Analysis of an evaporator-condenser-separated mechanical vapor compression system

An evaporator-condenser-separated mechanical vapor compression (MVC) system was presented. The better effect of descaling and antiscaling was obtained by the new system. This study focused on the method of thermodynamic analysis, and the energy and exergy flow diagrams were established by using the first and second law of thermodynamics analysis. The results show that the energy utilization rate is very high and the specific power consumption is low. Exergy analysis indicates that the exergy efficiency is low, and the largest exergy loss occurs within the evaporator -condenser and the compressor.     

Large-scale time evaluation for energy estimation of stand-alone hybrid photovoltaic–wind system feeding a reverse osmosis desalination unit

In this study, energy and water production estimation on a large-scale time from Photovoltaic–Wind hybrid system coupled to a reverse osmosis desalination unit in southern Tunisia has been elaborated. The use of a hybrid system for desalination appears nowadays as a very promising solution for remote and arid areas. The produced energy is used for potable water production. For energy production, metrological data (wind speed, solar irradiance…) and steady-state models have been used. The obtained results show that the hybrid solution (solar and wind) gives an energy availability during the year, despite changing energy according to daytime, season and year. The reverse osmosis desalination unit powered by Photovoltaic–Wind hybrid system for producing potable water from brackish water is an appropriate solution to southern Tunisia (salinity about 6 g/l). For this, compositions of brackish feed water in Djerba region were selected. Double stage configuration in the desalination process using spiral modules is adopted extensively and validation of the steady-state models is presented.     

Optimal sizing study of hybrid wind/PV/diesel power generation unit

In this paper, a methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system is presented. This approach makes use of a deterministic algorithm to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the total cost of the system is minimized while guaranteeing the availability of the energy. The collection of 6 months of data of wind speed, solar radiation and ambient temperature recorded for every hour of the day were used. The mathematical modeling of the main elements of the hybrid wind/PV/diesel system is exposed showing the more relevant sizing variables. A deterministic algorithm is used to minimize the total cost of the system while guaranteeing the satisfaction of the load demand. A comparison between the total cost of the hybrid wind/PV/diesel energy system with batteries and the hybrid wind/PV/diesel energy system without batteries is presented.The reached results demonstrate the practical utility of the used sizing methodology and show the influence of the battery storage on the total cost of the hybrid system.     

Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing

In this paper, we perform Simulated Annealing (SA) algorithm for optimizing size of a PV/wind integrated hybrid energy system with battery storage. The proposed methodology is a heuristic approach which uses a stochastic gradient search for the global optimization. In the study, the objective function is the minimization of the hybrid energy system total cost. And the decision variables are PV size, wind turbine rotor swept area and the battery capacity. The optimum result obtained by SA algorithm is compared with our former study’s result. Consequently, it is come up with that the SA algorithm gives better result than the Response Surface Methodology (RSM). The case study is realized for a campus area in Turkey.     

Design optimization of a polygeneration plant fuelled by natural gas and renewable energy sources

A new and systematic procedure to select and size a polygeneration plant fuelled by natural gas, solar energy and gasified biomass is presented in this paper. The proposed procedure is based on the superstructure definition, containing a long list of possible configurations for a polygeneration plant simultaneously producing electricity, heat, cold and fresh water. Based on that superstructure, a mathematical programming model was developed and applied to a Spanish tourist resort. Three key aspects were optimized in the mathematical programming problem: energy savings, greenhouse gases (GHG) emission reduction and economic feasibility. The results show, firstly, that the simultaneous production of electricity, heat, cold and fresh water is reliable upon the established assumptions. Secondly, that today higher economic profitability is yet achieved with only natural gas-based technologies, although higher energy savings and GHG reduction are obtained through the gradual increase of renewable energy sources.     

Size optimization of a PV/wind hybrid energy conversion system with battery storage using response surface methodology

This paper aims to show the use of the response surface methodology (RSM) in size optimization of an autonomous PV/wind integrated hybrid energy system with battery storage. RSM is a collection of statistical and mathematical methods which relies on optimization of response surface with design parameters. In this study, the response surface, output performance measure, is the hybrid system cost, and the design parameters are the PV size, wind turbine rotor swept area and the battery capacity. The case study is realized in ARENA 10.0, a commercial simulation software, for satisfaction of electricity consumption of the global system for mobile communications (GSM) base station at Izmir Institute of Technology Campus Area, Urla, Turkey. As a result, the optimum PV area, wind turbine rotor swept area, and battery capacity are obtained to be 3.95 m², 29.4 m², 31.92 kWh, respectively. These results led to $37,033.9 hybrid energy system cost, including auxiliary energy cost. The optimum result obtained by RSM is confirmed using loss of load probability (LLP) and autonomy analysis.     

A hybrid model for the optimum integration of renewable technologies in power generation systems

The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. Also, the procedure enables the estimation of the optimum feed-in-tariff to be offered to future RES-E systems. Also, the overall cost increase in the electricity sector for the promotion of RES-E technologies, for the period 2010–2020, is analyzed taking into account factors, such as, the fuel avoidance cost, the carbon dioxide emissions avoidance cost, the conventional power system increased operation cost, etc. The overall results indicate that in the case of RES-E investments with internal rate of return (IRR) of 10% the cost of integration is higher, compared to RES-E investments with no profit, (i.e., IRR at 0%) by 0.3–0.5 €c/kWh (in real prices), depending on the RES-E penetration level.     

An energy management approach for renewable energy integration with power generation and water desalination

The share of the renewable energy sources (RES) in the global electricity market is substantially increasing as a result of the commitment of many countries to increase the contribution of the RES to their energy mix. However, the integration of RES in the electricity grid increases the complexity of the grid management due to the variability and the intermittent nature of these energy sources. Energy storage solutions such as batteries offer either short-term storage that is not sufficient or longer period storage that is significantly expensive. This paper introduces an energy management approach which can be applied in the case of power and desalinated water generation. The approach is based on mathematical optimization model which accounts for random variations in demands and energy supply. The approach allows using desalination plants as a deferrable load to mitigate for the variability of the renewable energy supply and water and/or electricity demands. A mathematical linear programming model is developed to show the applicability of this idea and its effectiveness in reducing the impact of the uncertainty in the environment. The model is solved for the real world case of Saudi Arabia. The optimal solution accounts for random variations in the renewable energy supply and water and/or electricity demands while minimizing the total costs for generating water and power.     

A mobile renewable house using PV/wind/fuel cell hybrid power system

A photovoltaic/wind/fuel cell hybrid power system for stand-alone applications is proposed and demonstrated with a mobile house. This concept shows that different renewable sources can be used simultaneously to power off-grid applications. The presented mobile house can produce sufficient power to cover the peak load. Photovoltaic and wind energy are used as primary sources and a fuel cell as backup power for the system. The power budgeting of the system is designed based on the local data of solar radiation and wind availability. Further research will focus on the development of the data acquisition system and the implementation of automatic controls for power management.     

Techno-economic valuation and optimization of integrated photovoltaic/wind energy conversion system

Decentralized electricity generation by renewable energy sources offer greater security of supply for consumers while respecting the environment. But the random nature of these sources requires us to develop sizing rules and use these systems to exploit them. This paper proposes an integrated PV/wind hybrid system optimization model, which utilizes the iterative optimization technique following the Deficiency of Power Supply Probability (DPSP), the Relative Excess Power Generated (REPG), the Total Net Present Cost (TNPC), the Total Annualized Cost (TAC) and Break-Even Distance Analysis (BEDA) for power reliability and system costs. The flow chart of the hybrid optimal sizing model is also illustrated. With this merged model, the optimal size of PV/wind hybrid energy conversion system using battery bank can be performed technically and economically according to the system reliability requirements. Additionally, a sensitivity analysis was carried out in order to appreciate the most important parameters influencing the economic performances of the hybrid system. A case study is conducted to analyze one hybrid project, which is designed to supply small residential household situated in the area of the Center for Renewable Energy Development (CDER) localized in Bouzaréah, Algeria (36°48′N, 3°1′E, 345 m).     

Simulation based size optimization of a PV/wind hybrid energy conversion system with battery storage under various load and auxiliary energy conditions

In this paper, size of a PV/wind integrated hybrid energy system with battery storage is optimized under various loads and unit cost of auxiliary energy sources. The optimization is completed by a simulation based optimization procedure, OptQuest, which integrates various heuristic methods. In the study, the main performance measure is the hybrid energy system cost. And the design parameters are PV size, wind turbine rotor swept area and the battery capacity. The case study is realized for Izmir Institute of Technology Campus Area, Urla, Turkey. The simulation model of the system is realized in ARENA 12.0, a commercial simulation software, and is optimized using the OptQuest tool in this software. Consequently, the optimum sizes of PV, wind turbine and battery capacity are obtained under various auxiliary energy unit costs and two different loads. The optimum results are confirmed using Loss of Load Probability (LLP) and autonomy analysis. And the investment costs are investigated how they are shared among those four energy sources at the optimum points.     

Steady‐state model of a variable speed vapor compression system using R134a as working fluid

This paper presents a steady‐state physical model for a variable speed vapor compression system. Its development and validation for a wide range of operating conditions are presented. The model requires as input parameters: compressor speed, static superheating degree and volumetric flow rates and temperatures of secondary fluids at the evaporator and condenser inlet. Using these input parameters, which can be easily obtained in this kind of facility, the model predicts the operating pressures, the temperature of secondary fluids at the evaporator and condenser outlet, the evaporator and condenser thermal capacities, the electric power consumed by the compressor and the coefficient of performance, COP. The experimental validation of the model has been carried out with 177 tests using R134a as working fluid, concluding that the model can predict the energetic performance of a variable speed vapor compression chiller with an error lower than ±10%. Copyright © 2009 John Wiley & Sons, Ltd.     

A new approach of sizing battery energy storage system for smoothing the power fluctuations of a PV/wind hybrid system

In this paper, a new approach for optimally sizing the storage system employing the battery banks for the suppression of the output power fluctuations generated in the hybrid photovoltaic/wind hybrid energy system. At first, a novel multiple averaging technique has been used to find the smoothing power that has to be supplied by the batteries for the different levels of smoothing of output power. Then the battery energy storage system is optimally sized using particle swarm optimization according to the level of smoothing power requirement, with the constraints of maintaining the battery state of charge and keeping the energy loss within the acceptable limits. Two different case studies have been presented for different locations and different sizes of the hybrid systems in this work. The results of the simulation studies and detailed discussions are presented at the end to portrait the effectiveness of the proposed method for sizing of the battery energy storage system. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi-objective technoeconomic optimization of an off-grid solar-ground-source driven cycle with hydrogen storage for power and fresh water production

Utilizing renewable sources integrated with thermodynamic cycles has been gaining attention in recent years due to being economical and environment-friendly, among which, renewable-energy driven water and power generation systems have shown promising outcomes. In the field of renewable-energy based multi-generation systems (MGS), many recent works have focused on energy analysis or simple optimization. Therefore, in this study, an off-grid solar-geothermal cogeneration system which is able to produce power by Kalina cycle, hydrogen by proton exchange membrane electrolyzer (PEMEC), and freshwater by a multi-effect desalination (MED) unit, was investigated and optimized in terms of economic and energy viewpoints. Unlike previous studies, in this work, a comprehensive multi-objective optimization (MOO) was employed on the system in order to find the optimal working condition. The decision variables of the optimization include flat plate collector area, water mass flow, and ammonia concentration of the Kalina cycle, and the objective functions were levelized cost of electricity (LCOE), payback period (PBP), the overall energy efficiency of the system, and freshwater production of MED unit. Final results show that the system, in its optimum condition, is able to produce 182.09 m³.day⁻¹ fresh water, with energy efficiency, PBP, and LCOE equal to 6.23%, 5.19 years and 0.238 $.kWh⁻¹, respectively.     

Simulation and optimization of a stand-alone power plant based on renewable energy sources

By using the optimization software tool HOMER, this project aims at the energetic and economical optimization of a RES-based stand-alone system, already installed at Leicestershire, UK. Based on local meteorological data, an optimization strategy has been developed to identify the most economical and efficient scenarios for the generation of electricity to cover the desirable load in annual basis. Furthermore, the environmental-friendly character of the system was highly concerned in terms of emissions reduction, therefore the capability of an off-grid system was also investigated. The simulations show that an off-grid project with zero emissions is feasible, presenting the additional advantage of minimal capital investment costs. Finally, it is found that grid connection corresponds to very high operational costs in a long term.     

Development of an electrical model for a PV/battery system for performance prediction

This paper presents electrical model of a photovoltaic-battery system. This model helps to understand the behaviour of a solar-battery system under various load and irradiance conditions. And also it assists with investigation of the performance of the system. Hybrid energy systems use different energy sources such as solar and wind with a backup unit such as a battery or a diesel generator. They are an economical option in areas remote from national grid. In this context the performance of the system to supply electric power in an efficient way of operation is important. The problem comes from uncertain renewable energy supply and load and also non-linear characteristics of components in the system. The purpose of study we are involved in this relation is to see the behaviour of a solar-battery system under various load and irradiance conditions and to investigate the performance of the system. As a result an optimum system configuration and a correct and cost effective size of Balance of System (BOS) can be achieved. In this paper the complete electrical circuit of the entire hybrid system, the mathematical model and computational technique are presented.     

An artificial intelligence approach to optimization of an off-grid hybrid wind/hydrogen system

Off-grid electrification of remote areas using a hybrid renewable energy scheme is a requirement to achieve the goals of sustainable development. However, the optimization and sizing for the capacity of such systems are challenging. In this regard, this study targets an improved optimization algorithm with high efficiency for optimization and long-term capacity planning of an off-grid hybrid renewable energy scheme composed of wind, fuel cell, and hydrogen storage schemes. The suggested methods are three improved versions of the global dynamic harmony search to do pitch adjustment mechanism. The objective function of this study is to reduce the total net annual cost of the system and the loss of power supply probability to a minimum. The performance of this hybrid system is examined via a simulation study, which had been performed on a remote area located in eastern Iran over a long period. The results of the three improved proposed algorithms are compared with the original global dynamic harmony search algorithm. Also, sensitivity analysis is proposed to showcase the influence of uncertainties on the system and input parameters on the algorithm. The simulation results indicate that three improved versions of the global dynamic harmony search algorithm ?nd more promising results than the original algorithm, and confirm the superior accuracy, convergence speed, and robustness of the global dynamic harmony search-II. Also, reliability level and iteration values have a considerable impact on the total net annual cost of the optimal hybrid energy system based on wind and hydrogen energy.     

Sustainable energy planning based on a stand-alone hybrid renewableenergy/hydrogen power system: Application in Karpathos island, Greece

This study presents the sustainable planning of a renewables-based energy system, which aims to fulfil the electric needs of the island by replacing the existing diesel generators with new wind farms, photovoltaic installations and hydrogen production systems. Electric system design and least cost planning analysis were concluded using historic data from both demand and supply sides. An optimal “sustainable island” scheme should ensure 100% use of renewable energy resources for power generation, while hydrogen production is ideal for covering storage and transportation needs. Due to its morphology and scale, Karpathos applies perfectly for wind and solar energy systems, due to increased solar resource (about 1790 kWh/m².year of global irradiation) and high wind potential (average of 9 m/s in specific locations). Therefore, this case study examines an increase in RES penetration up to 20% in the electric energy mixture, a hydrogen production plan just for the needs of transport and a more aggressive, 100% renewables scheme that ensures a self-fulfilling energy system based on indigenous renewable resources.     

An investigation of optimum PV and wind energy system capacities for alternate short and long‐term energy storage sizing methodologies

The goal of this study is to find the optimal sizes of renewable energy systems (RES) based on photovoltaic (PV) and/or wind systems for three energy storage system (ESS) scenarios in a micro‐grid; (1) with pumped hydro storage (PHS) as a long‐term ESS, (2) with batteries as a short‐term ESS, and (3) without ESS. The PV and wind sizes are optimally determined to accomplish the maximum annual RES fraction (F_RES ) with electricity cost lower than or equal to the utility tariff. Furthermore, the effect of the use of battery and PHS on the electricity cost and F_RES are studied. A university campus on a Mediterranean island is selected as a case study. The results show that PV‐wind hybrid system of 8 MW wind and 4.2 MW PV with 89.5 MWh PHS has the highest F_RES of 88.0%, and the highest demand supply fraction as 42.6%. Moreover, the results indicate that the economic and technical parameters of RESs are affected significantly by the use of ESSs depending on the type and the capacity of both the RES and the ESS.     

Energy management hypothesis for hybrid power system of H2/WT/PV/GMT via AI techniques

This paper aims to attain an efficient and optimized energy management operation of Hybrid Power System (HPS) by using Artificial Intelligent (AI) controllers. The HPS comprises Wind Turbines (WTs) and Photovoltaic (PV) panels such as primary Renewable Energy Sources (RESs) in addition to both Fuel Cells (FCs) and Gas Micro–Turbines (GMTs) which are used as Backup Sources (BKUSs).To avoid the undesired negative impacts on the HPS functionality because of the RESs intermittency, the Hydrogen Storage System (HSS) is integrated into the system. Two different energy management strategies based on Neural Networks (NN) and Fuzzy Logic Control (FLC) respectively are applied to the HPS for minimizing the energy production cost and keeping the buffer role of HSS. Using MATLAB^?, the proposed two AI introduced solutions are used for reaching adequate energy management operation performance for the overall HPS during 24 h load variation. From the numerical simulations, the superiority of the FLC over the NN control approach is discussed. The proposed HSS can positively act as a buffer solution to avoid drawbacks of RESs during unexpected load peaks and/or discontinuous energy production.