Levelized Research Articles

Application of hydrogen storage in polygeneration microgrids: Case study of wind microgrid in India

Renewable energy based stand-alone microgrids are highly promising to supply electricity to isolated communities and remote locations. However, both buffer and long-term energy storage are essential due to the highly intermittent nature of renewable sources. By employing hydrogen energy storage with fuel cell and electrolyser in these microgrids, multiple outputs such as electricity, heat, water, and fuel, can be achieved. Design, development and optimization of efficient energy storage system remain a key challenge for the stand-alone microgrid technology. One must ensure that the microgrid satisfies the required electric load but is not over-designed, which is achieved by limiting the two performance parameters i.e., unmet electrical load fraction and excess electricity fraction. The capacities of wind turbine, electrolyser and hydrogen storage are optimized corresponding to the limiting values of unmet electrical load (fUL) and excess electricity (fEX) below 10 %. For the location of Ladakh which has rich availability of wind resource, the optimum size of microgrid is observed to be smallest as WT-20 kW, El-20 kW, H2-15 kg with fUL and fEX as 6.4 % and 8.9 % respectively. The Levelised Cost of Energy (LCOE) is also minimum as 0.89 $/kWh for the location of Ladakh. The distribution of wind resource has significant impact on the size of hydrogen storage. Uniform wind energy with higher velocity round the year reduces the capacity of hydrogen energy storage. Kanyakumari has non-uniform wind resource across different months of the year corresponding to which the capacity of H2 storage is as high as 370 kg.

Techno‐Economic Analysis of Additively‐Manufactured Wind Turbine Blade Tips That Enable Technology Integration

ABSTRACTThe Additively‐Manufactured, System‐Integrated Tip (AMSIT) project is leveraging the flexibility of 3D printing to integrate several technologies in a wind turbine blade tip, while reducing the levelized cost of electricity (LCOE) produced. The design integration is demonstrated for a 200‐kW–scale turbine with 13‐m blades, with the outer 15% of the blade replaced with a 3D‐printed design. Aerodynamic performance is enhanced without increasing swept area through inclusion of a winglet and surface texturing, both challenging for traditional manufacturing. Longevity and durability are improved through integrated lightning and leading edge erosion protection. Increased power, reduced repair frequency, and ease of repair through blade modularity all contribute to reduced LCOE. The analysis is also extended to modern MW‐scale designs to estimate the impact of the technology at scale, demonstrating the potential to reduce LCOE significantly for modern onshore turbines, with even higher potential savings offshore.

Reliability-aware techno-economic assessment of floating solar power systems

Floating solar photovoltaic systems (FPV) have emerged as a promising technology to harness solar energy on water surfaces. With its numerous benefits, including increased land availability, reduced water evaporation, and improved system cooling, FPV systems hold great potential for sustainable energy generation. However, due to its unique installation and operation in water bodies, the management of aging becomes a critical factor to ensure long-term success. Consequently, reliability analysis plays a pivotal role in predicting and mitigating operational risks and estimating the economic feasibility of FPV projects. In this context, this paper presents a reliability-aware techno-economic assessment approach of FPV systems. The approach is tested with a case study in India, and the results are compared with ground-based photovoltaic (GPV) systems. Here, different failure and repair strategies are taken into account to determine the lifetime performance. Results showed that even though FPV system has higher failure rate, considering standard maintenance, the energy generated by the FPV system is 5.38% higher than similar GPV system. The cost of electricity by the PV system depends on the repair and maintenance. For normal maintenance the levelized cost of electricity (LCOE) for FPV system is calculated as 0.0551 $/kWh which is comparable to the LCOE by GPV systems, while for reduced repair actions, the LCOE of the FPV is higher than the LCOE of the GPV system.

Cost-effective and optimal pathways to selecting building microgrid components – The resilient, reliable, and flexible energy system under changing climate conditions

Amidst the changing climate conditions, electricity retailers-led demand response programs and the emergency backup power for possible grid outages are often discussed in isolation, although several underlying linkages exist, which are important for how the existing building stock evolves with the energy transition. This study navigates through the linkages while investigating the levelized cost of electricity (LCOE)-based building microgrid components and undertakes a comparative analysis of energy optimisation models with and without emergency diesel generators. It also examines the building energy system’s resilience, reliability, and flexibility by using OpenStudio and HOMER Grid to develop energy simulation and optimisation models and other probabilistic models for a chosen building archetype in Sydney, Australia. This study finds that excluding the emergency diesel generator will require a larger battery storage system, increasing LCOE from A$0.17/kWh to A$0.20/kWh across climate scenarios. However, the larger battery storage system increases the probability of surviving outages (> 4 h) by around 10 % across climate scenarios. The LCOE increases up to 45 % for outages up to 8 h across climate scenarios and up to 85 % for outages up to 12 h. Additionally, for the building archetype, the probability of grid purchase (below the current average) is 0.78 in 2030, which drops to 0.55 in 2050. The probability of grid sales (above the current average) also drops from 0.69 to 0.46. Thus, while the narratives around the building energy system’s flexibility overstate the electricity exchange between the building and the grid, this study finds that increasing the on-site production utilisation rate and larger battery throughput contributes to demand response application and flexibility.

Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm

The study addresses the integration of hybrid hydrogen (H2) and battery (BT) energy storage systems into a renewable energy microgrid comprising solar photovoltaic (PV) and wind turbine (WT) systems. The research problem focuses on improving the effectiveness and computational efficiency of energy management systems (EMS) while ensuring high system reliability. Despite the existing optimization methods for hybrid microgrids, challenges remain in optimizing energy storage and capacity planning in grid-connected microgrids. To solve this, we propose the use of the Levy Flight Algorithm (LFA) to optimize the capacities of PV, WT, H2 tanks, electrolyzers (EL), fuel cells (FC), and BT, which presents a complex nonlinear optimization challenge. The novelty of this study lies in integrating the LFA with a rule-based EMS, enhancing system reliability and efficiency. The proposed approach significantly reduces the annualized system cost (ASC) and the levelized cost of energy (LCOE). The result demonstrate that the LFA outperforms methods like the Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Genetic Algorithm (GA), yielding cost savings of $3,309, $5,297, $4,484, and $5,129 respectively. The LFA achieves the lowest LCOE at $0.275/kWh, compared to $0.278/kWh with SSA, $0.289/kWh with GA, $0.280/kWh with PSO and $0.283/kWh with GWO. This research contributes to the broader scientific community by providing a more efficient approach to optimizing renewable energy microgrids with hybrid storage systems, thus promoting eco-friendly and cost-effective energy solutions. The proposed system design offers a pathway to future energy systems with high renewable integration, especially as technology advances and costs continue to decrease.

Underpinnings of reservoir and techno-economic analysis for Himalayan and Son-Narmada-Tapti geothermal sites of India

The high capital cost and risks associated with the extraction process of geothermal energy are key factors in the project economics. This paper presents a comprehensive technoeconomic study based on reservoir heat and flow simulations along with the levelized cost of energy (LCOE) for two geothermal sites (Himalayan and Son-Narmada-Tapti i.e. SONATA) in India.Dual porosity reservoir simulation models were constructed and were used to obtain the cumulative and the dynamic thermal energy potentials of these sites. The simulation studies suggest that both sites are equally potent for geothermal energy extraction. Comparatively, the proven cumulative energy potentials for the Himalayan and SONATA sites are found to be 4.92–5.10 and 3.62–3.7 TW h, respectively, for the 30 years of production at a rate of 92 kg/s. This difference can be attributed mainly to higher temperatures and deeper sites at the Himalayan Province. Sensitivity analyses were conducted to assess the impact of various parameters, including porosity, permeability, fracture spacing, and thermal conductivity. The results suggest that porosity and permeability are the key enablers of efficient energy production. The economic feasibility study suggests that the LCOE costs are high for these sites ($148/MWh for the Himalayan and $137/MWh for the SONATA). These two sites have CO2 mitigation potential in the range of 3.12 and 11.36 Megatons from a single doublet well configuration considering the CO2 emissions from conventional coal-fired thermal power plants. Overall, SONATA can be the better prospect considering the logistics and operational challenges along with reservoir heat potential.

Assessing the energy system's greenhouse emissions via the health of Smart Territories and Cities

The aim of this paper is to understand how the main drivers of air pollution and greenhouse emissions impact public health in a Smart Territory — meaning a technologically integrated city or neighborhood — as well as how to design an optimized energy system model beyond only data by including the holistic experience of its people through phenomenology and ethics. We understand that a Territory and a City is a complex system where mathematical tool modeling known as Design of Experiment (DOE) and its optimization solutions are required to establish causality and identify the variables that have a broader impact on public health so that mortality rates due to air pollution are reduced. DOE's statistical branch is a novel methodology when applied to energy systems and the design of Smart Territories and Cities. Because of it, we have been able to demonstrate how energy emissions, capacity and Levelized Cost of Energy (LCOE) affect the mortality rate and create the foundations for building fully decarbonised energy systems enhanced by mathematical solutions. However, the Cartesian approach of extrapolating from models which align themselves with economic growth alone will not solve the energy dilemma. In fact, the current energy transition project is based on outdated archetypes that lead to scary futures. To course-correct the problematic energy model of a Smart Territory, phenomenologists and creative imagination need to be cultivated and put into action together with mathematical modeling, leading to vectors of positive change and adaptation. Only then might the energy models designed to be reproducible could became ethically virtuous and therefore accepted by the Territory's co-dwellers within the chain of causalities.

Comprehensive Analysis of 100 MW Wind Farm Losses and Their Financial Impacts: A Study on Array Losses Across Multiple Turbines Using a RETScreen Expert Software

Abstract This study aimed to analyze and evaluate the influence of array losses on the financial sustainability and economic viability of wind farm projects with a capacity of 100 MW. The Al-Fajer site has been proposed for a feasibility study to assess the viability of building an onshore wind farm. The assessment of investment costs was conducted using the RETScreen program. The findings demonstrated that alterations in array losses impact the amount of energy exported to the grid, influencing changes in revenue, pre-tax internal rate of return (IRR), and net present value (NPV). When array losses in (case 1) decrease by 2%, that will positively impact financial feasibility factors. Therefore, it will lead to a gain in income for all turbines; the net present value (NPV) and pre-tax internal rate of return (IRR) values experienced an increase, indicating a positive impact on the project’s profitability. When array losses in (case 2) increase by 2%, it will lead to negative results on the wind farm and, thus, reduce the energy exported to the grid; wind turbine revenue will experience a decline. This increase substantially affects the NPV and IRR, leading to decreases. The capacity factor experienced a drop, resulting in significant changes to the project’s financial returns. The levelized cost of energy (LCOE) has increased due to decreased production, leading to higher prices. The simple payback likewise experienced a boost beyond its usual norms.

Unlocking development of green hydrogen production through techno-economic assessment of wind energy by considering wind resource variability: A case study

Generating hydrogen from renewable energy sources is widely recognized as an effective strategy for addressing critical challenges in the energy sector while contributing to the reduction of greenhouse gas emissions. This study aims to assess the wind energy potential for electricity and hydrogen production in five locations on Sumba Island using 10 years (2011–2020) of data from the NASA's POWER Project. A wind variability assessment was performed on five wind turbines ranging from 500 kW to 1.5 MW and using electrolysis technology. The results indicated a hydrogen production potential of 25–57 tons per year. Economic analysis of hydrogen production for Haharu reveals an attractive internal rate of return (IRR) of 43% with a payback period (PBP) of 2.25 years and a net present value (NPV) of 1.3 MM USD, the levelized cost of electricity (LCOE) of 0.0241 USD/kWh, and the levelized cost of Hydrogen (LCOH) of 1.01 USD/kg. Sensitivity analysis underscores the critical influence of investment and revenue on project profitability, highlighting their substantial impact on determining a project's success or failure. These findings emphasize the potential of Sumba Island as a hub for sustainable energy production to meet the growing demand for clean and renewable energy sources.

Towards decarbonizing large-scale industries: A decision support framework for optimizing grid-connected PV-battery energy systems planning – Case study of an OCP mining site, Morocco, North Africa

Incorporating renewable energy into forthcoming grid-connected or decentralized energy systems assumes an escalating significance and can potentially enhance endeavors toward accomplishing Sustainable Development Goal 7 (SDG7). Nevertheless, deploying sustainable renewable energy-intensive systems may present challenges related to their intermittency and cost instability. This paper proposes the development of a decision support model aimed at planning an optimal on-grid PV battery system. The model builds upon the Open Energy Modeling Framework (OEMOF) and defines asset capacities, energy dispatch, operational strategies, and optimal costs for the designated system. Key factors considered include energy demand profile, photovoltaic potential, electricity tariffs, and the availability of the National Grid. Furthermore, the model evaluation incorporates the computation of pertinent performance, feasibility, and viability indicators, notably the Levelized Cost of Energy (LCOE). To validate the framework, the article conducts a case study to determine the optimal sizing and planning of a grid-connected PV battery energy system. The objective is to cater to the electricity needs of an OCP (Office Chérifien des Phosphates) mining site in Morocco. The study considers the characteristics of the national power grid, incorporating time-varying electricity tariffs based on a Demand-Response program taking into account various rates according to the time of use (ToU). The case study includes a sensitivity analysis that examines different factors, namely the proportion of renewable energy, the investment costs of photovoltaic systems and batteries, and the financial parameter known as the weighted average cost of capital (WACC). Through this analysis, the study assesses the impact of these variables on the calculated cost of energy. Experimental results revealed a range of LCOE values from $0.07111/kWh to $0.11847/kWh for high renewable energies integration.

Energy and exergy analysis of photovoltaic systems integrated with pulsating heat pipe and hybrid nanofluids

Solar energy is harnessed from solar radiation and converted into various forms of energy, primarily electricity. It is a crucial part of the renewable energy landscape due to its abundance, sustainability, and potential to reduce greenhouse gas emissions. Photovoltaic (PV) panels have become a critical component in the transition toward sustainable energy; however, the efficiency and longevity of PV systems are significantly influenced by their operating temperature. Excessive heat can reduce the efficiency of PV cells and accelerate material degradation. Pulsating heat pipes (PHPs), with their excellent thermal management capabilities, present a promising solution to these challenges. This paper comprehensively investigates the effect of incorporating a three-dimensional PHP into PV systems, using working fluids with varying thermal properties, namely water, graphene oxide (GO) nanofluid with three different concentrations (0.2, 0.4, and 0.8 g/L) and their mixture with nano-encapsulated phase change material (Nano PCM), forming a hybrid nanofluid, at a concentration of 5 g/L. The collected data are analyzed from energy and exergy perspectives. The findings show that using Nano PCM in the nanofluid-based PV system (at the highest concentration) produces 22.3 Wh/day, increasing the system’s electrical power output by approximately 12 % compared to a PV panel with no cooling system. It outperforms the other systems studied, with the highest overall exergy efficiency of 35.4 %. The results also indicate an average improvement in first-law efficiency. Additionally, the study shows varying levelized costs of energy (LCOE) for the system cooled with different coolants.

Annual relative performance degradation in photovoltaic solar plants

This study aims to assess annual relative performance degradation σ to be used in the computations of the Levelised Cost of Energy (LCOE) of new plants based on the standard year for weather and solar resource. The assessment is based on the experimental data of power generation, weather, and resource for different years, and simulations of power generation by using the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) software. The raw data of power generation for 53 different plants spanning about one decade show a σ assessed at less than 0.29%. This makes it reasonable to assume in SAM σ=0% to σ=0.29%. This is less than the default σ=0.5% currently used in SAM based on limited outdated data. The updated performance degradation factor diminished to σ=0-0.29% reduces the computed LCOE for typical new projects in the United States from 2.86 to 2.74-2.80 ¢/kWh. Correction of the σ trends for interannual variability of weather and resource is unnecessary, providing enough years of operation are covered, given the inaccuracies in the model and the supporting data, the mitigation by management of the performance changes, and the complex phenomena correlated to the change of weather and irradiance affecting the power output in different directions. The reduced σ is the result of a significant product improvement over the last decades, especially for large power plants, compared to the plant which provided data for the prior correlation of performance degradation, and much better management and maintenance of the plants.

A multi-stage stochastic programming model for multi-mission selective maintenance optimization

This research introduces a novel selective maintenance model in the case of systems undergoing multiple consecutive missions. The model considers uncertainties related to future operating conditions during each mission. Within each maintenance break, various optional actions ranging from replacements which are perfect to imperfect and also minimal repairs can be chosen for individual components. Evaluating the probabilities of successful future mission accounts for uncertainties associated with component operational conditions. The selective maintenance problem is formulated as a nonlinear mixed-integer model for optimization, and computational challenges are addressed using the progressive hedging algorithm. Numerical examples validate the new proposed model and illustrate the benefits of the model by estimating a more realistic reliability level and lower maintenance cost.

Design, multi-aspect investigation and economic advantages of an innovative CCHP system using geothermal energy, CO2 recovery using a cryogenic process, and methanation process with zero CO2 footprint

The significance of devoting attention to environmental pollution control strategies is widely recognized as an effective means of mitigating the harmful environmental effects caused by fossil fuels in industrial and power plant sectors. Carbon dioxide (CO2) capture and recovery technologies have opened up the possibility of utilizing this pollutant gas. Hence, the current study suggests a methodology for the CO2 hydrogenation of the flue gas leaving a power plant. This approach facilitates methane generation via a methanation reactor, subsequently is utilized as fuel for a power plant. For this purpose, a cryogenic method using liquefied natural gas cold energy facilitates CO2 recovery. Moreover, the whole system utilizes geothermal energy to launch a power plant for power generation and supply the power demands of a hydrogen production unit, relying on a water electrolysis process. The hydrogen generated is employed for CO2 hydrogenation, while the oxygen produced is utilized for the combustion reaction. Heating provider units and an absorption chiller are also included in the design. The system is modeled utilizing Aspen HYSYS software. This study incorporates a sensitivity analysis alongside energy, exergy, environmental, and economic assessments. The energy and exergy efficiencies, as determined by the thermodynamic analysis, are 30.87% and 48.61%, respectively. Additionally, according to the economic study, the levelized energy cost amounts to 16.65 $/MWh, demonstrating a substantial reduction of 87.6% compared to the power generation mode. One notable merit of the suggested system lies in its zero CO2 footprint framework, showing a noteworthy supremacy when compared with previous studies.

Optimization of Solar PV System Efficiency in Bangladesh

This paper presents a comprehensive review and analysis of Sarishabari Engreen Solar Plant Ltd., a 3.3 MW grid-connected solar photovoltaic (PV) system located in Sarishabari, Jamalpur, Bangladesh. The study evaluates the plant's economic and operational performance, revealing a competitive payback period of 10.1 years and a levelized cost of energy (LCOE) of 0.11 USD/kWh. These metrics highlight the plant's financial viability, largely due to the low cost of public land used for construction. However, profitability may be challenged if similar projects require significant investments in private land acquisition. Key areas for improvement identified include optimizing the tilt angle and integrating smart automation systems. Additionally, the potential for hybrid renewable energy systems combining solar and wind power is discussed. The paper also provides actionable recommendations for future renewable projects, emphasizing the importance of advanced technologies, and supportive policies. These insights aim to inform the optimization of existing solar PV systems and guide the development of future renewable energy projects in Bangladesh, contributing to the country's sustainable energy goals.

Comparative Analysis of Hybrid Geothermal-Solar Systems and Solar PV with Battery Storage: Site Suitability, Emissions, and Economic Performance

Renewable energy integration has become a critical focus in the global effort to reduce carbon emissions and diversify energy sources. In regions with distinct geographic features, such as Türkiye, combining different renewable technologies can offer enhanced energy security. This study investigates the site suitability and economic and environmental performance of hybrid geothermal-solar systems and solar PV systems with battery storage across the provinces of Osmaniye, Hatay, and Kilis, of Türkiye. Using the fuzzy-AHP method, site suitability is evaluated, addressing a key gap in comparing these systems' adaptability to varying geographic conditions. This study is the first to directly compare these two renewable energy technologies in terms of site suitability. The findings reveal significant differences in site suitability, with solar PV systems with battery storage demonstrating broader applicability across the region. The suitable sites (20-100% suitability) cover 1260.82 km² for solar PV systems with battery storage and only 122.18 km² for hybrid geothermal-solar systems. In terms of environmental impact, hybrid geothermal-solar systems exhibit significantly lower carbon emissions, averaging 44.6 kg CO₂/MWh, compared to 123.8 kg CO₂/MWh for solar PV systems with battery storage. Economically, hybrid geothermal-solar systems also outperform with a lower levelized cost of electricity of $0.091/kWh versus $0.254/kWh for solar PV systems. These results highlight the environmental and economic advantages of hybrid geothermal-solar systems, while also emphasizing their limited scalability to regions with geothermal activity. Conversely, solar PV systems, despite their higher emissions and costs, offer greater flexibility and potential for widespread deployment.

Techno-economic and environmental assessment of green hydrogen and ammonia production from solar and wind energy in the republic of Djibouti: A geospatial modeling approach

This study conducts a thorough economic and technical analysis to assess the viability of green hydrogen and green ammonia production using renewable energy sources in the Republic of Djibouti. We explore the economic competitiveness of utilizing wind and solar power for sustainable energy production through various measures including levelized cost of energy (LCOE), hydrogen (LCOH), and ammonia (LCOA). Our analysis incorporates sensitivity assessments and Monte Carlo simulations to predict financial feasibility and environmental impact, focusing on CO2 emission reductions. A cost mapping of electricity, green hydrogen, and green ammonia from solar and wind resources was created to find Djibouti's most cost-effective production sites. The feasibility of exporting green ammonia to neighboring countries with high fertilizer demand was also evaluated using rail and truck transport scenarios. Key findings demonstrate that Moulouhlé, endowed with robust wind and solar resources, presents a strategic site for deploying renewable energy technologies. Wind energy, with a lower LCOE of 0.066 $/kWh compared to solar's 0.093 $/kWh, emerges as a more cost-effective solution for both hydrogen and ammonia production. Notably, wind-powered hydrogen production costs are 2.25 $/kgH2, significantly lower than solar-powered costs at 4.17 $/kgH2. In terms of green ammonia, wind power achieves production costs of 399.76 $/tonNH3, outperforming solar power which stands at 537.11 $/tonNH3. Additionally, our study evaluates the logistics of exporting green ammonia, determining rail transport as a more economically viable option than trucking. This research not only underscores Djibouti's potential as a leader in green energy exportation but also aligns with global decarbonization efforts, showcasing significant CO2 savings—154.94 Mt annually from wind. This work emphasizes the importance of strategic resource utilization in Djibouti, offering insights critical for stakeholders in making informed decisions about investing in renewable energy infrastructures. The outcomes suggest a promising future for regional energy sustainability and economic resilience, fostering a transition towards low-carbon energy systems.

A Review of Numerical Methodologies for Predicting Rotating Stall and Surge in High-Speed Centrifugal Compressors

Abstract High-speed supersonic radial compressors are a critical enabling technology for meeting the requirements of future aviation- propulsion and thermal-management systems. These turbomachines must be designed to be both efficient and robust on the widest possible operating range. Flow instabilities in the form of rotating stall and surge are therefore phenomena that must be accurately predicted early in the design process. Unsteady full-annulus computational fluid dynamics can be used to get accurate information about the onset of instabilities, but at the expense of costly simulations. As a result, the design of new compressors continues to rely on existing correlations for the prediction of the critical mass flow rate. This approach, however, leads to sub-optimal compressor designs. This article provides a review of the numerical methodologies that can be used for the accurate prediction of the critical mass flow rate in high-speed centrifugal compressors. Methods of different fidelity level and computational cost are described. Two particularly promising models, namely those proposed by Spakovszky and Sun, are subsequently examined in more detail. Exemplary applications of these two models are finally discussed.

Carbon footprint of solar based mini-grids in Africa: Drivers and levers for reduction

The massive development of mini-grids (MGs) is seen as a promising alternative to the extension of national grids to achieve universal access to electricity. MGs based on solar photovoltaic are often recognized fully consistent with net-zero CO2 emissions objectives. However, if they have low or even no direct emissions from diesel consumption, they embed indirect carbon emissions due to solar panels and batteries manufacturing. Electrification policies, mainly based on the levelized costs of electricity (LCOE), should likely account for the carbon footprints (CFP) of possible electrification strategies.In this work, we assess the CFP of hybrid MGs (solar, battery, diesel) for rural electrification in Africa. We consider a large number of MG configurations for many locations across the continent. For each location, we identify the lowest CFP and LCOE, and estimate their dependency to meteorological and socio-economic factors.Our results show that: (i) the lowest CFP depends on location and is around 200gCO2/kWh; (ii) it can be higher than the CFP of certain African national grids; (iii) the CFP of hybrid MGs can be lower than the CFP of MGs relying only on solar PV; (iv) for most techno-economic and environmental assumptions, moderate LCOE increases allow significant CFP reductions.

Characterisation and simulated evaluation of electricity management strategies for Prosumers, Prosumagers, and other end-users

ABSTRACT Distributed photovoltaic generation has been raised as a dependable electricity substitute for implementing a decarbonised energy transition. The dynamics of PV systems with battery storage have led to new electricity end-user classifications that select their electricity systems and resources wisely, i.e. Prosumers and Prosumagers. This work presents a technical and economic assessment to analyse the effect of decision-making independent end-users and electricity management strategies through a novel time-discrete deterministic simulation model. The end-user's choice of battery storage technology and their approach to electricity management emerge as pivotal factors influencing their strategic decisions. Adopting a prosumer strategy, such as storing and selling surplus self-production, reduces the Levelized Cost of Energy (LCOE), benefiting the end-user economically. Notably, the most effective battery storage technology may only sometimes be the one that is most readily available in the market. These findings enhance our understanding of novel end-user types and underscore the practical implications of their evolutionary shift towards independence.