Designing an optimized configuration for a hybrid PV/Diesel/Battery Energy System based on metaheuristics: A case study on Gobi Desert

doi:10.1016/j.jclepro.2020.122467

Journal of Cleaner Production

Volume 270, 10 October 2020, 122467

https://doi.org/10.1016/j.jclepro.2020.122467 Get rights and content

Highlights

•
An optimal configuration is proposed for a Hybrid PV/Diesel/Battery energy System.
•
The configuration is applied to a practical case study in Gobi Desert, China.
•
$ε$ -constrained method is used for the multi-objective optimization problem.
•
A new metaheuristic is used for the optimization of the problem.
•
A comparison is performed by the HOMER software and PSO-based algorithm.

Abstract

Among different renewable energies, the sun as an endless source of energy has been the focus of many researchers worldwide. The use of solar radiation energy in conventional power generation systems can play an important role in reducing fuel consumption and environmental pollution. The importance of this energy has been increased when we need to supply the load demand, especially in desert-like places. The main objective of this research is to propose a new optimal hybrid solar/diesel/battery system to cover the demand load of a rural part in the Gobi Desert in China. The main objectives for optimization are the loss of load probability, CO₂ emissions value, and the annualized cost of the system. Here, the ε-constraint method is adopted to simplify the multi-objective problem into a single objective problem. The optimization of the problem is performed by a developed version of the elephant herd optimization algorithm and the system sensitivity analysis has been analyzed on the parameters. Simulation results show that the proposed method can provide a reliable supplement for the load demand such that the PV penetration has a prominent impact by 97.9% of the costs. The results also present that the emitted CO₂ gas by the proposed cEHO algorithm by 1735 kg/year is the minimum value compared with the PSO-based optimal system and HOMER software results. The initial capital cost of the system is also achieved 48,680 $ that specifies less value than the net present cost.

Graphical abstract

Introduction

The off-grid electricity generation is a viable way of powering residential, commercial, industrial, and rural areas, which have an impossible chance to connect to the grid due to their geographical distress and high cost of transmission. In such cases, the use of renewable energies can facilitate the development process of these areas. Taking advantage of low-cost options to develop new energy services in these areas is a viable and sustainable solution. However, the conventional off-grid power generation is the use of diesel generators, the advent of new technologies has created capabilities based on the hybrid system architecture with the participation of renewable energy technologies alongside diesel generators to supply the needed electricity at the least cost. In the new approach, diesel generators are combined with renewable energy technologies such as PV panels, wind, biomass, fuel cells and small or micro hydropower. Hybrid technology combines multiple energy sources such as renewables and diesel generators, which may also utilize a battery storage system. The simultaneous application of renewable energy generators with a hybrid configuration is called Hybrid Renewable Energy System (HRES). The HRES can greatly reduce the environmental power output fluctuations, in addition to reducing the environmental pollution.

A hybrid system can be very versatile and have a variety of uses. Each combination can be used depending on geographical location and access to a variety of renewable energies and technical and economic constraints. In an off-grid power generation situation, the hybrid system provides a clean and cost-effective power generation, which is more cost-effective than diesel generator power generation. As a result, renewable energy options are a preferred solution for off-grid electricity generation. Hybrid systems are an evolving technology approach that has attracted worldwide attention. One of the important issues related to hybrid power systems is their control and management. The performance of hybrid systems is strongly dependent on how they control their production energy so that failure to properly manage them can lead the system out of its safe operating range. Several works are performed in this area, for instance, Djellouli et al. (2019) worked on controlling and management of an HRES by combination and managing the power flow of the resources. The study worked on the connecting of renewable energies into the network. The research then proposed a control configuration for the system.

Hossain et al. (Hossainet al., 2019) proposed a bioethanol generation system based on banana stem waste and hydrolysis and fermentation methods. The simulation was applied based on HOMER software to validate the techno-economic and environmental effects. The total bioethanol generation system offered an economical favorable result.

Chowdhury et al. (Chowdhuryet al., 2020) proposed a hybrid system for electricity production of Rohingya refugees in Cox’s Bazar in Bangladesh. The study adopted six different scenarios to analyze the proposed optimal arrangement. The proposed configuration contained a hybrid Generator/PV Panel/Wind/Converter/Battery and the results showed a good efficiency at a lower cost.

Krishan et al. (Krishan and Suhag, 2019) proposed a technique for optimal sizing and analysis of an HRES for the electric loads of an energy-poor rural community. The study analyzed different optimal configurations from wind, battery, and PV in terms of Cost of Energy (COE) and Net Present Cost (NPC). The HOMER software was adopted for optimized sizing and cost-effective analysis. The paper was then technically analyzed using MATLAB/Simulink. Murugaperumal et al. (Murugaperumal and Raj, 2019) introduced an optimal design and economic analysis of an HRES for a rural area in Korkadu. The hybrid system included a wind turbine, bio-diesel, and solar PV generators. The study utilized a HOMER platform for the analysis. The simulation results indicated the proposed HRES for a distant position can be a cost-effective solution to the reliable design of rural areas. Murugaperumal et al. (2020) designed an optimal techno-economic synthesis for an HRES in a distant rural area in India. The worked on a PV-wind-bio generator system due to the design’s high potential in the studied area. The paper analyzes the load forecasting of the system. The analysis has been performed based on HOMER software. Finally, the operational behavior of the HRES was compared with three different strategies. Simulation results indicated that using the presented strategy gives a good cost-effective and reliable electricity alternative to the network.

In recent years, due to nonlinearity and complexity of the hybrid renewable energy systems, metaheuristics as efficient tools of nonlinear problem solvers have been increasingly utilized. For instance, Sandeep et al. (Sandeep and Nandihalli, 2020) demonstrated an optimal sizing for HRES using a new meta-heuristic, called Social Spider Optimization. The optimization scenario was applied to power demand compensation. The paper analyzed four other meta-heuristics to compare the efficiency of the presented algorithm with them. Final results indicated that the proposed Social Spider Optimization gave the best results in contrast the other compared meta-heuristics. Das et al. (2019) proposed an off-grid optimal HRES for a radio transmitter station in India. They utilized three popular meta-heuristics including Moth-Flame Optimization, Genetic Algorithm, and Water Cycle Algorithm to optimize the hybrid system. Statistical analysis among the three meta-heuristics showed that the Water Cycle Algorithm gave the best efficiency for the hybrid system. Khare et al. (2019) simulated and optimized an HRES of a Police Control Room in India. The meteorological data were extracted from the Sagar Central India and the system suitability for the optimization was simulated based on the HOMER platform. The study recorded the load profile and the Weather data analyzed the system based on the fault tree analysis for the robustness assessment of the HRES.

Fodhil et al. (Makhdoomi and Askarzadeh, 2020) proposed a method for optimal sensitivity analysis of an autonomous HRES based on Particle Swarm Optimization (PSO) and ε-constraint method. The main purpose was to simultaneously minimize the unmet load, CO2 emissions, and the total system cost. A village area with 20 households in Algeria was selected to verify the method. The results were finally verified by the HOMER environment to show the PSO-based methodology.

Makhdoomi et al. (Makhdoomi and Askarzadeh, 2020) worked on optimal operation of a HRES based on a modified crow search algorithm (CSA). The idea was to minimize the fuel consumption during a definite period. The minimization process was performed based on the proposed CSA. Final results indicated that the suggested method addresses better results compared with others.

As can be seen, the use of metaheuristics in solving HRES is increasing. Also, each algorithm has its advantages and disadvantages. Therefore, in this paper, a developed version of the elephant herd optimization algorithm is suggested for addressing a more reliable and more accurate results. The main purpose of this paper is to find an optimized configuration for a hybrid Diesel/Solar/Battery Energy System to present a reliable guaranteed power supply for a rural area in the Gobi Desert in China. The ε-constraint method and a meta-heuristic approach is adopted for the optimization by the purpose of minimizing the unmet load, the $C O_{2}$ emissions and system capital cost simultaneously. The method typically requires less computational time that makes it comfortable from additional operations required by Pareto-based techniques. For the optimal selection of the hybrid system as a reliable power supply unit, the best optimal solution is chosen among the achieved solutions. The study also does the sensitivity analysis to synthesis the effect of each three components on the hybrid system. Finally, the results of the presented method are compared with the literature Particle Swarm Optimization (PSO)-based method and the HOMER software. The contribution of the present study is briefly given below:

-
A new and optimal configuration is proposed for a Hybrid PV/Diesel/Battery energy System
-
The configuration is applied to a practical case study in Gobi Desert, China
-
-constrained method is used for simplifying the multi-objective optimization problem.
-
A Converged Elephant Herd Optimization Algorithm is used for the optimization of the problem.
-
A comparison is performed by the HOMER software and PSO-based algorithm.

Section snippets

Method of the solution

The purpose of this study is to propose a hybrid Diesel/Solar/Battery Energy System for a rural area in Gobi Desert in China based on a new model of a new meta-heuristic, called Elephant Herding Optimization (EHO) algorithm. The results of the introduced EHO are also compared with the results of the HOMER software and literature based on the PSO algorithm. This study can be also to apply all the other remote locations with similar weather. The meteorological data for the Gobi Desert is

The Gobi Desert

One of the world’s most famous deserts, the Gobi Desert is a large desert area in northern China and southern Mongolia. The word “Gobi” in Mongolian means “desert”. The Gobi Desert with 1,300,000 $k m^{2}$ with hot summers and cold winters. It is the fifth-largest desert in the world. The Gobi suffers from the blocking of most of the precipitation by the Himalayas; however, this does not mean that the area is devoid of rainfall. Temperatures in winter and fall can reach as low as −40 °F. In summer,

The mathematical model of hybrid diesel/solar/Battery Energy System

Fig. (2) shows the general energy flow configuration of the proposed HRES. As can be observed, the proposed Hybrid system includes a diesel generator, photovoltaic modules, and battery storage system. The photovoltaic modules attempt to provide the required load demand by absorbing solar radiation and solar energy and converting it to electricity. During the energy generating, if the generated electricity is more than the load demand, the surplus energy will be stored in the battery storage. In

Balanced Elephant Herding Optimization algorithm

Today, the use of meta-heuristic methods for achieving satisfactory responses in combinatorial optimization has grown dramatically. Due to the approach of problems to real-world situations and the increasing complexity of the problems and the inability of current mathematical methods to deliver optimal points with reasonable resources, this has intensified. The development of meta-heuristic methods is usually simulated and inspired by nature. Different kinds of these algorithms have been

The ε-constraint method

The ε-constraint is a simple multi-objective problem which is adopted where an objective has been selected for optimizing and the residual objectives have been assumed as the limited constraints by given target levels ( $ε_{i}$ ). The non-inferior solutions for the considered problem are achieved by changing the levels. Consider the following multi-objective problem: $M i n (F_{1} (x), F_{2} (x), \dots, F_{n} (x))$ where, $F_{i} (i = 1,2, \dots, n)$ represents the objective functions, $n$ determines the number of objective functions, and $x$

The main objective function

In this research, the annual $L L P$ and the $C O_{2}$ emission is adopted as the constraint bounds and the annual cost of the system ( $A C S$ ) is selected as the objective function that is formulated as follows: $A C S = C o s t_{c}^{a} + C o s t_{R}^{a} + C o s t_{o & m}^{a} + C o s t_{F}^{a}$ where, $C o s t_{c}^{a}$ describes the capital cost for a year, $C o s t_{R}^{a}$ represents the replacement cost for a year, $C o s t_{o & m}^{a}$ defines the operation and maintenance cost for one year, and $C o s t_{F}^{a}$ describes the fuel cost for a year.

The yearly capital cost for the units that do not

Optimization process

The sizing optimization process on the proposed hybrid PV/diesel/battery system based on the proposed Elephant Herding Optimization (EHO) algorithm and the ε-constraint has been implemented by considering three objective functions including the total $C O_{2}$ emissions generated by the diesel generator, the loss of load probability (LPP), and the total cost of the system. The adopted variables for the optimization process include the rated capacity of diesel generator, battery storage size, and the

Simulation results

This section discusses the results of the hourly simulation for the hybrid system that has been analyzed by using both cEHO algorithm and HOMER under a definite load. Based on the simulation, the generator just can provide enough power to satisfy the primary load and the DG has been used to supply when the PV system and the battery storage unit as the backup system can’t supply enough energy for the load and the power demand exceeds than the generated power.

Conclusions

This paper proposed an optimization model based on a new improved version of the Elephant Herd Optimization Algorithm to optimal designing of a hybrid PV/diesel/battery system as a solution for supplying distant places. The research used three objectives functions including the loss of load probability, CO₂ emissions value, and the annualized cost of the system. For simplifying the optimization system, an ε-constraint method has been adopted. The results of the presented method were compared

CRediT authorship contribution statement

Muhammad Aqeel Ashraf: Conceptualization, Data curation, Writing - original draft, Writing - review & editing. Zhenling Liu: Conceptualization, Data curation, Writing - original draft, Writing - review & editing. As’ad Alizadeh: Conceptualization, Data curation, Writing - original draft, Writing - review & editing. Sayyad Nojavan: Conceptualization, Data curation, Writing - original draft, Writing - review & editing. Kittisak Jermsittiparsert: Conceptualization, Data curation, Writing -

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Designing an optimized configuration for a hybrid PV/Diesel/Battery Energy System based on metaheuristics: A case study on Gobi Desert

Highlights

Abstract

Graphical abstract

Introduction

Section snippets

Method of the solution

The Gobi Desert

The mathematical model of hybrid diesel/solar/Battery Energy System

Balanced Elephant Herding Optimization algorithm

The ε-constraint method

The main objective function

Optimization process

Simulation results

Conclusions

CRediT authorship contribution statement

Declaration of competing interest

Energy Rep.

Int. J. Electr. Power Energy Syst.

Energy Rep.

Energy

Energy Convers. Manag.

Renew. Energy

Renew. Energy

Renew. Sustain. Energy Rev.

Energy

Eng. Appl. Artif. Intell.

Reliab. Eng. Syst. Saf.

J. Energy Storage

Adv. Eng. Inf.

Energy

J. Energy Storage

Sol. Energy