Design Of Hybrid Energy System Research Articles

Urban energy system management for enhanced energy potential for upcoming smart cities

Scientific and industrial development has given rise to a rapidly increasing energy demand. Alternative and augmented energy resources are expected everywhere due to scarcity and depletion of other non-renewable resources. During recent years wind and solar had emerged as a promising cleaner energy source to offer a favourable solution with better efficiency. Hence, the attention has now diverted towards scaling up of hybrid system of energy generation. Numerous attempts have been taken to demonstrate the technological development concerning the requirement of the region. Whilst some research has already started to evaluate the working of the prototype, insignificant attention has been paid towards it. The current work also focuses on the simulation with hybrid urban renewable energy systems for techno-economic feasibility analysis. There were earlier attempts to report the advancement occurred in the technological, scientific and industrial sector due to hybrid renewable energy system. In some regard, it was an attempt to showcase the modelling of a typical urban requirement in an hourly load profile to identify in the energy potentials of the urban region. These will help to summarize the past, present and future trends of the hybrid energy system design, development and implementation for the urban region, which can be later on replicated to other parts of the world.

A MILP algorithm for the optimal sizing of an off-grid​ hybrid renewable energy system in South Tyrol

The exploitation of renewable energy sources through sustainable energy technologies are taking the field to decrease the pollutions’ emissions into the Earth’s environment. To offset the limitations of such resources, hybrid energy systems are becoming fundamental in grid-connected applications as well as in off-grid ones. However, the unsteady behavior of renewable sources, such as Sun and Wind, complicates the prediction of the energy production’s trend. The main factors and components involved in the design of hybrid energy systems are: (i) type of generators, (ii) their optimal number, (iii) storage systems and (iv) optimal management strategies. All of them have to be considered simultaneously to develop the optimal solution aimed at either reducing the dependence from fossil fuels or granting the supply of energy. In this paper, a methodology based on the Mixed Integer Linear Programming (MILP) is presented and adopted to meet the electric demand of a mountain lodge located in a remote area in South-Tyrol (Italy). The methodology has been developed implementing an algorithm through the Matlab ©software. The algorithm is capable of evaluating the optimal size of a hybrid off-grid Solar–Wind system with battery storage in order to replace an Internal Combustion Engine (ICE) fueled by diesel.

Powering community electrical loads in Cameroon using off-grid hybrid energy systems

The millions of users in developing countries often live far off the electric grid (rural areas) which seems not very cost effective extending the national grid to these rural areas as per respective governments. Africa’s total primary energy supply has seen an increasing annual rate of about 3%, seeming to be the highest among all other continents. The African continent as a whole is endowed with large renewable energy potential, varying in type across diverse geographic locations. These resources, and the settings in which they exist, can point to country or regional specific renewable energy solutions to fit each nation’s strengths and needs. In Sub-Saharan Africa, reliable access to electric power must be consider a basic precondition to improve people’s lives as it further promote education, health care and economic growth via the creation of sustainable and clean energy jobs. Until recently, renewable energy technologies (RETs) have been confronted with a huge up-front cost and technologies in development but massive and global deployment of renewable energy systems has led to significant cost reductions and performance improvements and the hope is to see increasing uptake of RETs by African countries. Cameroon a Central African country is heavily reliant on hydropower, which contributes an estimated 60% to the country’s total installed 1,400MW capacity in 2015. In addition, there is constants power failure due to the non-reliability of the electric grid and load shedding to meet increasing demand. However, climate change poses additional huge risk (large reservoirs and dams drying up) and to meet the increasing demand, Cameroon is being forced to seek alternative power sources. This paper proposes the need for a sustainable hybrid energy system design and the development of an effective design, simulation and analysis approach of stand-alone off-grid in Cameroon as a potential optimal solution to help power community electrical loads. Finding an optimized mix of renewable energy technologies for Bandjoun and Muyuka were the goals of this paper.

Hybrid energy systems in unmanned aerial vehicles

Purpose The presented research is carried out in reaction to the soaring costs of fuel and tight control over environmental issues such as carbon dioxide emissions and noise. The purpose of this paper is to study the feasibility of applying the environmental-friendly energy source in an unmanned aerial vehicles (UAVs) propulsion system. Design/methodology/approach Currently, the majority of UAVs are still powered by conventional combustion engines. An electric propulsion system is most commonly found in civilian micro and mini UAVs. The UAV classification is reviewed in this study. This paper focuses mainly on application of electric propulsion systems in UAVs. Investigated hybrid energy systems consist of fuel cells, Li-ion batteries, super-capacitors and photovoltaic (PV) modules. Current applications of fuel cell systems in UAVs are also presented. Findings The conducted research shows that hybridization allows for better energy management and operation of every energy source onboard the UAV within its limits. The hybrid energy system design should be created to maximize system efficiency without compromising the performance of the aircraft. Practical implications The presented study highlights the reduction of the energy consumption, necessary to perform the mission and maximizing of the endurance with simultaneous decrease in emissions and noise level. Originality/value The conducted research studies the feasibility of implementing the environmental-friendly hybrid electric propulsion systems in UAVs that offers high efficiency, reliability, controllability, lack of thermal and noise signature, thus, providing quiet and clean drive with low vibration levels. This paper highlights the main challenges and current research on fuel cell in aviation and draws attention to fuel cell – electric system modeling, hybridization and energy management.

An improved genetic algorithm-based optimal sizing of solar photovoltaic/wind turbine generator/diesel generator/battery connected hybrid energy systems for standalone applications

This paper proposes an improved GA-based new approach for the optimal design of hybrid energy systems comprises of solar PV, wind, diesel generator and battery connected systems for supplying the electrical power. The proposed system uses the meteorological data of wind speed, wind velocities and solar radiations, which were collected from NASA website. Optimisation of hybrid energy system includes minimisation of total cost, net present cost, loss of power system probability, reduced greenhouse gas emissions, cost of energy, annualised system cost to make the system more economically for the domestic house hold applications. The optimisation of results can be achieved by using improved Genetic Algorithm (GA), which uses the variables such as wind turbine capacity, PV array ratings, number of battery banks, diesel generator rated power, system initialisation cost and operation and maintenance cost were considered as the input chromosomes for the algorithm. A suitable improved GA programme has been formulated using MATLAB toolbox with the objective function of minimising the total/net present cost of the proposed hybrid energy system for electrifying the rural areas in standalone applications.

Comparative analysis of hybrid systems for on-grid and off-grid applications in central China: Case study of university dormitory in Ma’anshan

In order to compare the design of hybrid energy systems for on-grid and off-grid applications, a university dormitory in central China is selected and investigated to achieve the target of a zero energy dormitory. The building is modeled in DeST and hybrid system design optimization is performed in HOMER. Results show that the on-grid hybrid system under time-of-use rate policy is much more economic than that under single rate policy for on-grid case. The total net present cost is 230,534 $ and the levelized cost of energy is 0.124 $/kWh. The off-grid system with generators is more economical than system without them, and the cost is found to be about 6 times than on-grid system. Sensitivity analysis is performed by considering sell-back price and diesel price, it is found that NPC and COE can be increased by 9.7% and 12.7% for the decreased sell-back price and doubled diesel price respectively.

Optimal design of hybrid energy system based on persuasive policies for renewable resources in Iran (case study: University of Bojnord)

Governments all over the world are tending to accelerate the process of replacing fossil based energies with renewable energy sources through developing incentive or punitive policies. In Iran, various incentive and punitive guidelines are regulated to persuade governmental and nongovernmental organizations to use renewable energy resources. In this paper, optimal planning and sizing of distributed renewable energy resources for governmental organizations in Iran, under persuasive policies, is proposed. This design includes a techno-economic analysis on the basis of total Net Present Cost (NPC) to obtain the optimal configuration of the hybrid energy system for governmental institutes among all possible combinations of distributed diesel generators (consisting of internal combustion engines with diesel fuel) as well as renewable energy resources such as wind energy conversion systems and solar photovoltaics. In order to evaluate the economic and technical aspects of the persuasive policies for governmental institutes in Iran, an optimal hybrid energy system is designed to provide for the energy consumption of the University of Bojnord. The proposed hybrid energy system consists of 100 kW photovoltaic panels, 20 kW wind turbines, a 10 kW diesel generator, and 10 one kW h batteries. The total NPC of the system is estimated to be 1.04 $M. In addition, a sensitivity analysis is carried out to investigate the impact of economic indicators on the design. The results show that the University of Bojnord would benefit from investing in the proposed design after six years.

Optimal design of hybrid energy systems incorporating stochastic renewable resources fluctuations

The potential impacts of variability and intermittency in renewable resources on the design of stand-alone renewables-based energy systems incorporating storage are addressed at the design stage. The framework developed accounts for climate-based variability by considering different stochastically generated renewable input scenarios in the evaluation of system reliability. Operational constraints which control the availability and discharge of storage technologies based on previous storage states and technology start-up times are incorporated into the energy system model to account for the intermittent power output from renewables. A cost-reliability bi-criteria sizing problem is solved for two cases of a remote Canadian mine to demonstrate that intermittency in generation can influence technology choices, system configuration and system operation. Approximations to the non-dominated fronts are generated with NSGA-II, and the operating characteristics of the maximum-reliability designs generated in the cases are investigated. The methodology provides the decision maker with information about a number of operable designs and an understanding of the performance risks associated with the selection of any given design.

The Value of Flexibility in the Design of Hybrid Energy Systems: A Real Options Analysis

In this paper, the impact of incorporating flexibility in the design of hybrid energy systems (HES) is considered. Flexibility is introduced by considering the option to upgrade or reconfigure HES configurations at some point in the future in response to economic and technological changes that are initially unknown and uncertain. Such flexibility has been studied previously in real options analysis. We first investigate the impact of flexibility on the most preferred design alternative and its value. Simply considering the option to upgrade or reconfigure the system affects the design choice. The most preferred design alternative for a flexible system will often sacrifice some initial technical or economic performance to better take advantage of a future option. For the HES case study, the most preferred flexible design alternative is more valuable than the most preferred inflexible alternative. In other words, flexibility adds value as is reflected in an increase of the expected utility of the net present value. Second, we investigate the impact of the size of the uncertainty on the option value. Unexpectedly, for the HES case study considered here, increasing uncertainty does not strongly affect the value of flexibility. Furthermore, investigation is necessary to determine whether this relationship holds more generally or is specific to this case study.

Evaluation of the effect of flexible demand and wave energy converters on the design of hybrid energy systems

Many islands have high electricity prices due to the reliance on imported diesel. However, hybrid energy systems (HES) which combine renewable generation with backup generators and energy storage are becoming cost competitive. Diesel usually provides about 10% of the demand because most renewables are non-dispatchable and thus the complete decarbonisation requires massively oversized renewable generation and storage. By including renewables with different resource profiles and demand side management (DSM), the diesel consumption could be decreased without increasing storage and renewable generation capacities. Here a framework for the design and optimisation of HES using wind, wave and solar generation and DSM is introduced. For the Mediterranean it is shown that wave energy is not competitive but that DSM reduces the emissions and costs by 21 and 8%. In the North Sea, DSM has lower benefits because waves act as an energy store for the wind. Thus, the combination of wave energy converters (WECs) and wind turbines significantly reduces the need for backup generation and energy storage which leads to large reductions in costs (up to 40%) and emissions (up to 60%). DSM and WECs can both simultaneously reduce the cost and emissions of HES but need to be designed for the particular circumstances.

Development of an ontology-based generic optimisation tool for the design of hybrid energy systems

The reliability and cost of energy systems and diversity of weather are the two main concerns for Hybrid Energy Systems (HES) optimisation in the face of energy scarcity. Many techniques for sizing and optimisation of such systems have been developed. However, these techniques are developed independently of each other and require end-users to know a priori the techniques to use as well as data inputs of each. There is no sharing of data between the various techniques although they can use the same data. The novelty of this study is to develop an ontology-based system that offers the end-user an optimal design solution without having to know in advance the optimisation techniques. To that effect, we present an ontology-based generic tool that includes most used energy sources for optimising HES. The proposed tool has been applied and tested on an isolated wind-photovoltaic hybrid power system with battery storage.

Development of an ontology-based generic optimisation tool for the design of hybrid energy systems

Development of an ontology-based generic optimisation tool for the design of hybrid energy systems

Maiden application of Cuckoo Search algorithm for optimal sizing of a remote hybrid renewable energy System

Solar and wind power based hybrid energy system with energy storage unit provides a reliable and cost effective energy alternative above the conventional diesel generator based system commonly used by remote consumers. In this context, this paper explores the application of a new meta-heuristic algorithm called Cuckoo Search (CS) in the area of a hybrid energy system design problem. Cuckoo Search (CS) is applied for optimal sizing of three different system schemes viz. Photovoltaic-Battery, Wind-Battery and Photovoltaic-Wind-Battery system applicable to a remote area located in Almora district of Uttarakhand, India while minimizing total system cost and considering seasonal variation of load. The effectiveness of Cuckoo Search algorithm in solving hybrid energy system design problem is investigated and its performance is compared with other well known optimization algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. Optimization results further, shows that hybrid integration of photovoltaic, wind and battery storage gives most reliable and economical system scheme for the study area. In addition, this paper assesses the effect of wind turbine generator (WTG) force outage rate (FOR) on the optimal system reliability and economics.

A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems

Hybrid energy systems (HESs) are becoming popular for standalone applications due to global concern regarding green house gas (GHG) emissions and depletion of fossil fuel resources. Research in the optimal design of HESs is ongoing, with numerous optimization techniques giving special emphasis to Pareto optimization, incorporating conflicting objectives. The subsequent decision-making process including the non-dominant set of solutions has yet to be addressed.This work focuses on combining multi-objective optimization with a multi-criterion decision making (MCDM) technique to support decision makers in the process of designing HESs. Four different objectives, i.e., levelized energy cost (LEC), unmet load fraction, wasted renewable energy (WRE) and fuel consumption are used to obtain the Pareto front. A decision support tool based on Fuzzy TOPSIS and level diagrams is proposed to analyze the Pareto front and support the subsequent decision-making activity. A case study is used to illustrate the applicability of the proposed method. The study shows that the novel method is useful when determining the relative weights of objectives, providing a detailed picture of the objective space to the designer when coming up with the optimum system. The technique proposed in this study can be further extended to analyze similar problems in energy system design where MCDM is necessary after multi-objective optimization.

Economic analysis and power management of a stand-alone wind/photovoltaic hybrid energy system using biogeography based optimization algorithm

The stand-alone energy system having a photovoltaic (PV) panels or wind turbines have low reliability and high cost as compared with wind/PV hybrid energy system. In this study, Biogeography Based Optimization (BBO) algorithm is developed for the prediction of the optimal sizing coefficient of wind/PV hybrid energy system in remote areas. BBO algorithm is used to evaluate optimal component sizing and operational strategy by minimizing the total cost of hybrid energy system, while guaranteeing the availability of energy. A diesel generator is added to ensure uninterrupted power supply due to the intermittent nature of wind and solar resources. Due to the complexity of the hybrid energy system design with nonlinear integral planning, BBO algorithm is used to solve the problem. The developed BBO Algorithm has been applied to design the wind/ PV hybrid energy systems to supply a located in the area of Jaipur, Rajasthan (India). Conventional methods require calculation at every single combination of sizing, operation strategy and the data for each variation of component needs to be entered manually and execute separately. Results show that the hybrid energy systems can deliver energy in a stand-alone installation with an acceptable cost. It is clear from the results that the proposed BBO method has excellent convergence property, require less computational time and can avoid the shortcoming of premature convergence of other optimization techniques to obtain the better solution.

Economic and technical study of a hybrid system (wind–photovoltaic–diesel) for rural electrification in Algeria

This paper deals with design of hybrid energy system consisting of wind and photovoltaic with battery storage. A diesel generator is added to ensure continuous power supply and to take care of intermittent nature of wind and photovoltaic. The paper reports results of the technical–economic optimization study of photovoltaic/wind/diesel hybrid with battery storage in Algeria. The primary objective of this study is to estimate the appropriate dimension of stand-alone hybrid photovoltaic/wind/diesel with battery storage that guarantee the energy autonomy of typical remote consumer with lowest cost of energy. A secondary aim is to study the impact of renewable energy potential quality on the system size. The optimum dimensions of the system are defined for six sites in Algeria. In this context, a complete sizing model is developed in Matlab/Simulink V.6.5, able to predict the optimum system configuration. The simulation results indicate that the hybrid system is the best option for all the sites considered in this study. Thus, it provides higher system performance than photovoltaic or wind alone. It s shown that the principal advantage of photovoltaic/wind/diesel hybrid with battery storage are used all together, the reliability of the system is enhanced. The economic analysis has resulted in the calculation of kWh cost of energy for different types of resources and optimized cost of hybrid energy system. It s revealed too that the energy cost depends largely on the renewable energy potential quality. So, our objective for the optimization parameters is not the production cost but the offered service.

POWER (power optimization for wireless energy requirements): A MATLAB based algorithm for design of hybrid energy systems

We have expanded and implemented an algorithm for selecting power supplies into a turnkey MATLAB code, “POWER” (power optimization for wireless energy requirements). Our algorithm uses three approaches to system design, specifying either: (1) a single, aggregate power profile; (2) a power system designed to satisfy several power ranges (micro-, milli- and Watt); or (3) a power system designed to be housed within specified spaces within the system. POWER was verified by conducting two case studies on hearing prosthetics: the TICA (LZ 3001) (Baumann group at the Tübingen University) and Amadeus cochlear implant (CI) (WIMS-ERC at the University of Michigan) based on a volume constraint of 2 cm 3. The most suitable solution identified by POWER for the TICA device came from Approach 1, wherein one secondary cell provided 26,000 cycles of 16 h operation. POWER identified Approach 2 as the solution for the WIMS-ERC Amadeus CI, which consisted of 1 cell for the microWatt power range and 1 cell for the milliWatt range (4.43 cm 3, ∼55% higher than the target volume), and provided 3280 cycles of 16 h operation (including re-charge of the batteries). Future work will be focused on continuously improving our present tool.