Stand-alone Hybrid Renewable Energy Research Articles

Dispatch strategies based performance analysis of a hybrid renewable energy system for a remote rural area in India

A significant Indian population lives in villages and some live in remote areas disconnected from the grid connectivity. Extension of grid connection to provide power supply to these villages is not feasible, but stand-alone hybrid renewable energy system may be a feasible option. In this perspective, dispatch strategy based performance analysis has been carried out to provide power supply using the hybrid renewable energy system for a remote rural area in the state of Karnataka (India). The effect of load following, cycle charging and combined dispatch strategies on Lead Acid and Lithium-Ion batteries with Photovoltaic/Hydro/Battery and Photovoltaic/Wind/Hydro/Diesel Generator/Battery configurations has been studied using Hybrid Optimization Model for Electric Renewable (HOMER Pro®). The feasible Cost of Energy and Net Present Cost obtained for the proposed hybrid system are found in the range of 0.1 $/kWh – 0.162 $/kWh, $4,65,790 – $7,16,658 under the proposed dispatch strategies. The Cost of Energy and Net Present Cost of Lithium-Ion battery based system are found to be 30% and 35% lesser than Lead Acid battery based system. Using Lithium-Ion batteries, the Cost of Energy is reduced by 34%, 25% and 37% under Load Following, Cycle Charging and Combined Dispatch strategies. From the results obtained, it is found that under Combined Dispatch strategy, Lithium-Ion battery based hybrid renewable energy system delivers the most optimal operational costs. The study is also extended to perform sensitivity analysis on varying input parameters such as discount rate, Photovoltaic cost, battery cost, fuel cost, wind speed and design flow rate. Variation of discount rate and fuel cost affect the Cost of Energy and Net Present Cost significantly.

Resilience of standalone hybrid renewable energy systems: The role of storage capacity

Evaluating the resilience of a power supply system after a sudden disturbance is essential in standalone hybrid renewable systems. Reliability assessments have strongly focused on the static condition during supply, opposite to the dynamic response to sudden disturbances, which is less studied in reliability literature. This study proposes a novel approach to analyze dynamic-response resilience from a sudden disturbance, focusing on the role of storage capacity of the standalone hybrid renewable system. Using a computer-based simulation, the magnitude, duration and instant of battery failure in the system is quantified and two indices to quantitatively measure resilience based on the three parameters are developed. Using these indices, it is discovered that the system resilience non-linearly declined with increasing trouble rate and trouble duration. The same tendency was observed for ten battery capacities analyzed. Also, larger storage capacity provided higher resilience as a general rule. However, battery capacities of 11,500, 12,500 and 14,500 Wh seem to equal or even slightly outperform the immediate larger type at the most critical duration and magnitude of failure. The developed algorithm presents one approach to clarify dynamic performance of the system and can be implemented in any system scale.

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

Microgrids being an important entity in the distribution system, and to get their full advantages by incorporating maximum distributed generation, standalone hybrid renewable energy systems (HRESs), being environmentally-safe and economically-efficient, are considered as the promising solution to electrify remote areas where the grid power is not available. In this work, a techno-economic investigation with an optimal design of HRES is presented to fulfill the domestic electricity need for a residential area of the Sherani district in the Province of Baluchistan, Pakistan. Nine case studies based on PV/wind/diesel/battery are analyzed based on net present cost (NPC), cost of energy (COE), and emission to decide the feasible solution. HOMER tool is utilized to accomplish modeling and simulation for economic analysis and optimal sizing. Simulation results demonstrated that HRES with PV-wind-battery is the most viable option for the specified area, and the optimal sizing of components are also obtained with $ 28,620 NPC and $ 0.311/kWh COE which shows 81.65 % reduction in cost and 100 % preserving in toxic emission while fulfilling 100 % energy demand with 67.3 % of excess energy. Furthermore, MATLAB/Simulink modeling for the optimally designed system is built for technical analysis while its effectiveness is proved by keeping dc and ac buses voltage constant, safe operating range of battery state of charge (SOC) with active power balance between HRES components, as well as efficient ac voltage quality, regardless of generation disturbances and load fluctuations. The output signal has total harmonic distortion (THD) of 0.30 % as compared to 5.44 % with the conventional control scheme. The novelty lies in the sequential application of both HOMER and MATLAB simulations of the proposed HRES model and validation of the proposition for the studied area; by using and implementing model predictive control (MPC) of a reconfigurable inverter.

A new sizing and optimization framework for stand-alone hybrid renewable energy systems

A new sizing and optimization framework for stand-alone hybrid renewable energy systems

Design of Stand-alone Solar-Wind-Hydro Based Hybrid Power System: Case of Rural Village in Malawi

Malawi has current electrification rate of less than 10% for a population of 18 million connected to the grid. The electricity generation company in Malawi (EGENCO) is greatly affected by low water levels making it difficult to satisfy the existing demand of electricity. This makes it difficult for Malawi to extend its National electricity grid. Thus, the aim of the study is to design stand-alone hybrid renewable energy system which is economically and technically feasible with focus on hydropower, wind, solar and battery bank within Dwangwa area. The study area is estimated to have 420 households, commercial and public service load with primary load demand of 5,556.31 kWh/day and peak load of 302.93 kW. River discharge data were collected from ministry of irrigation and water development while solar and wind data were collected from NASA. HOMER modeling tool was used to design a stand-alone system. From simulation results, the best design flow for Dwangwa river is 159 L/s at elevation of 100 metres and the best hybrid system combination was hydropower-wind-solar-battery and converter. The whole hybrid system initial capital cost was $2,662,638 while Net present cost (NPC) and levelized cost of energy (LCOE) were $3,597,197 and $0.134/kWh respectively. However, the cost of electricity in Malawi on the grid is K88.02/kWh ($0.11/kWh) which makes the system expensive. Therefore, the study has shown that the hybrid system is not economically viable. However, Government intervention can help to make the system monetarily acceptable and viable.

Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm

This paper presents a methodology to size Standalone Hybrid Renewable Energy System (SHRES) which combines solar PV, wind turbine (WT) and battery energy storage (BES) for application in rural areas. These sources are integrated via an AC bus to support the load demand. SHRES is simulated under varying load demand, solar radiation, temperature and wind speed obtained from the Malaysian Meteorological Department. A Multi-objective Optimization using Non-dominate Sorting Genetic Algorithm (NSGA-II) was utilized to determine the best sizing of PV / wind turbine / battery, and minimize Cost of Energy (COE) and Loss of Power Supply Probability (LPSP). The results show that the NSGAII optimization of the model is able to determine the best techno-economic sizing for the suggested location. For the case study, the optimum COE was 0.1099 (USD/kWh) and LPSP was 0.0865. The proposed tool can be used to size the SHRES for rural electrification and enhance energy access within remote locations.

Life cycle assessment and energy payback time of a standalone hybrid renewable energy commercial microgrid: A case study of Town Island in Hong Kong

Microgrid solutions can incorporate clean renewable energy and operate autonomously to power remote areas unreachable by the main grid. While microgrids have thus attracted the interest of many electricity operators, some suggest that renewable energy is not as environmentally friendly as it is claimed to be. This study investigates the life cycle environmental impacts and energy payback time (EPBT) of a microgrid through a life cycle assessment (LCA) case study of the Town Island Microgrid, the first standalone hybrid renewable energy commercial microgrid in Hong Kong. The environmental performance of the Town Island Microgrid was further tested against 2 electrification options, including an on-site diesel generator system and a grid extension. Our results indicate that the Town Island Microgrid is the least impactful in 8 impact categories out of 12. For instance, the global warming potential (GWP) of the diesel generator system and the grid extension was 4.3 times and 7.8 times greater than that caused by the microgrid, respectively. The EPBT for the microgrid was 9.2 years, while the grid extension and the diesel generator EPBT values were 6.4 and 10.1 times longer than that of the microgrid, respectively. In conclusion, the case study provides substantial evidence that a microgrid solution can deliver a significantly superior life cycle environmental performance than other common electrification options.

An investigation on wind/PV/fuel cell/battery hybrid renewable energy system for nursing home in Istanbul

This paper presents a techno-economic analysis of hybrid renewable energy systems to supply the electrical load requirements of the nursing home located in Istanbul, Turkey. The standalone hybrid renewable energy systems (Photovoltaic (PV)/wind/fuel cell/electrolyzer, PV/fuel cell/electrolyzer, and wind/fuel cell/electrolyzer, etc.) considered in the analysis were comprised of different combinations of PV panels, fuel cells, and wind turbines supplemented with hydrogen storage. In this study, the Hybrid Optimization of Multiple Energy Resources (HOMER) software is used as the assessment tool to determine the optimal configuration of hybrid renewable energy systems taking total net present cost and cost of energy into consideration. As a result, it is determined that the optimal system configuration of standalone wind/PV/fuel cell/electrolyzer hybrid renewable energy systems with the lowest total net present cost consists of 30 kW PV panel, 20 kW wind turbine, 20 kW fuel cell, 20 kW power converter, 50 kW electrolyzer, 20 kW rectifier, and 100 kg hydrogen tank. Besides, the net present cost and cost of energy of the optimum configuration are calculated to be $607,298 and $1.306/kWh, respectively. The system is considered as completely renewable. When wind speed and solar radiation values increase, then the cost of energy decrease about $0.979/kWh.

Integration of sizing and energy management based on economic predictive control for standalone hybrid renewable energy systems

An Hybrid Renewable Energy Systems (HRES) can be described as a set of loads, renewable generation and storage units that can operate in standalone mode or connected to the main grid. In order to obtain a good compromise between capital investment and system reliability, an optimum sizing of all HRES components is needed. As power reliability, system cost and operation of the system depend on each other, the sizing methodology must be integrated with the energy management strategy (EMS). This paper presents an optimization methodology for sizing the components of a standalone hybrid wind/PV system (with hydrogen storage and battery storage), which integrates an EMS based on an economic model predictive control (EMPC) approach. The integrated problem to be solved is presented as a bi-level optimization framework composed of an outer loop and an inner loop. The outer loop is in charge of the HRES sizing and it is solved using Genetic Algorithms (GA). The inner loop solves the EMS for each candidate solution as a rolling horizon mixed integer linear problem (MILP). The results have shown an investment saving as well as a reduction of the operation costs with the proposed methodology.

NSGA-II and MOPSO based optimization for sizing of hybrid PV/wind/battery energy storage system

<span lang="MS">This paper presents a Stand-alone Hybrid Renewable Energy System (SHRES) as an alternative to fossil fuel based generators. The Photovoltaic (PV) panels and wind turbines (WT) are designed for the Malaysian low wind speed conditions with battery Energy Storage (BES) to provide electric power to the load. The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. The optimized hybrid system was examined in MATLAB using two case studies to find the optimum number of PV panels, wind turbines system and BES that minimizes the Loss of Power Supply Probability (LPSP) and Cost of Energy (COE). The hybrid power system was connected to the AC bus to investigate the system performance in supplying a rural settlement. Real weather data at the location of interest was utilized in this paper. The results obtained from the two scenarios were used to compare the suitability of the NSGA-II and MOPSO methods. The NSGA-II method is shown to be more accurate whereas the MOPSO method is faster in executing the optimization. Hence, both these methods can be used for techno-economic optimization of SHRES. </span>

Optimal PI controller of DVR to enhance the performance of hybrid power system feeding a remote area in Egypt

This article proposes optimal PI controllers of Dynamic Voltage Restorer (DVR) to enhance the performance of stand-alone hybrid renewable energy system that is feeding a new community located in Egypt. The hybrid system includes three renewable energy sources, namely, solar PV cells, wind turbines based permanent magnet synchronous generator and fuel cells. These three sources are connected to a common DC link by three boost converters, one for each source. The common DC link is integrated to the AC loads via DC/AC inverter. The optimal size of the three proposed renewable sources is obtained using the HOMER software package. The main contribution of this study is designing optimal PI controller for DVR for enhancing the performance of a hybrid PV-wind-fuel cell. Two PI controllers are used to regulate the IGBT pulses of the voltage source inverter (VSI) driving DVR by adjusting the D-Q axes voltage signals. The D-Q axis components of the load voltage represent the inputs to the two PI controllers respectively. While the D-Q axis voltage signals driving the IGBT pulses of the DVR-VSI IGBT are the outputs of the two PI controllers respectively. A Cuckoo Search (CS), as an optimization technique is used for determining the optimal PI control parameters used to drive the DVR at different operating conditions. To validate the effectiveness of the DVR based PI-CS control, four test scenarios are investigated includes (three phase fault, sag, swell and unbalance voltage conditions). The enhancement of the system performance is achieved through improving the voltage, the current and the power waveforms for each source, improving the dynamic performance of the wind turbine generator and keeping the continuous operation of the three sources during faulty conditions. The proposed system is modeled using MATLAB/Simulink.

Optimal Design of Standalone Hybrid Renewable Energy Systems with Biochar Production in Remote Rural Areas: A Case Study

Abstract For remote agriculture-based rural areas, utilizing the local renewable resources such as biomass, wind, and solar energy could be potentially more efficient than long-distance transmission of electricity. In this paper, a multi-objective optimization model for the design of standalone hybrid renewable energy systems (HRES) in remote rural areas is proposed. The objective is to maximize the profits and the carbon abatement capability of the system by optimal process selection and sizing of HRES components including solar, wind, and biomass generation systems. A case study for the design of an HRES on the Carabao Island in the Philippines is conducted. The result shows a 122 kW solar power plant, a 67 kW onshore wind farm and a 223 kW biomass pyrolysis system constitute the optimal configuration of the hybrid energy system, generating a daily profit of US$ 940. The greenhouse gas emission of the optimal system is -3,339 kg CO2 eq/day, indicating good carbon sequestration performance.

Fuzzy logic-based energy management system of stand-alone renewable energy system for a remote area power system

ABSTRACTRenewable energy systems (RES) are being widely accepted as an alternative to standard conventional energy sources due to depletion of natural resources and their consequential environmental impact. One of the increasing uses of stand-alone RES is in powering the remote areas where grid power is significantly expensive due to transportation. However, the energy management of such systems is quite complex. This paper deals with fuzzy logic-based controller design for power management of a stand-alone hybrid renewable energy systems (HRES). The proposed intelligent energy management aims to minimise the operation cost and the environmental impact of a microgrid while significantly improving the economic and technical performance of power supply. The proposed fuzzy logic controller (FLC) ensures the power management between renewable energy generation, energy storage, and load. The simulation results clearly show that the controller demonstrated high performance under various load and generation conditions.

Design Optimization and Model Predictive Control of a Standalone Hybrid Renewable Energy System: A Case Study on a Small Residential Load in Pakistan

Renewable energy sources (RESs) offer a promising prospect for covering the fundamental needs of electricity for remote and isolated regions. To serve the customers with high power quality and reliability, design optimization methodology and a possible power management strategy (PMS) for wind-diesel-battery-converter hybrid renewable energy system (HRES) is proposed in this paper. The analysis is applied to a real case study of a standalone residential load located in a remote rural area in Pakistan. Firstly, optimal component sizing is investigated according to actual meteorological and load profile data. Different hybrid configurations are modeled, analyzed, and compared in terms of their technical, economic and environmental metrics with the aid of HOMER® software. The main objective is to determine the most feasible and cost-effective solution with least life-cycle cost, keeping in view the impact of carbon emissions. Secondly, a suitable PMS based on the state of charge (SOC) of the battery is proposed and implemented in MATLAB/Simulink® software for the designed HRES. The PMS is targeted to maintain load balance and extract maximum wind power while keeping the battery SOC within the safe range. Model predictive control (MPC) approach is applied to improve the output voltage profile and reduce the total harmonic distortion (THD). The boost converter is used for maximum power extraction from the wind. The DC-DC buck-boost battery controller is utilized to stabilize the DC bus voltage. The design optimization results show that the hybridization of wind, battery, and converter presents optimal configuration plan with minimum values of total net present cost (14,846 $) and cost of energy (0.309 $/kWh), which means 76.7% reduction in both total system cost and energy cost and 100% saving in harmful emissions when compared to the base case using diesel generator. The proposed system is able to support hundred percent of the load demand with excess energy of 30.1%. Performance analysis of PMS under variable load and fluctuating wind power generation is tested, and promising results with efficient load voltage profile is observed. Further, THD is reduced significantly to 0.26% as compared to 2.62% when the conventional PI controller is used. The output of this work is expected to open a new horizon for researchers, system planners for efficient design and utilization of HRES to curb drastic increase in load demand for urban as well as rural areas.

Flexible design and assessment of a stand-alone hybrid renewable energy system: a case study Marrakech, Morocco

The main objective of this study is to propose an optimal ‘hybrid renewable energy system’ (HRES) destined to supply a group of typical houses in Marrakech-Morocco. The renewable hybrid system consists of a wind turbine, a photovoltaic field (PV), a diesel generator (DG), converters and batteries. Hybrid Optimization of Multiple Electric Renewables (HOMER) software has been used to assess the techno-economic feasibility. Four scenarios are evaluated and modeled by HOMER. A comparison of economic feasibility, renewable fraction, total emissions, and excess of electricity for all the scenarios is done. For an interest of 7%, the optimum hybrid system (PV/battery) has a levelized cost of energy (COE) of 0.236$/kWh, which is lower than the COE of the other hybrid systems ( PV/DG/battery, PV/Wind/battery and PV/wind/DG/battery) which are respectively, 0.242, 0,270 and 0.274 $/kWh. The Sensitivity analysis was also investigated in the intent to present the impact of changing the interest rate, battery increase, solar radiation, and the load demand increase on the performance of the hybrid system. The sensitivity results elucidate that the PV/Battery hybrid system is still viable for all interest rates ranging from 7 to 10% compared to PV/DG/Battery and PV/Wind/DG/Battery that are also report good economic performance but still suffer from harmful emissions. The combination of PV and batteries together ensures a clean electricity production compared to the PV/DG/Battery and PV/Wind/DG/Battery. The latter present a total CO 2 emission of 5200 kg/year with an increase of the COE that achieves 50% for DG/battery system. Furthermore, the hybrid system combining PV with batteries gives a high renewable fraction compared to the second optimal system.

Optimal design of stand-alone hybrid power system using wind and solar energy sources

Stand-alone hybrid renewable energy systems are more reliable than one-energy source systems. However, their design is crucial. For this reason, a new methodology with simulation having as aim to design an autonomous hybrid PV-wind-battery system is proposed. Based on a triple multi-objective, the present methodology combines life cycle cost (LCC), embodied energy (EE) and loss of power supply probability (LPSP). For a location, meteorological and load data have been collected and assessed. Afterwards, components of the system and optimisation objectives have been modelled. Finally, an optimal configuration has been put in place using a dynamic model and applying a controlled elitist genetic algorithm for multi-objective optimisation. This methodology has been applied successfully for the sizing of a PV-wind-battery system to supply at least 95% of yearly total electric demand of a residential house.

Power management and sizing optimisation of renewable energy hydrogen production systems

This paper presents the combined sizing and power management optimisation methodology for a small-scale stand-alone hybrid renewable energy (RE) hydrogen production system. System cost is argued to be dependent on efficiency and reliability. The optimisation strategy developed, implements a strength Pareto evolutionary algorithm (SPEA) and a single objective genetic algorithm (GA) in cascade. The objectives for optimisation are: system efficiency, cost and reliability. Three different geographic sites with different wind and solar renewable energy input potentials are optimised. Results are presented as three-dimensional Pareto surfaces as well as two-dimensional scatter plots. Relationships between objectives are illustrated as well as important correlations between objectives and design variables. The expected conflicting relationship between cost and efficiency is clearly observed from the Pareto curves. The methodology developed highlights the importance of considering the simultaneous optimisation of sizing and power management. It is concluded that the optimisation methodology developed is useful in evaluating these and similar hybrid RE systems and provides insight into the design trade-offs for multiple conflicting objectives.

Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm

Due to increasing energy demand and fossil fuel costs in island and remote areas, renewable energy resources are becoming increasingly attractive. The hybridization of these resources can help overcome their variability and intermittency and improve efficiency. Many independent hybrid renewable energy systems are used in remote and island areas for which weather data often is unavailable. To increase the accuracy of size optimization of such systems, more accurate weather data is needed and the use of weather forecasting data is helpful. In this article, a new hybrid optimization algorithm is proposed for the optimal sizing of a stand-alone hybrid solar and wind energy system based on three algorithms: chaotic search, harmony search and simulated annealing. To improve the accuracy of the size optimization algorithm results, weather forecasting is used along with artificial neural networks for solar radiation, ambient temperature, and wind speed forecasting. The main objective function of minimizing the total life cycle cost is used to assess the feasibility of the hybrid renewable energy system accounting for system reliability. The reliability of the system is assessed by the loss of power supply probability parameter. The new method is tested for the electrical load of the city of Khorasan, Iran. The results are compared with those obtained by the proposed algorithm (harmony search and simulated annealing-based artificial neural networks). The simulation results demonstrate the advantages of utilizing the hybrid optimization algorithm with weather forecasting data for a stand-alone hybrid renewable energy system.

Dynamic vulnerability in standalone hybrid renewable energy system

Ensuring continuous power supply in the hybrid renewable energy and battery system is important because power utilization is fundamental to economy and human well-being. Earlier studies have been concerned with the ability to supply a desired amount of power in a long-term static condition in the context of system reliability. Meanwhile, short-term dynamic behavior and its relevant vulnerability in a hybrid system associated with a continuous power supply has been given less attention due to the modeling complexity of the problem. This study uses a parametric approach to assess the dynamic transition of vulnerabilities potentially leading to disruptions in electricity supply throughout a given day to identify a specific vulnerable time. The methodology of quantifying the dynamic vulnerability of power source components during a given day in a hybrid system is developed. Then, the temporal dynamic vulnerability and overall vulnerability in the system are presented by changing the capacity size in the case of a fictitious standalone house. Through the analysis, the approach developed in this study would potentially highlight the greater contribution of the battery to continuous power supply, compared with the solar PV in the hybrid system.

Hybrid renewable energy supply for rural healthcare facilities: An approach to quality healthcare delivery

The lack of modern electricity supply has been a major impediment to proper functioning of the healthcare centers in the rural areas, contributing to high maternal and child mortality rates in a country. Therefore, this study focuses on how to address the identified problem so that the healthcare centers or clinics in the remote areas can provide timely delivery of medical services for the concerned people. This paper, then, presents the analysis of stand-alone hybrid renewable energy systems for basic healthcare services in the rural areas, where there is no grid energy supply or the supply from the existing grid is erratic and unreliable. One major factor that informs the selection of the hybrid energy system in this study is that it promises high reliability compared to a single energy system. The research presents a statistical analysis of the potential of wind and solar energies for a selected rural locations in Nigeria based on the available long-term hourly and daily meteorological data. It employs an optimal technical and economic design and sizing of hybrid electrical power systems’ components such as the wind, PV, battery and inverter systems, using the hybrid optimisation software (HOMER). Results show that Sokoto and Jos sites exist in the high wind potential regions, while the remaining sites are only suitable for small wind applications. Values obtained for global radiation show that all the sites enjoy considerable solar energy potential suitable for varying degree of solar energy applications. PV/wind/diesel/battery hybrid system configuration is considered optimum for rural health center at Iseyin, Sokoto, Maiduguri, Jos and Enugu, while hybrid systems involving PV/diesel/battery is considered ideal for Port-Harcourt, due to the quality of renewable energy potential. Hence, it was concluded that, the abundance of wind and solar resources in the country create an ideal environment for inclusion of renewable energy systems in the design and implementation of standalone power supply systems to improve rural healthcare delivery.