Modeling Of Hybrid Energy System Research Articles

Carbon neutrality strategy with small modular reactor-based hybrid energy system: A case study for a small Island and isolated power grid

As the threat of climate change intensifies, various efforts are being made to achieve carbon neutrality. Decarbonization across all industries, especially in the power generation sector, is a critical aspect to be considered. The introduction of renewable energy sources and an increase in their installed capacity in the power grid is essential to achieve carbon neutrality in the power generation sector. However, the expansion of renewable energy sources increases the vulnerability of the power grid due to their intermittent and variable characteristics and requires high levels of load-following performance from other power sources. In this study, we propose a hybrid energy system using nuclear (especially small modular reactors)-based hydrogen production, as an alternative solution for achieving carbon neutrality. The feasibility of the proposed hybrid energy system model was analyzed for the small Island isolated grid systems with simplified multi-physics simulation. The performance analysis results demonstrate that the proposed small modular reactor-hydrogen-based hybrid system can reliably meet grid demands while producing an annual surplus of 10,320.96 tons of hydrogen with reduced potential risk of thermo-mechanical-related component failures in the plant. The results of the current study can be expected to provide a significant milestone and insight into the achievement of carbon neutrality and a transition to a hydrogen economy, utilizing small modular reactor-based hydrogen production technology.

Techno-economic feasibility analysis of hydrogen production by PtG concept and feeding it into a combined cycle power plant leading to sector coupling in future

Power-to-Gas offers an efficient opportunity to turn renewable energy into “green” hydrogen, establishing an inevitably remunerative spectrum of end-uses. In this spirit, the current paper intends to establish a techno-economic perspective by evaluating a hybrid energy system model for sizing hydrogen generation by water electrolysis from renewable energy and using it in thermal power plants for electricity production for localized grids in Pakistan. Modeling of this hybrid system is done using HOMER Pro. Hydrogen is produced using a hybrid energy system and then fed into a hypothetical combined cycle power plant to produce electricity. Hydrogen has economic dominance over batteries in terms of energy storage and cost of energy, as per results. Four scenarios regarding proposed system configurations are considered in this study pondering upon how hydrogen can be produced from the perspective of cleaner production and assessing it techno-economically. Firstly, base case scenario consisting of wind turbine generators, genset, solar panels, batteries, convertor, electrolyzer and hydrogen tank is evaluated. Scenario − 1 is analyzed on the basis of techno-economic evaluations, excluding Li-Ion batteries from the base case. For scenario – 2, Li-Ion batteries have been included and genset is excluded from the system architecture to provide backup power to the electrolyzer during hours of intermittency aiming at least interruption. Lastly, scenario – 3 is exclusive of the photovoltaics and all rest remain intact. The economic analysis is constructed on economic parameters like payback period, internal rate of return, and cost of energy, and multiple configurations of the system. The most feasible configuration yielded levelized cost of energy being 0.465 USD/kWh, internal rate of return being 17.3 %, and payback period of 2.3 years. Renewable energy sources are thoroughly assessed for coupling with the desalination plant and electrolyzer array. This system can further be expanded on a larger scale to transform the region into a hydrogen hub to produce green, high-energy–density hydrogen to be supplied to and utilized by multiple sectors.

Development of fuzzy logic-based demand-side energy management system for hybrid energy sources

Demand-side energy management techniques, such as load shielding, shifting, and delaying appliance operation during peak periods, are typically used to reduce electricity costs at the expense of users’ comfort. To address these challenges, especially where operational delays are unacceptable, distributed generation (DG) is frequently incorporated into the grid system to improve power balance and total energy costs. However, dynamic load demands and varying outputs from renewable DG sources such as solar photovoltaic (PV) systems make energy management in microgrids (MGs) extremely challenging. Moreover, most of the existing studies in this domain focus on objective functions that are geared on optimising the economic balance between cost and value of MG operation over a certain time period. Nevertheless, research that took into consideration the stochastic behaviour of DG’s subsystems in addition to cost and benefit of MG operation are still limited. This current study proposed a fuzzy logic control (FLC) integrated energy management system (EMS) for commercial loads with hybrid grid-solar PV/battery energy system. The proposed technique intelligently selects energy sources using the grid energy cost and the state of charge (SoC) of the solar PV/battery at any time of the day. The EMS operate the loads at a reduced cost without any operational delay or shifting. The system was implemented in the MATLAB/Simulink environment, and the techno-economic feasibility of energy cost savings was investigated by comparing the developed scheme with the Homer hybrid energy system model for a hotel building. The developed EMS reduced energy costs by an average of 11.87 % per day and 7.94 % over a 20-year lifetime.

Power Scheduling Optimization Method of Wind-Hydrogen Integrated Energy System Based on the Improved AUKF Algorithm

With the proposal of China’s green energy strategy, the research and development technologies of green energy such as wind energy and hydrogen energy are becoming more and more mature. However, the phenomenon of wind abandonment and anti-peak shaving characteristics of wind turbines have a great impact on the utilization of wind energy. Therefore, this study firstly builds a distributed wind-hydrogen hybrid energy system model, then proposes the power dispatching optimization technology of a wind-hydrogen integrated energy system. On this basis, a power allocation method based on the AUKF (adaptive unscented Kalman filter) algorithm is proposed. The experiment shows that the power allocation strategy based on the AUKF algorithm can effectively reduce the incidence of battery overcharge and overdischarge. Moreover, it can effectively deal with rapid changes in wind speed. The wind hydrogen integrated energy system proposed in this study is one of the important topics of renewable clean energy technology innovation. Its grid-connected power is stable, with good controllability, and the DC bus is more secure and stable. Compared with previous studies, the system developed in this study has effectively reduced the ratio of abandoned air and its performance is significantly better than the system with separate grid connected fans and single hydrogen energy storage. It is hoped that this research can provide some solutions for the research work on power dispatching optimization of energy systems.

Economic impacts of carbon capture and storage on the steel industry–A hybrid energy system model incorporating technological change

Carbon capture and storage (CCS) is necessary to reduce greenhouse gas emissions that cannot be mitigated using other reduction options. However, the high cost of CCS raises doubts about its economic feasibility. This study analyzes CCS cost reduction and its macroeconomic effects and shows that CCS can be economically feasible in the long term. This study incorporates technology learning into a hybrid energy system model and investigates its impact on the economic feasibility of CCS in the Korean steel industry. The hybrid model integrates a bottom-up energy system model and a computable general equilibrium model and overcomes the limitations of employing independent models in exploring technology learning. According to the model, in 2050, the CCS unit cost decreases by 64% when the learning rate is 20%. Due to this cost reduction, the steel industry’s additional capital and labor costs resulting from CCS adoption decrease by 60%. Moreover, although CCS adoption and diffusion reduce steel production, 60% of this production loss can be mitigated by CCS cost reduction. The cost reduction also helps to reduce the GDP loss resulting from CCS adoption by 0.3 %p.

Techno-economic modelling of hybrid energy system to overcome the load shedding problem: A case study of Pakistan.

This paper demonstrates the application of hybrid energy system (HES) that comprises of photovoltaic (PV) array, battery storage system (BSS) and stand-by diesel generator (DGen) to mitigate the problem of load shedding. The main work involves techno-economic modelling to optimize the size of HES such that the levelized cost of electricity (LCOE) is minimized. The particle swarm optimization (PSO) algorithm is used to determine the optimum size of the components (PV, BSS). Simulations are performed in MATLAB using real dataset of irradiance, temperature and load shedding schedule of the small residential community situated in the city of Quetta, Pakistan. The LCOE for the HES system under study is 8.32 cents/kWh-which is lower than the conventional load shedding solution, namely the uninterruptable power supply (UPS) (13.06 cents/kWh) and diesel and generator system (29.19 cents/kWh). In fact, the LCOE of the HRES is lower than the grid electricity price of Pakistan (9.3 cents/kWh). Besides that, the HES alleviates the grid burden by 47.9% and 13.1% compared to the solution using the UPS and generator, respectively. The outcomes of the study suggests that HES is able to improve reliability and availability of electric power for regions that is affected by the load shedding issue.

Intelligent reactive power control of a renewable integrated hybrid energy system model using static synchronous compensators and soft computing techniques

Modern power system faces a severe problem of instability, largely due to inconsistent reactive power. It causes damage to the power grid within a few milliseconds. Therefore, proper management of reactive power under disturbing situations plays a key role in its safe operation. Devices such as flexible alternating current transmission systems (FACTS) accurately manage the system’s reactive power in accordance with the load demand. In this study, a new reactive power control strategy is employed for optimization of the reactive power along with the stability improvement of the system under different small perturbed conditions. Therefore, this study focuses on controlling the reactive power for an isolated wind-diesel hybrid power system model (WDHPSM) with the aid of a static synchronous compensator (STATCOM) together with the use of an integral minus proportional derivative (IPD) controller keeping a derivative-based filter (IPDF) as a secondary controller for better utilization of its purpose. The obtained results are compared when the no-control strategy is applied in the model. Another comparison has been done between the multiple applied soft computing techniques (oppositional harmonic search, ant lion optimization, binary-coded genetic algorithm, and symbiosis organisms search) that optimize the parameters of the controller of WDHPSM.

Hybrid Energy System Model in Matlab/Simulink Based on Solar Energy, Lithium-Ion Battery and Hydrogen

In this work, a model of an energy system based on photovoltaics as the main energy source and a hybrid energy storage consisting of a short-term lithium-ion battery and hydrogen as the long-term storage facility is presented. The electrical and the heat energy circuits and resulting flows have been modelled. Therefore, the waste heat produced by the electrolyser and the fuel cell have been considered and a heat pump was considered to cover the residual heat demand. The model is designed for the analysis of a whole year energy flow by using a time series of loads, weather and heat profile as input. This paper provides the main set of equations to derive the component properties and describes the implementation into MATLAB/Simulink. The novel model was created for an energy flow simulation over one year. The results of the simulation have been verified by comparing them with well-established simulation results from HOMER Energy. It turns out that the novel model is well suited for the analysis of the dynamic system behaviour. Moreover, different characteristics to achieve an energy balance, an ideal dimensioning for the particular use case and further research possibilities of hydrogen use in the residential sector are covered by the novel model.

Capacity configuration optimization of a hybrid renewable energy system with hydrogen storage

ABSTRACT Different from low-temperature electrolysis systems, the large power consumption for the balance of plant (BOP) of the reversible solid oxide cell (RSOC) system for a high-temperature operating condition needs to be considered in the determination of the capacity configuration of the hybrid renewable energy (HRE) system. To address this issue, a power-based model of the RSOC system is developed and the corresponding capacity configuration strategy especially for the HRE system is also proposed in this paper. An optimization program of a hybrid energy system model composed of the wind turbines (WT), photovoltaic panels (PV), reversible solid oxide cell (RSOC) system, hydrogen storage tank (HST), and battery are presented to urge the minimization of the total system cost, power redundancy, and power shortage. Particle swarm optimization (PSO) algorithm is utilized to determine the optimum size and operational energy management within the system. The results show that after the regulation of the energy storage system, the power redundancy and shortage of the hybrid energy system are greatly reduced with the decreases by 85.08% and 64.42%, respectively. Moreover, the power mismatch is still significantly affected by seasons. It is also found that the energy storage efficiency of the RSOC system is within 20% due to the fact that part of the electric energy is consumed by the BOP to maintain the operation of the RSOC system. Thus, more improvements should focus on simplifying the BOP system of the RSOC system and reducing the excess power consumption in the future.

Study of Modeling of Hybrid Energy System for Optimum Power Extraction from the System to the Grid

With the growing demand of electricity, deployment of micro grid is becoming an attractive option to meet the energy demands. At present, large-scale wind/solar hybrid system is of great potential for development. The large-scale wind/solar hybrid system is of higher reliability compared with wind power generation alone and solar power generation alone However, a grid-connected micro grid suffers from critical stability problems during a power grid failure. For stable operation of the micro grid during a grid failure. In this paper, the transition stability of the micro grid is examined during a power failure

Price Based Demand Response for Optimal Frequency Stabilization in ORC Solar Thermal Based Isolated Hybrid Microgrid under Salp Swarm Technique

Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system’s stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system.

A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects

Improving efficiency is an important option for reducing manufacturing sector emissions. More efficient technologies reduce energy use and emissions. However, efficiency improvements can induce unexpected effects known as rebound effects. Although previous studies have analyzed these effects, these studies fail to precisely evaluate the rebound effects due to improvements in technology efficiency. Bottom-up models are appropriate for analyzing efficiency improvements at the technology level, but they face limitations in exploring output changes because they usually assume that demand is given. In contrast, top-down models are appropriate for observing output changes in an efficiency-improving sector and in the rest of the economy, but they face limitations in explicitly describing technological changes. This study therefore constructs a hybrid model to overcome the limitations of both types of models and evaluates the impacts of climate policy in Korea’s manufacturing sector when rebound effects are considered. The expected emissions reduction due to new technology adoption in the manufacturing sector is 23.8 million tons CO2eq without rebound effects, but when rebound effects are included, the actual emission reduction (12.7 million tons CO2eq) is about 50% of the expected amount.

Modified Cascaded H-bridge Multilevel Inverter for Hybrid Renewable Energy Applications

Renewable energy sources and technologies have the potential to provide solutions to the long-standing energy problems being faced by developing countries. The renewable energy sources like wind energy, solar energy, geothermal energy, ocean energy, biomass energy and fuel cell technology can be used to overcome energy shortage in India. This paper proposes a modified multi-level inverter (MLI) topology for Hybrid Renewable Energy Sources (HRES) and a design of hybrid solar-wind power generation model with 9-level, 13-level and 17-level inverter topologies. A HRES connected to a modified Cascaded H-Bridge Multi Level Inverter (CHB-MLI) is developed, whose switches are controlled using Artificial Neural Network (ANN) model. The proposed hybrid energy system model consists of 10 Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) that intend to give 17 levels of output voltage. The proposed topology performs effectively with reduced number of components and reduced Total Harmonic Distortion (THD). The performance of the proposed system is analyzed by designing the model in MATLAB/SIMULINK environment. The simulation results of the proposed inverter for the HRES application are compared with the results of the existing topologies to show the effectiveness of the proposed model.

Event-Triggered Multiagent Optimization for Two-Layered Model of Hybrid Energy System With Price Bidding-Based Demand Response.

Due to uncertainty and dynamic characteristics from intermittent energy and load demand response (DR), the optimal operation of the hybrid energy system is a great challenge. This article proposes an event-triggered multiagent coordinated optimization strategy with two-layered architecture. First, the price-bidding-based DR model is proposed with different stakeholders, and it also deduces the optimal bidding price with the Nash equilibrium theory. Then, four agents are designed to control different kinds of energy resources: agent 1 mainly analyzes the uncertainty or randomness caused by intermittent power, agent 2 takes charge of the dynamic economic dispatch (DED) within thermal units, agent 3 manages the optimal scheduling of energy storage, and agent 4 mainly undertakes the load-shifting strategy from consumers. In the upper-layer level, all agents coordinate together to ensure the stability of the hybrid energy system with an event-triggered mechanism, and the intelligent control approach mainly depends on switching ON/OFF power generators or curtailing system load, and the consensus algorithm is utilized to optimize the subsystem problem in the lower-layer level. Furthermore, the simulation results can further verify the efficiency of the proposed method, and it also reveals that the event-triggered multiagent optimization strategy can be a promising way to solve the hybrid energy system problem.

Optimal sizing of off-grid hybrid energy system based on minimum cost of energy and reliability criteria using firefly algorithm

Solar and wind energy based hybrid energy system (HES) have received considerable global attention for remote applications where extension of grid supply is infeasible. This paper attempts to develop an optimal hybrid energy system model using available solar and wind energy resources with battery storage for fulfilling the electrical needs of three un-electrified remote villages located in Senapati district of Manipur, India. A Firefly algorithm based approach is used to find the optimal hybrid system configuration based on minimum cost of energy (COE) while satisfying a specified reliability criteria identified with loss of load probability (LOLP) reliability index. Further, system investigation has been carried out for optimal system feasibility at various values of LOLP. The optimal hybrid energy system is able to provide feasible solutions for LOLP values lying between 0 and 0.03. For LOLP value above 0.03, the system becomes infeasible as the COE increase with increase in LOLP.

Integration of Different Individual Heating Scenarios and Energy Storages into Hybrid Energy System Model of China for 2030

Traditional energy supply infrastructures are on the brink of facing a major transformation due to energy security concerns, environment pollution, renewable energy intermittency and fossil fuel scarcity. A hybrid energy system constitutes the integration of different energy carriers like electricity, heat and fuel which play a vital role in addressing the above challenges. Various technological options like combined heat and power, heat pumps, electrolysers and energy storages ease out multiple carrier integration in an energy hub to increase system flexibility and efficiency. This work models the hybrid energy system of China for the year 2030 by using EnergyPLAN. Atmosphere decarbonization is achieved by replacing conventional coal and natural gas boilers with alternative individual heating sources like hydrogen operated micro combined heat and power natural gas micro combined heat and power and heat pumps. Moreover, rockbed storage as well as single and double penstock pumped hydro storages are added in the proposed system in order to cope with the stochastic nature of intermittent renewable energy such as wind and solar photovoltaic. The technical simulation strategy is employed to analyze the optimal combination of energy producing components by determining annual costs, fuel consumption and CO2 emissions. The results substantiate that a heat pump and double penstock pumped hydro storage addition to the individual heating and electricity network not only proves to be an economically viable option but also reduces fuel consumption and emissions.

Research and simulation of energy control strategy for pure electric vehicle based on advisor

This paper is based on the simulink and advisor2002 simulation software, aiming at the energy control strategy of pure electric vehicle whose energy storage system is composed of batteries and ultracapacitors in parallel. In order to improve the efficiency of braking energy recovery, a hybrid energy system model was built and a fuzzy control based energy allocation strategy was established. The hybrid energy system can reasonably distribute the energy output ratio of batteries and ultracapacitors, and improve the system performance.

Modeling of hybrid energy system for futuristic energy demand of an Indian rural area and their optimal and sensitivity analysis

Abstract The aim of this paper is to model a hybrid energy system for rural India. In this analysis a hybrid renewable system consists of solar-wind-hydrokinetic-bioenergy is proposed. Overall analysis including Optimization and sensitive analysis are evaluated by HOMER software. Optimized results are evaluated considering total net present cost, cost of energy, annual electric generation, renewable fraction and CO2 emission. The analysis is done in order to increase efficiency of the system with comparatively less cost. From this exercise it is found that, combinations of more varieties of different renewable energy system are better to fulfill futuristic demand. Futuristic demand is calculated by logistic growth model. The value of COEs ($) and total generations (kWh/yr) are 0.3563 and 133045; 0.247 and 170948; 0.242 and 179018; 0.241 and 179303 for the year (2012–2021), (2022–2031), (2032–2041) and (2042–2051) respectively. However some other combinations may produce more power, although in such cases, in order to storage excess power COE will increase. As compared to the year (2012–2021) to (2042–2051) the optimized COE of electricity is minimized, keeping Annual cost nearly constant and amount of electric generation is increased without much effect on environment.

A Review on Economical and Technical Analysis for Modelling of Hybrid Energy System

A Review on Economical and Technical Analysis for Modelling of Hybrid Energy System

Optimization of PV/WIND/DIESEL Hybrid Power System in HOMER for Rural Electrification

A large proportion of the world's population lives in remote rural areas that are geographically isolated and sparsely populated. The present study is based on modeling, computer simulation and optimization of hybrid power generation system in the rural area in Muqdadiyah district of Diyala state, Iraq. Two renewable resources, namely, solar photovoltaic (PV) and wind turbine (WT) are considered. The HOMER software is used to study and design the proposed hybrid energy system model. Based on simulation results, it has been found that renewable energy sources perhaps replace the conventional energy sources and would be a feasible solution for the generation of electric power at remote locations with a reasonable investment. The hybrid power system solution to electrify the selected area resulted in a least-cost combination of the hybrid power system that can meet the demand in a dependable manner at a cost about ($0.321/kWh). If the wind resources in the study area at the lower stage, it's not economically viable for a wind turbine to generate the electricity.