An optimization model for a mechanical vapor compression desalination plant driven by a wind/PV hybrid system

Wind/solar hybrid system optimization is a key point for cost control. Here a multi-object optimization model is raised. Then a multi-object optimization method based on GA is used to find the Pareto solutions of wind/solar hybrid system. The test data shows that this method can get a good result.

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Superstructure-Based Optimization of Vapor Compression-Absorption Cascade Refrigeration Systems

Entropy ◽

10.3390/e22040428 ◽

2020 ◽

Vol 22 (4) ◽

pp. 428

Author(s):

Sergio F. Mussati ◽

Tatiana Morosuk ◽

Miguel C. Mussati

Keyword(s):

Heat Transfer ◽

Optimization Model ◽

Double Effect ◽

Total Heat ◽

Optimal Configuration ◽

Vapor Compression ◽

Heat Transfer Area ◽

Refrigeration System ◽

Cascade System ◽

Total Heat Transfer

A system that combines a vapor compression refrigeration system (VCRS) with a vapor absorption refrigeration system (VARS) merges the advantages of both processes, resulting in a more cost-effective system. In such a cascade system, the electrical power for VCRS and the heat energy for VARS can be significantly reduced, resulting in a coefficient of performance (COP) value higher than the value of each system operating in standalone mode. A previously developed optimization model of a series flow double-effect H2O-LiBr VARS is extended to a superstructure-based optimization model to embed several possible configurations. This model is coupled to an R134a VCRS model. The problem consists in finding the optimal configuration of the cascade system and the sizes and operating conditions of all system components that minimize the total heat transfer area of the system, while satisfying given design specifications (evaporator temperature and refrigeration capacity of −17.0 °C and 50.0 kW, respectively), and using steam at 130 °C, by applying mathematical programming methods. The obtained configuration is different from those reported for combinations of double-effect H2O-LiBr VAR and VCR systems. The obtained optimal configuration is compared to the available data. The obtained total heat transfer area is around 7.3% smaller than that of the reference case.

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Development of a General Hybridized Optimization Model for Biogas and Solar PV Renewable Energy System Designs

European Journal of Engineering Research and Science ◽

10.24018/ejers.2018.3.5.747 ◽

2018 ◽

Vol 3 (5) ◽

pp. 82

Author(s):

Ganiyu Adedayo Ajenikoko ◽

T. O. Araoye ◽

O. O. Aguda ◽

S. F. Owolabi ◽

A. O. Olushola

Keyword(s):

Renewable Energy ◽

Solar Energy ◽

Hybrid System ◽

Optimization Model ◽

Energy System ◽

Total Power ◽

Solar Pv ◽

Renewable Energy System ◽

Biogas Energy ◽

Electrical Generation

Hybrid biogas/solar renewable energy system is an electricity production system made up of combination of biogas and solar energy. This hybrid is considered to be best module because it is abundant and environmentally friendly due to the limited reserves of fossil fuels and global environmental concerns for the production of electrical power generation and utilization. This paper develops a general hybridized optimization model for biogas/solar system for electrical generation of Ade-Oyo in Ibadan, Oyo State. In this paper, a pig dug was used to prepare the digester materials for biogas energy while a Shockley diode principle was used for PV power model. Simulation was carried out using MATLAB software and the total power for the hybrid system is formulated. The result revealed that the total power generated by biogas/solar hybrid system is the addition of the power generated by the biogas energy and solar PV panel and is given as: . The result shows that that there is a positive relationship between the electrical energy/power generated with biogas/solar energy. This paper will be helpful in demonstrating the viability of biogas/solar energy for rural communities and remote areas

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Real-time fault tolerant control of a Reverse Osmosis desalination plant based on a hybrid system approach

2009 American Control Conference ◽

10.1109/acc.2009.5160684 ◽

2009 ◽

Cited By ~ 5

Author(s):

Adrian Gambier ◽

Nikolaus Blumlein ◽

Essameddin Badreddin

Keyword(s):

Real Time ◽

Reverse Osmosis ◽

Hybrid System ◽

System Approach ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Desalination Plant ◽

Reverse Osmosis Desalination

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A new standalone single effect thermal vapor compression desalination plant with nano-filtration pretreatment

Energy Conversion and Management ◽

10.1016/j.enconman.2021.115095 ◽

2022 ◽

Vol 252 ◽

pp. 115095

Author(s):

Mohamed A. Farahat ◽

Hassan E.S. Fath ◽

Mahmoud Ahmed

Keyword(s):

Vapor Compression ◽

Desalination Plant ◽

Single Effect ◽

Nano Filtration

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IGDT-Based Wind–Storage–EVs Hybrid System Robust Optimization Scheduling Model

Energies ◽

10.3390/en12203848 ◽

2019 ◽

Vol 12 (20) ◽

pp. 3848

Author(s):

Bo Sun ◽

Simin Li ◽

Jingdong Xie ◽

Xin Sun

Keyword(s):

Robust Optimization ◽

Wind Power ◽

Hybrid System ◽

Electricity Market ◽

Optimization Model ◽

Probabilistic Approach ◽

System Optimization ◽

Stable Operation ◽

Scheduling Model ◽

Optimization Scheduling

Wind power has features of uncertainty. When wind power producers (WPPs) bid in the day-ahead electricity market, how to deal with the deviation between forecasting output and actual output is one of the important topics in the design of electricity market with WPPs. This paper makes use of a non-probabilistic approach—Information gap decision theory (IGDT)—to model the uncertainty of wind power, and builds a robust optimization scheduling model for wind–storage–electric vehicles(EVs) hybrid system with EV participations, which can make the scheduling plan meet the requirements within the range of wind power fluctuations. The proposed IGDT robust optimization model first transforms the deterministic hybrid system optimization scheduling model into a robust optimization model that can achieve the minimum recovery requirement within the range of wind power output fluctuation, and comprehensively considers each constraint. The results show that the wind–storage–EVs hybrid system has greater operational profits and less impact on the safe and stable operation of power grids when considering the uncertainty of wind power. In addition, the proposed method can provide corresponding robust wind power fluctuation under different expected profits of the decision-maker to the wind–storage–EVs hybrid system.

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