and recent developments are given to offer high-quality Pareto front for decision makers, with an emphasis on evolutionary algorithms. Finally, the selected analysis and synthesis methods for layout improvement are compared and future perspectives are concluded with the emphasis on considering additional constraints for real-world designs and retrofits, possible methodology development for evaluation and synthesis, and the importance of good modeling practice.

show abstract

Section: 2016mentioning

confidence: 99%

A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The optimization approach described in this paragraph involves the coupling of the thermodynamic model of the ORC system with the evolutionary algorithm MOGA II. Starting from the assigned values of the input parameters and the ORC system model deeply discussed in [35], the optimization process enabled the identification of a set of Pareto dominant solutions for the specific system configuration and application. With reference to the general scheme of the optimization process represented above in Figure 4, analyses were conducted by selecting the following two objective functions: global electric efficiency (to be maximized) :…”

Section: The Multi-objective Approach For Orc System Optimizationmentioning

confidence: 99%

“…The range of definition for the pressure in the decision variable space (Table 2) was limited according to the thermodynamic restrictions imposed by the hot and cool sources. More details are reported in [35]. The overall heat exchangers area and the global electric efficiency were evaluated via a 0D model of the ORC system, which became the calculation algorithm coupled with the optimization algorithm MOGA II according to the scheme shown in Figure 4.…”

Section: The Multi-objective Approach For Orc System Optimizationmentioning

confidence: 99%

“…In this context, unlike centralized power plants [31,32], ORC technology encourages distributed power generation [33,34]. However, the efficiency and cost optimization of ORC plants is a key issue, due to their high specific investment cost and low thermal efficiency [35]. Therefore, the goal of this research work is to highlight the key role that advanced mathematical methods could have for the optimal configuration of polygeneration plants, also focusing on the optimization of ORC plants given their increasing use within complex polygeneration systems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Key Role of the Vector Optimization Algorithm and Robust Design Approach for the Design of Polygeneration Systems

Gimelli

Muccillo

2018

Energies

View full text Add to dashboard Cite

In recent decades, growing concerns about global warming and climate change effects have led to specific directives, especially in Europe, promoting the use of primary energy-saving techniques and renewable energy systems. The increasingly stringent requirements for carbon dioxide reduction have led to a more widespread adoption of distributed energy systems. In particular, besides renewable energy systems for power generation, one of the most effective techniques used to face the energy-saving challenges has been the adoption of polygeneration plants for combined heating, cooling, and electricity generation. This technique offers the possibility to achieve a considerable enhancement in energy and cost savings as well as a simultaneous reduction of greenhouse gas emissions. However, the use of small-scale polygeneration systems does not ensure the achievement of mandatory, but sometimes conflicting, aims without the proper sizing and operation of the plant. This paper is focused on a methodology based on vector optimization algorithms and developed by the authors for the identification of optimal polygeneration plant solutions. To this aim, a specific calculation algorithm for the study of cogeneration systems has also been developed. This paper provides, after a detailed description of the proposed methodology, some specific applications to the study of combined heat and power (CHP) and organic Rankine cycle (ORC) plants, thus highlighting the potential of the proposed techniques and the main results achieved.

show abstract

“…Behzadi et al [14] conducted energy, exergy, and exergoeconomic analyses of an ORC unit that was coupled with a waste-to-heat plant, and found that R123 achieved the best performance for the integrated system. Gimelli et al [15] established a multi-objective optimization model of an ORC system with electric efficiency and the overall area of the heat exchangers as objective functions; in the Pareto optimal front, electric efficiency is in the range of 14.1-18.9% and the overall area of the heat exchangers rangers from 446 m 2 to 1079 m 2 .…”

Section: Introductionmentioning

confidence: 99%

An Improved Analysis Method for Organic Rankine Cycles Based on Radial-Inflow Turbine Efficiency Prediction

Han

Jia

et al. 2018

Applied Sciences

View full text Add to dashboard Cite

The organic Rankine cycle (ORC) has been demonstrated to be an effective method for converting low-grade heat energy into electricity. This paper proposes an improved analysis method for the ORC system. A coupling model of the ORC system with a radial-inflow turbine efficiency prediction model is presented. Multi-objective optimization was conducted for a constant turbine efficiency ORC system (ORCCTE) and a predicted turbine efficiency ORC system (ORCDTE), and the optimization results were compared. Additionally, a sensitivity analysis was conducted with respect to the heat source temperature and the ambient temperature. It can be found that the predicted turbine efficiency decreases with the increasing evaporation temperature, and increases with the increasing condensation temperature. The turbine efficiency is not constant and it varies with operating conditions. The distribution of the Pareto frontier for ORCCTE system and ORCCTE system is different. Compared with the ORCCTE system, the ORCDTE system has a lower optimal evaporation temperature, but a higher optimal condensation temperature. The deviation between the predicted turbine efficiency and the constant turbine efficiency increases with the increasing heat source temperature but decreases with the increasing ambient temperature. Thus, the difference in the theoretical analysis results between ORCCTE system and ORCDTE system increases with the increasing heat source temperature but decreases with the increasing ambient temperature.

show abstract

Efficiency and cost optimization of a regenerative Organic Rankine Cycle power plant through the multi-objective approach

Cited by 46 publications

References 36 publications

A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants

A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants

The Key Role of the Vector Optimization Algorithm and Robust Design Approach for the Design of Polygeneration Systems

An Improved Analysis Method for Organic Rankine Cycles Based on Radial-Inflow Turbine Efficiency Prediction

Contact Info

Product

Resources

About