Configuration Of Hybrid System Research Articles

Evaluation of the pollutant removal efficiency of swine wastewater through two configurations of hybrid wetlands with tropical ornamental plants

The pig farming industry in Mexico is an important economic activity that is growing significantly, generating large volumes of wastewater that negatively affect water bodies and human health. The lack of adequate treatment systems exacerbates this problem. Hybrid constructed wetlands that combine Vertical Flow Constructed Wetlands (VF-CWs) and Horizontal Flow Constructed Wetlands (HF-CWs) offer an economical and effective treatment using natural processes. The objective was to evaluate the removal of contaminants from pig farm wastewater using two configurations of hybrid systems with ornamental plants. Two configurations were established: System I: VF-CWs + HF-CWs and System II: HF-CWs + VF-CWs. The VF-CWs were planted with Canna hybrids and the HF-CWs with Heliconia latispatha. The results indicated higher removal efficiencies of organic matter, nitrogen, and phosphorus in System I (BOD5: 72.99 %, COD: 71.41 %, TN: 79 %, NH4+: 84.31 %, NO3-: 74.29 %, TP: 59.54 %, FC: 99.88 %) compared to System II (BOD5: 66.80 %, COD: 67.01 %, TN: 77.90 %, NH4+: 82.31 %, NO3-: 70.48 %, TP: 55.81 %, FC: 99.89 %), regarding FC, the same results were obtained in both systems. Both plant species showed vigorous development, although the growth of Heliconia latispatha was more notable. In conclusion, the results suggest that the VF-CWs + HF-CWs configuration in hybrid wetlands could be a suitable option for treating this type of effluent.

Feasibility analysis of hybrid photovoltaic, wind, and fuel cell systems for on–off‐grid applications: A case study of housing project in Bangladesh

AbstractThis study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development.

A Design of Economically Feasible Hybrid Energy System with Renewable Energy Ratio Priority

The reduction of fossil fuels which produce CO2 emission that damage the environment, can be done by implementing renewable energy-based power generations, such as solar and wind. This research designs a hybrid energy system by optimizing the use of existing diesel generators through the integration of renewable energy sources, such as solar photovoltaic and micro wind turbine, and is equipped with an energy storage system. This research uses HOMER Pro software to determine the optimal capacity of hybrid system components, and to calculate the cost of energy (CoE). Furthermore, the hybrid system configuration is analyzed by applying several objectives. The objectives of the hybrid system design are to prioritize a maximum renewable energy penetration ratio within permitted annual capacity shortage and with the CoE lower than the existing CoE. The research results show that the proposed hybrid energy system can provide a renewable energy penetration ratio of 57.1% with CoE of IDR 3,510/kWh.

Design Solar Photovoltaic Diesel Hybrid System with Battery Storage for Rural Remote Area: A Case Study of Mwala Village Mbeya District

Reliable hybrid systems (solar photovoltaic and diesel generators) have been shown to produce high-quality energy that supports different social and economic activities in Mwala village and Mbeya region in the United Republic of Tanzania, which contain three hundred households for the purpose of reducing poverty. The system was designed after load demand analysis with the help of Hybrid Optimisation of Multiple Electric Renewables (HOMER) software. For simulations on a diesel generator standalone system, a generator with penetration of renewable energy resources (solar photovoltaic) system, and a solar PV standalone system. The components of the hybrid system configuration include a generator of 24 kW, a solar photovoltaic of 29.5 kW, an inverter of 10.4 kW, and a generic 1 kWh lead acid with 120 strings. The paper features a detailed analysis of fuel consumption, optimisation of the system, capital cost, operating cost, electrical energy obtained, gas emissions, and sensitivity analysis. The result obtained from the model revealed that the total energy generated was about 75366 kWh per year, with an excess of 7240 kWh per year, which increased the reliability of power and allowed the availability of energy for new buildings and electrical appliances. The gas emissions from a generator standalone system were three times higher than those of a reliable hybrid system. Based on the energy demand, the solar PV diesel hybrid system with batteries has proven to supply reliable power 24/7.

Technical, economic, and environmental feasibility assessment of solar-battery-generator hybrid energy systems: a case study in Nigeria

Supermarkets in Nigeria rely on diesel generators for electricity due to the unreliability of the national grid. The recent removal of petroleum subsidies in 2023 has increased fuel prices by 60%. This research examines the technical, economic, and environmental viability of employing solar PV/battery storage/generator systems to generate electricity for high-load supermarkets. The case study was conducted in the Market Square (MS) supermarket in Port Harcourt (PH) city, Nigeria. The MS supermarket had a load demand of 59.8 kW/day for an energy audit in 2022. The average solar radiation and temperature for PH city were 4.21 kWh/m2 and 25.3°C, respectively. The hybrid system was simulated with the HOMER Pro software. The simulation revealed that the optimum baseline (BL) system for the present price of a liter of diesel in Nigeria ($0.63 USD/L) was a solar PV/Battery/Generator. The optimal BL system produced 401,599 kWh/year, which was more than adequate to cover the yearly load requirement of 204,765 kWh/year and left a surplus of 173,195 kWh/year. The BL system had a levelized cost of electricity of $0.106 USD/kWh, a net present cost of $232,533, and Operation and Maintenance cost of $7,928. When the overall environmental impact of the optimal BL system was assessed, it contributed 10,935 kg CO2-eq/year of global warming potential, 1,611 kg O3-eq/year of smog formation, and 72.2 kg SO2-eq/year of acidification potential to the environment. Sensitivity analysis shows that the BL system could have a net present value of $710,364, a 38% internal rate of return, and a 2-year simple payback period over a 25-year life if the excess energy is sold to the grid. Also, LCOE increases with fuel price or discount rate increase, while CO2 falls as all renewable hybrid system configurations become more advantageous. The potential reduction in CO2 emission in the proposed system highlights the environmental benefits compared to traditional ones. This finding will guide decisions on adopting hybrid energy solutions for supermarkets in Nigeria. This analysis offers crucial insights for energy sector decision-makers seeking to balance reliability, cost-effectiveness, and environmental sustainability in a volatile market.

Optimal design and analysis of a grid‐connected hybrid renewable energy system using HOMER Pro: A case study of Tumbatu Island, Zanzibar

AbstractThis study addresses the pressing issue of quality electricity access in remote regions, with a specific focus on Tumbatu Island in Tanzania. Most studies on quality improvement concentrate on low‐voltage distribution lines and leave high‐voltage (HV) transmission lines behind. It is essential to address quality issues in HV lines due to their critical role in electricity transmission and distribution infrastructure. The objective of the study is to improve the voltage profile on the island's HV transmission line by identifying the optimal hybrid energy system comprising solar PV, wind turbine, and battery technologies. The study begins by presenting the total power demand and consumption on Tumbatu Island, which are important factors in designing an efficient energy system. The findings reveal a power demand of 7173 kW and a consumption of 28540 kWh/day, with an average scaled value of 1507.9 and 6000 kWh/day. To achieve the desired voltage profile improvement, the research incorporates HOMER Pro software for simulating and analyzing various hybrid system configurations. Essential input parameters, such as costs, resources, technology components, and load, are considered in the simulation process. The software generates a ranked list of options based on the system's net present cost (NPC). The simulation results demonstrate that the integration of solar PV, wind turbine, and HV lines provides a substantial improvement in the voltage profile, increasing it from 29.6 to 31.23 kV during peak demand periods. This solution proves to be the most economically viable, with the lowest NPC of $4,003,851 and a relatively short payback period of 3.79 years. In addition, a sensitivity analysis is performed to identify the most influential parameter in the system's performance. Wind speed is found to have the greatest impact, emphasizing its significance in the design and operation of the hybrid energy system. The implementation of this optimal hybrid renewable energy system on Tumbatu Island will not only improve the voltage profile and meet the island's energy needs but also shall contribute to global efforts in reducing pollution and the cost of electricity to the Tumbatu Island population. Moreover, it addresses the current and future demands for clean energy, underlining its importance in achieving sustainable and accessible electricity in sub‐Saharan Africa and beyond.

Evaluating the impact of off-design CHP performance on the optimal sizing and dispatch of hybrid renewable-CHP distributed energy resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52 %), too conservative in frequently cold climates (up to 11 %), or unaffected (＋/−1 %) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems’ ability to mitigate potentially negative consequences attributed to off-design performance.

Assessing the performance of hydro-solar hybrid (HSH) grid integration: A case study of Bui Generating Station, Ghana

Renewable energy sources (RES) are rapidly expanding as a result of energy security and environmental concerns. Despite their numerous benefits, they pose significant challenges to power grid operation. Ghana is dedicated to reaching a 10 % renewable energy mix target by 2030 to promote low-emission development. Ghana has the first hybrid power plant made up of 400MW hydropower plant and 50 MW solar PV plant supplying power to the national grid. The study designs a hydro-solar hybrid system configuration for Ghana's Bui generation unit, using data from the 50 MW ground-mounted solar PV and 133.33 MW hydropower units to assess the performance and challenges of the hydro-solar hybrid system at the Bui Generating Station. Methodology involves modeling and simulation in the DIgSILENT power factory software environment. Utilizing quasi-dynamic simulations, the study investigates variations in active power generation, voltage fluctuations, grid losses, and reactive power generation. Results highlight technical challenges such as voltage fluctuations and power loss, and propose mitigation measures. Comparisons between simulated and field data reveal discrepancies attributed to factors such as temperature effects, dust accumulation, and conductor resistance. Mitigation strategies are proposed, including energy storage expansion, smart grid implementation, advanced control techniques, FACTS device deployment and grid monitoring improvements. Despite limitations in data availability and simulation accuracy, the study underscores the system's reliability and provides insights for enhancing renewable energy integration in the region. Generally, the study contributes to advancing renewable energy integration efforts, with implications for sustainable development and climate action in Ghana and West Africa at large.

A hybrid poly-generation system for power and hydrogen production by thermal recovery from waste streams in a steel plant: Techno-economic analysis

The steel industry stands as a prominent energy-intensive sector characterized by significant heat losses. In this research, a novel configuration of a poly-generation hybrid system, specifically tailored to explore the viable prospects of waste heat recovery within a steel manufacturing facility, is introduced. The proposed system comprises a steam Rankine cycle (SRC), a Kalina cycle, two organic Rankine cycles (ORC), and a proton exchange membrane (PEM) electrolyzer, collectively facilitating the recuperation of an impressive 262 MW of dissipated energy from the steel plant. A technical and economic assessment is conducted to evaluate the performance of the system. The proposed system demonstrates an energy efficiency of 25.76%, resulting in the concurrent production of power, heat, and hydrogen at rates of 48.39, 29.42 MW, and 8.12 tons/day, respectively. The system exhibits an exergy efficiency of 57.46%, with an exergy destruction magnitude of approximately 45 MW. It is revealed that the SRC cycle represents the primary contributor to the energy destruction portfolio of the proposed system, accounting for an impressive 67.83%. Furthermore, a comprehensive economic analysis has been conducted, revealing an initial capital cost of 36.6 MM$ for the implementation of this system. The revenue generated from the sale of electricity and hydrogen amounts to 3.6 and 3.8 MM$ per annum, respectively. Based on these financial considerations, the estimated return period for the investment is projected to be approximately 7 years.

Driving Behaviour Estimation System Considering the Effect of Road Geometry by Means of Deep NN and Hotelling Transform

In this work, an intelligent hybrid model is proposed to identify hazardous or inattentive driving manoeuvres on roads, with the final goal being to increase and ensure travellers’ safety and comfort. The estimation is based on the effects that road geometry may have on vehicle accelerations, displacements and dynamics. The outputs of the intelligent systems proposed are how the type of driving can be characterized as normal, careless or distracted. The intelligent system consists of an LSTM (Long Short-Term Memory) neural network in a first step that distinguishes between normal and abnormal driving behaviour and then a second module that classifies abnormal forms of driving as aggressive or inattentive, with the latter implemented with another LSTM, a CNN (convolutional neural network) or the Hotelling transform. They are applied to some of the characteristics of vehicle dynamics to estimate the driving behaviour. Smartphone inertial sensors such as GPS, accelerometers and gyroscopes are used to measure these vehicle characteristics and to identify driving events in manoeuvres. Specifically, the critical acceleration due to the influence of the road geometry can be measured with inertial sensors, and then, this road acceleration with the lateral acceleration allows us to estimate the driver’s perceived acceleration. This perceived acceleration affects the driving style and, consequently, the estimation of the appropriate speed to travel on that road. There is use of both a traditional two-lane and a motorway route located in the Madrid region of Spain. Driving behaviour is determined by considering how changes in road geometry may affect one’s driving style and, consequently, the estimation of the proper speed. The results obtained with some of the proposed configurations of the intelligent hybrid system reach an accuracy of 97.21% in detecting dangerous driving or driving with a certain risk. This could allow generating real-time alerts for potentially dangerous or inattentive manoeuvres, leading to safer and more appropriate driving.

Techno‐economic optimization framework of renewable hybrid photovoltaic/wind turbine/fuel cell energy system using artificial rabbits algorithm

AbstractIn order to maximize the electricity supply from clean energy sources, the goal of the smart power system is to unite all renewable energy sources. The goal of the present study is to use three optimization techniques, artificial rabbits optimization algorithm (ARO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA), to reduce the cost of electricity (COE) while improving the reliability of the power supply for rural areas. While using the same control variables for the optimization methods and load profile, various hybrid system configurations are explored. Photovoltaic, wind turbine, fuel cell, and electrolyser systems are all involved in the proposed hybrid renewable system. The ARO methodology is more effective than the GWO, WOA, and PSO procedures in terms of net present cost (NPC) and cost of energy (COE) generation, according to data comparing the three optimization techniques with the traditional Particle Swarm Optimization (PSO) method. The proposed ARO reached a value of COE of 0.4412$/kWh compared to 0.4438$/kWh for GWO, 0.4443$/kWh for WOA, and 0.44378$/kWh for PSO.

Integrative analysis of diverse hybrid power systems for sustainable energy in underdeveloped regions: A case study in Indonesia

<abstract> <p>There is a goal for practical renewable electrification and renewable energy investments in underdeveloped regions. Indonesia's experience underscores the complexities and challenges in implementing such projects effectively. A study on the effects of various socio-economic factors on Carbon dioxide (CO<sub>2</sub>) emissions in Indonesia highlights the significant impact of forest area, urbanization, and industrialization on carbon emissions. A hybrid system consists of PV, a Biogas Generator, and a Wind Turbine that are successfully deployed. However, no economic analysis has been conducted to obtain the best configuration of the hybrid system. We propose to delve into the effective integration combination of hybrid power systems. In this study, we thoroughly analyzed hybrid power systems in underdeveloped areas using the HOMER software. We examined five different hybrid system configurations: Solely biogas, complete generator integration, a biogas and hydrogen combo, biogas coupled with a PV system, and biogas combined with a wind turbine. Our findings indicated varying levels of economic viability, operational performance, and environmental impact across the configurations, providing crucial insights for policymakers and stakeholders in underdeveloped regions like Indonesia. The results showed the Wind-Hydrogen and Hydrogen Only schemes as the most cost-effective, with a Total Net Present Cost (NPC) of, 969.27 and Levelized Cost of Energy (LCOE) at zhongwenzy.218. Moreover, while CO<sub>2</sub> emissions were similar across all schemes, around 27,744 kg/year, the All-Generator scheme had slightly higher emissions at 27,667 kg/year but led in electricity production with 29,101 kWh/year. These results underscore the importance of balancing cost, energy output, and environmental impact in hybrid power system schemes for underdeveloped regions.</p> </abstract>

Assessing the impact of power dispatch optimization and energy storage systems in Diesel–electric PSVs: A case study based on real field data

This research paper presents an in-depth analysis of diesel–electric power systems in offshore Platform Supply Vessels (PSVs). The main contribution is the use of real data obtained from a PSV to produce and validate computational models subsequently used to accurately calculate fuel consumption and emissions, with representative load demands, considering different configurations of non-hybrid and hybrid power systems with the addition of lithium-ion batteries to provide a reliable analysis. Power dispatch optimization had a significant impact, achieving fuel and CO2 reductions of around 7%–12% in non-hybrid systems, depending on the generator loading limits. Hybridization and battery integration further enhanced reductions, with up to 10% improvements in fuel consumption and CO2 emissions. Particulate matter (PM) emissions and running hours were substantially reduced, but NOx varied. Validity checks accounted for biases, and the study provided reliable assessments of trends. The differences between monthly averages and robust approaches were minimal. Overall, the strategies presented achieved reductions of up to 15% in fuel consumption and CO2 emissions, 20% in NOx emissions, and 68% in PM emissions for the complete mission.

Novel approach for optimizing wind-PV hybrid system for RO desalination using differential evolution algorithm

Access to clean water is a basic human right, and reverse osmosis (RO) is a common method for producing potable water from seawater. However, the high energy demands of RO systems make them expensive to operate. Hybrid systems that combine renewable energy sources (RES), such as wind and photovoltaic (PV) systems, can reduce the energy costs associated with powering RO systems. In this paper, a novel approach that uses a differential evolution (DE) algorithm to optimize wind-PV hybrid systems for RO desalination is proposed. (DE) is a heuristic, population-based algorithm that searches for the global optimal solution. The approach aims to minimize the levelized cost of energy (LCOE) and ensure that Desalinated water costs are within an appropriate range. The algorithm was used in a case study of the city of Dhahran, Saudi Arabia, which faces significant water scarcity challenges. The results show that for an RO load demand of 1 kW, the optimized hybrid system's configuration includes a 26 PV panels with generation capacity of 7.67 kW, 2 wind turbines with 1 kW production capacity each and 9-battery storage system with 38.79 kWh storage capacity. The LCOE is 0.39 $/kWh for Dhahran city, and the cost of desalinated water falls between 1.98 and 2.16 $/m3, which is lower than the costs reported in the literature.

Effect of system configuration on the performance of a hybrid air conditioning system based on R-1234yf

The study presents theoretical results on a hybrid air conditioning system in which the sensible and latent loads are separately managed. The problem studied is significant in view of the growing demand for air conditioning systems globally, and also due to the adverse impact of these systems on global warming. In order to reduce the environmental impact of the air conditioning systems, this study proposes a hybrid system comprised of a vapour compression heat pump and a desiccant wheel. Due to restrictions on high global warming potential (GWP) refrigerants, R-1234yf, a low GWP refrigerant is considered as the working fluid for the heat pump. An enthalpy wheel is included to reduce the ventilation load on the system. The proposed hybrid system’s performance is evaluated using the first and second laws of thermodynamics and psychrometric principles. Results are compared with that of a conventional air conditioning system. Based on the calculated values of component and process wise irreversibility, further modifications to the hybrid system are proposed. These modifications consist of addition of a liquid-to-suction heat exchanger and use of a split condenser. Results show that depending upon the latent load on the conditioned space, the compressor power input can be reduced by as much as 47% using the proposed hybrid system. Compared to the conventional system, the modified hybrid system shows excellent performance under both high as well as low latent loads, whereas the simple hybrid system performs very well in applications involving high latent loads. The work presented is novel as it considers both first and second laws of thermodynamics to arrive at an optimum hybrid system configuration using an environment friendly refrigerant. It is expected that the study will be useful in the development of energy efficient and environment friendly air conditioning systems that operate equally well under low and high latent loads.

Optimization Effect of the Improved Power System Integrating Composite Motors on the Energy Consumption of Electric Vehicles

The multi-power source coupled transmission system is a high-performance and energy-saving potential power transmission system, and most of the commonly used pure electric vehicles in the market that use multi-power source coupled drive adopt the motor dual-axis distributed independent drive scheme. The configuration design method for multi-power source fusion hybrid systems mainly focuses on the search and selection of power split hybrid systems based on planetary gear mechanisms. But it has not yet covered the configuration design of transmission systems, resulting in a lack of universal expression and generation methods for the configuration of multi-power source fusion hybrid systems in pure electric vehicles. Therefore, to solve the configuration optimization design problem of a dual-motor single-planetary-array power system, an improved general matrix topology design method is proposed to generate all feasible topology structures. And energy consumption, economy, and the dynamic performance of alternative configurations are optimized and simulated through the control strategy based on a dynamic programming algorithm. Under comprehensive testing conditions, 25 alternative options that met the screening criteria were selected, and, ultimately, five optimized configuration options were obtained. Configuration 1 has the best economy, reducing energy consumption by about 6.3%and increasing driving range by about 6.7%. Its 0–100 km/h acceleration time is about 31.4% faster than the reference configuration. In addition, the energy consumption economy during actual driving is almost the same as the theoretical optimal energy consumption economy, with a difference of only 0.3%. The success of this study not only provides an innovative method for optimizing the configuration of dual-motor single-row star train power systems, but also has a positive impact on improving energy utilization efficiency, reducing energy consumption, and improving the overall performance of electric vehicles.

Quantitative techno-economic comparison of a photovoltaic/wind hybrid power system with different energy storage technologies for electrification of three remote areas in Cameroon using Cuckoo search algorithm

This research work presents a techno-economic comparisons and optimal design of a photovoltaic/wind hybrid systems with different energy storage technologies for rural electrification of three different locations in Cameroon. The determination of the optimal, cost-effective, and reliable configuration is performed for the locations of Fotokol, Figuil and Idabato which describe the weather conditions diversity in Cameroon with different solar and wind energy potentials. The sizing-optimisation problem is founded on real data of wind speed and solar radiation, with the principal goal of minimizing the hybrid system net present cost (NPC) while taking into consideration the load deficit probability (LDP) as the reliability constraint. The cuckoo search algorithm with a high convergence rate is utilised to find the optimal combination of the hybrid system with the lowest cost of energy (COE) and NPC which satisfies the LDP of the considered locations. At each location, six different configurations namely photovoltaic/wind/battery, photovoltaic/battery, wind/battery, photovoltaic/wind/fuel-cell, photovoltaic/fuel-cell and wind/fuel-cell are optimised and compared in view of satisfying the heavy, medium and small activities electrical loads demand of non-domestic subscribers. The optimal configuration is obtained for each activity and location in connection with the minimum cost and best reliability. The results revealed that the optimal, cost-effective, and reliable configuration for all activities and locations is a battery-based photovoltaic/wind hybrid system. The results showed that integration of 20 photovoltaic arrays, 1 wind turbine and 27 batteries with LDP value of 0.0486 is the most appropriate configuration which leads to the lowest NPC and COE of 23,024$ and 0.1570 $/kWh, respectively for satisfying the heavy activity load demand at Fotokol. The best hybrid system configuration needed for covering loads demand for medium and small activities at Fotokol were found to be 8 photovoltaic arrays, 1 wind turbine and 19 batteries with LDP, NPC and COE values of 0.0497, 16,640$ and 0.1942 $/kWh, respectively for medium activity; and 5 photovoltaic arrays, 1 wind turbine and 10 batteries with NPC, COE and LDP values of 12,860$, 0.2120 $/kWh and 0.0494, respectively for small activity. The optimisations studies performed at the site of Figuil considering the heavy activity load demand revealed that the cost-effective configuration which leads to the minimum NPC and COE of 28,400$ and 0.1937 $/kWh, respectively consists of 26 photovoltaic panels, 1 wind turbine and 38 batteries with the LDP equal to 0.0499. The obtained results also indicated that substituting the battery banks with a chemical storage which consist of a combination of an electrolyser, hydrogen reservoir and fuel cell is possible, though the cost increases because of the important investment cost of the system constituents. Integrating photovoltaic/wind/fuel-cell at the site of Idabato gives the lowest NPC and COE values of 48,864$ and 0.8056 $/kWh, respectively with a LDP of 0.0491. The optimum sizing of this configuration has 9 photovoltaic arrays, 1 wind turbine and 15 hydrogen tanks.

Efficient Power Management and Control Strategy of Hybrid Renewable Energy System in Microgrid

Currently, the use of renewable energy has gradually increased due to the environmental problems present nowadays. The intermittency of distributed renewable generation poses significant challenges for the operation and integration of microgrids. Unlike the main power grid, where load balancing resources, in general, are abundant, the balancing of generation and load in a microgrid must be done by small gas turbines, diesel generators, or energy storage devices with very limited capacity and at much higher costs. Consequently, the proposed methodology seeks a model for minimizing the Energy Cost (EC) and enhancing the power supply for rural areas by designing and analyzing four different hybrid system configurations based on integrating a biomass system with a photovoltaic (PV), wind turbine (WT) and battery system. To ensure the desired power demand with minimum production cost, the research proposed an energy-efficient Hybrid DC/AC microgrid using four renewable energy sources. Lithium-ion batteries were chosen for this study due to their high energy density, long life cycle, and high efficiency. The existence of both AC and DC microgrids has led to a new concept of hybrid AC/DC microgrids which consists of both AC and DC grids tied by an Interlinking Converter (ILC). It comprises a DC grid and AC grid interlinked by a bidirectional DC/AC converter. Such a hybrid AC/DC microgrid has the advantages of both AC and DC with increased efficiency and less cost. To provide higher voltages, the Multi-Input Booster (MIB) DC-DC converters are used as a power converter in between load and source to enforce and increase the PV depending on the voltage output signal. Further extract maximum power from the solar PV system, perturb and observe algorithm-based power point tracking control mechanism is proposed DC link voltage of ILC is regulated usually by DC side control in load sharing among sources in the DC microgrid. In addition, to overcome the load fluctuation problem in a microgrid, the research introduced a Mamdani type 2 PID-fuzzy controller. Performance index parameters of the transient response characteristics are also improved by using the proposed control approach. The time-domain dynamic responses reveal that the proposed type-II fuzzy PID controller can balance the power generation and demand properly and control both system frequency and tie-line power effectively.

Cost and size optimization of hybrid solar and hydrogen subsystem using HomerPro software

Hybrid Renewable Energy Systems have been considered as a suitable way to supply electricity. The hybrid energy (Solar-Wind-Storage-hydrogen-diesel) is increasingly used in various applications, especially at isolated sites. This study proposes the optimization and analysis of a stand-alone photovoltaic/battery/fuel cell/electrolyzer/hydrogen hybrid system (HS) to find out the optimal sizes and costs. In the first step, SAM software was used to estimate the global solar irradiance (GHI) for the studied area and to select the best PV, battery and fuel cell components. MATLAB software was handled to predict the power output of the renewable source (PV system) using an Artificial Neural Network (ANN) model. Then, simulation, optimization and techno-economic analysis were carried out in the second step with HomerPro software. Four proposed configurations are optimized in this work and different comparisons have been made regarding the found results. The results of the cost optimization were found to be 50861.21 $ and 0.95657 $ for NCP and COE, respectively. Moreover, the same HS configurations are simulated and optimized under Moroccan climate.

Economic Controls Co-Design of Hybrid Microgrids with Tidal/PV Generation and Lithium-Ion/Flow Battery Storage

Due to the uncontrollable generators, islanded microgrids powered only by renewable energy require costly energy storage systems. Energy storage needs are amplified when load and generation are misaligned on hourly, monthly, or seasonal timescales. Diversification of both loads and generation can smooth out such mismatches. However, the ideal type of battery to smooth out remaining generation deficits will depend on the duration(s) that energy is stored. This study presents a controls co-design approach to design an islanded microgrid, showing the benefit of hybridizing tidal and solar generation and hybridizing lithium-ion and flow battery energy storage. The optimization of the microgrid’s levelized cost of energy is initially studied in grid-search slices to understand convexity and smoothness. Then, a particle swarm optimization is proposed and used to study the sensitivity of the hybrid system configuration to variations in component costs. The study highlights the benefits of controls co-design, the need to model premature battery failure, and the importance of using battery cost models that are applicable across orders of magnitude variations in energy storage durations. The results indicate that such a hybrid microgrid would currently produce energy at five times the cost of diesel generation, but flow battery innovations could bring this closer to only twice the cost while using 100% renewable energy.