Array Sizing Research Articles

New Sizing Methodology and Efficiency Analysis of Satellite’s Electrical Power Subsystem

This paper describes a novel methodology to improve the preliminary design and efficiency analysis of the satellite’s electrical power subsystem. Several studies have addressed this issue by proposing a solar array sizing method based on the use of fixed efficiency paths during sunlight and eclipse periods. Indeed, these studies restrict the use of the battery for eclipse periods, and thus the solar array is sized to support the peak power loads on its own. To the authors’ knowledge, no one has so far deeply and jointly analyzed the influence of the power profile demand, the use of the battery during sunlight periods, and the architecture on the efficiency paths to size the electrical power subsystem. This work offers a methodology that takes into account these variables to better estimate the global efficiency of the electrical power subsystem and, consequently, to refine the first design iterations of a satellite. This methodology is particularized for the most common architectures based on power and voltage bus regulation, although it can be implemented in more complex architectures. A case study involving a real space mission, the UPMSat-2 (a 50 kg satellite launched in September 2020), is conducted to test this methodology.

A parametric design approach for multi-lobed hybrid airships

AbstractIn recent years, there has been an increasing interest in the research and development of hybrid airships for various applications. Airship design involves multiple design parameters from various disciplines that interact mutually. Existing design methodologies, however, are often limited to fixed shapes and geometry. This paper provides a comprehensive parametric design approach for the sizing of multi-lobed hybrid air vehicles for low- and high-altitude applications. The proposed design techniques are robust so that the designer has the freedom to change the number of lobes, the relative location of lobes, the envelope profile, and the optimiser for the design optimisation process. The outcomes of the proposed methodology are envelope volume, wetted surface area, length and span of the envelope, sizing and layout of the solar array, and sizing and layout of the fins. The modeling techniques highlighted in this paper are very efficient for the design and optimisation of multi-lobed airships in the conceptual design phase with a large design exploration space. The robustness of the shape generation algorithms is tested on some of the standard envelope profiles of airships. The effect of the shape and geometry of the multi-lobed envelope on added mass is demonstrated through the added mass estimation using Boundary Element Method.

Sizing of Rooftop PV Array and Community-Run Battery Storage for an Energy Cooperative in Prosumer Cluster

A standalone system can address the problem of uncovered electricity from the grid. The cost of energy storage for installing renewable energy systems is one of the issues of such a system. This paper introduces and investigates the optimal capacity of a novel energy cooperative system with prosumer clusters and a community battery bank as typical energy storage. The system’s function is formulated to minimize the investor’s annual expenditure. The proposed energy cooperative system uses actual annual solar insolation data and the electric load demand of houses in the optimization process. The model, as mentioned above, is applied to two system configurations – energy cooperative without and with Prosumer to Prosumer (P2P) energy sharing. The reliability factor Loss of Power Supply Probability (LPSP) from the Cooperative Energy Sharing algorithm is taken as a constraint in the formulation. The comparison of the two configurations brings out the importance of P2P energy sharing in a standalone Energy Cooperative system. Particle Swarm Optimization (PSO) algorithm is used to achieve this optimization. The PSO results show that the proposed Energy Cooperative configurations are promising to facilitate the system’s reliability.

8. Optical genome mapping analysis of FMR1 expansions in fragile X syndrome

Fragile X syndrome (FXS) is associated with cognitive impairment and intellectual disability. Nearly all cases of FXS are associated with an expansion of a CGG triplet repeat in the FMR1 gene. Phenotype severity is often correlated with the expansion size; thus, accurate sizing of the CCG repeat array is crucial. The repetitive nature of these regions presents difficulties: 1. PCR is unable to traverse through long repeats; 2. sequencing has limited read lengths; 3. Southern blot may be inaccurate, time consuming, and expensive. Optical genome mapping (OGM) has the potential to address some of these shortcomings. OGM utilizes images of ultra-long DNA molecules, labeled at specific sequence motifs linearized in nanochannel arrays and can be used for structural and copy number variation calling and absence of heterozygosity analysis. Bionano Genomics has developed a targeted analysis workflow for analysis of FMR1. To evaluate the capability of measuring repeat arrays consistent with normal (<45 repeats), premutation (55-200 repeats), and full mutation (>200 repeats), we analyzed the FMR1 repeats in 75 samples. We also analyzed the repeat region on 20 phenotypically normal control subjects. We observed alleles consistent with annotation across the entire range of repeat counts. Analytical sensitivity was measured at 97% with 100% PPV for expansions >200 repeats. The largest expansion we detected was ∼1000 repeats. In the control samples, we measured repeat counts below the full mutation cutoff in all cases. Repeatability studies were carried out to show analytical consistency and to establish minimum molecule quality requirements. EnFocus™ analysis report provides pass/fail for QC metrics for input data quality as well as analytic measurement quality using internal control regions of the genome on each autosome. OGM performance for FMR1 repeat lengths analyzed here show a much higher dynamic range compared to PCR and higher precision compared to Southern blot.

EP391: Optical genome mapping for constitutional postnatal SV, CNV, and repeat array sizing: A multi-site clinical study

Chromosomal aberrations that include structural variations (SVs), copy number variations (CNVs), and tandem repeat expansions/contractions are major causes of human genetic disorders. Current cytogenetic methods that are routinely employed for the detection of SVs and CNVs are low resolution (karyotype), targeted and require prior knowledge (FISH), or cannot detect balanced SVs and orientation of duplicated segments of genome (chromosomal microarrays). Repeat array analysis methods are time-consuming and have low accuracy (southern blotting) or low dynamic range (PCR, NGS).

Dynamic Modeling of an Optimal Hybrid Power System for a Captive Power Plant in Pakistan

This paper presents the optimized design, economic feasibility and dynamic modeling of a grid-tied captive hybrid renewable energy power plant for a Pakistani industrial area. Since the proposed plant, encompasses a photovoltaic (PV) array - as its main component - and for an efficient and reliable operation many issues - including industrial load variations and expected dynamics - should be investigated before its implementation. In this context, Homer Pro software is utilized in the design and economic optimized sizing of the PV array, and the PVWatts is used in land requirement analysis. The designed grid-tied plant is modeled in the MATLAB/Simulink using Simscape blocksets to investigate the plant’s dynamic behavior due to typical practical disturbances. The obtained results reveal that the plant has a low per-unit energy cost and provides significant savings. Results of dynamic simulation show that the plant can respond to the ramp-up and ramp-down load variations in industrial settings. Moreover, the plant has a fast response to step changes in irradiance; proving that the proposed plant is reliable and suitable candidate for fulfilling the designated load.

Designing photovoltaic arrays for groundwater pumping for remote agriculture using synthetically generated daily rainfall and irrigation needs

PurposeThis study aims to provide a new method for precisely sizing photovoltaic (PV) arrays for standalone, direct pumping PV Water Pumping (PVWP) systems for irrigation purposes.Design/methodology/approachThe method uses historical weather data and considers daily variability in regional temperatures and rainfall, crop evapotranspiration rates and seasonality effects, all within a nonparametric bootstrapping approach to synthetically generate daily rainfall and crop irrigation needs. These needs define the required daily supply of pumped water to achieve a user-specified level of reliability, which provides the input to an intuitive approach for PV array sizing. An economic comparison of the costs for the PVWP versus a comparably powered diesel generator system is provided.FindingsPumping 22.8646 m³/day of water would meet the pasture crop irrigation needs on a one-acre (4046.78 m²) tract of land in South Florida, with 99.9% reliability. Given the specified assumptions, an 8.4834 m² PV array, having a peak power of 1.1877 (kW), could provide the 1.2347 (kWh/day) of hydraulic energy needed to supply this volume over a total head of 20 meters. The PVWP system is the low-cost option when diesel prices are above $0.90/liter and total installed PV array costs are fixed at $2.00/Watt peak power or total installed PV array costs are below $1.50/Watt peak power and diesel prices are fixed at $0.65/liter.Originality/valueBecause the approach is not dependent on the shapes of the sampling distributions for regional climate factors and can be adapted to consider different types of crops, it is highly portable and applicable for precisely determining array sizes for standalone, direct pumping PVWP systems for irrigating diverse crop types in diverse regions.

Output power computation and sizing of a photovoltaic array by advanced modeling

The precise design of a photovoltaic (PV) array is best achieved by considering all types of physical real losses in the computation of output power. In this paper, the losses of PV equivalent circuit have been evaluated leading to ideal single diode (ISD), simplified single diode, single diode, simplified two-diode, and two-diode (TD) PV models. These models were compared with the 6th, 7th, 8th, and 9th PV models. The impact of PV modeling has been investigated using Ant Lion optimization on an on-grid PV array in Marsaa', Jordan using measured data. It is found that the TD model results in an optimal value of 99.9% of the index of reliability with 38,070 PV panels. Moreover, examining the system with other PV models, such as the ISD model, decreases the number of PV panels by 23.52%. Further, adapting the TD model reduces the system emissions by 10.15% compared with the ISD model. Also, sensitivity analysis, on the measured data, is tested to validate the robustness of the system. In sum, the investigation revealed that even the TD model has the lowest output power, it is more realistic because it considers all circuit losses (i.e. diffusion, recombination, internal series, and leakage losses).

Realistic coordination and sizing of a solar array combined with pumped hydro storage system

This paper presents a realistic coordination and sizing of a photovoltaic (PV) plant connected with pumped-hydro storage (PHS) system at King Talal dam (KTD), Jordan. KTD is proposed to serve as the upper reservoir of the PHS. Two scenarios are investigated. First, both recombination loss in the two-diodes PV power and effective head loss in the PHS plant are not considered. Second, those two losses are considered, so the output power of the system's components is accurately modelled. Data of system demand, air temperature, water flow rate and solar irradiance are collected from different formal institutions in Jordan. This paper employs particle swarm optimization to find the optimal value of the index of reliability (IR). Results show that the optimal values of the IR are 99.67% and 99.90% for the first and second scenarios, respectively. The required number of PV panels (NPV) and the volume of the lower reservoir (VLR) are 44,063 panels and 69.348 M.m3, respectively. In the second scenario, these decision variables are decreased by 14.33% and 5.39%. Uncertainty analysis, on the measured inputs, is performed to assess the system's effectiveness. The proposed methodology is recommended anywhere to get reliable renewable systems with true-sizes and realistic performance.

Efficient economic optimisation of large-scale tidal stream arrays

As the tidal energy industry moves from demonstrator arrays comprising just a few turbines to large-scale arrays made up of potentially hundreds of turbines, there is a need to optimise both the number of turbines and their spatial distribution in order to minimise cost of energy. Optimising array design manually may be feasible for small arrays, but becomes an impractically large approach when the number of devices is high, especially if taking into account both the cost effectiveness of each turbine and also the coupled nature of the turbine locations and the local as well as far-field hydrodynamics.Previous work has largely focused on producing computational tools to automatically design the size and layout of large-scale tidal turbine arrays to optimise power. There has been some limited preliminary work to incorporate costs into these models, in order to improve the economic viability of tidal arrays. This paper provides the first in depth implementation and analysis of economic functionals, based upon metrics such as break even power and levelised cost of energy, used for design of explicit array sizing and spatial variation.The addition of these new economic functionals introduces complexity by increasing the number of inputs to the model, each of which are subject to their own uncertainty in value. For this reason, sensitivity analysis becomes both more important as well as more difficult to undertake. This paper presents a novel rapid methodology for deriving the optimal array design (number of turbines and their spatial distribution throughout the farm area) to minimise cost functionals, and its sensitivity to variations in the economic inputs. Importantly, the new aspects of this method introduced here do not rely on repeated model runs and iterative optimisation, two aspects that typically prove to be impractically expensive computationally. This more readily allows for the impact of changes in investor priorities to be investigated. It is also shown that, while the optimal solution varies greatly with uncertainty in the input parameters, this uncertainty is reduced significantly through Monte Carlo analysis.

PV array and inverter optimum sizing for grid-connected photovoltaic power plants using optimization design

This paper aims to select the optimum inverter size for large-scale PV power plants grid-connected based on the optimum combination between PV array and inverter, among several possible combinations. Inverters used in this proposed methodology have high-efficiency conversion in the range of 98.5% which is largely used in real large-scale PV power plants to increase the financial benefits by injecting maximum energy into the grid. To investigate the PV array-inverter sizing ratio, many PV power plants rated power are considered. The proposed method is based on the modelling of several parts of the PV power plant taking into account many design variables and constraints. The objective function is the levelized cost of energy (LCOE) and the optimization is performed by a multi-verse algorithm. The optimization method results in an optimum inverter size that depends on the PV plant rated capacity by providing an optimum number of inverters required in the installation site. The optimum sizing ratio (Rs) between PV array and inverter were found equal to 0.928, 0.904, and 0.871 for 1 MW, 1.5 MW, and more than 2 MW, respectively, whereas the total power losses reached 8% of the total energy generation during the PV power plant operational lifetime.

High Level Synthesis Optimizations of Road Lane Detection Development on Zynq-7000

In this work, we proposed High-Level Synthesis (HLS) optimization processes to improve the speed and the resource usage of complex algorithms, especially nested-loop. The proposed HLS optimization processes are divided into four steps: array sizing is performed to decrease the resource usage on Programmable Logic (PL) part, loop analysis is performed to determine which loop must be loop unrolling or loop pipelining, array partitioning is performed to resolve the bottleneck of loop unrolling and loop pipelining, and HLS interface is performed to select the best block level and port level interface for array argument of RTL design. A case study road lane detection was analyzed and applied with suitable optimization techniques to implement on the Xilinx Zynq-7000 family (Zybo ZC7010-1) which was a low-cost FPGA. From the experimental results, our proposed method reaches 6.66 times faster than the primitive method at clock frequency 100 MHz or about 6 FPS. Although the proposed methods cannot reach the standard real-time (25 FPS), they can instruct HLS developers for speed increasing and resource decreasing on an FPGA.

On the Impacts of PV Array Sizing on the Inverter Reliability and Lifetime

To enable a more wide scale utilization of photovoltaic (PV) systems, the cost of PV energy should be comparable to or even lower than other energy sources. Due to the relatively low cost of PV modules, oversizing PV arrays becomes a common approach to reduce the cost of PV energy in practice. By doing so, the total energy yield can be increased under weak solar irradiance conditions. However, oversizing the PV array will increase the loading of PV inverters, which may have undesired influence on the PV inverter reliability and lifetime. In that case, it may result in a negative impact on the overall PV energy cost, due to the increased maintenance for the PV inverters. With the above concern, this paper evaluates the reliability and lifetime of PV inverters considering the PV array sizing. The evaluation is based on the mission profile of the installation sites in Denmark and Arizona, where the reliability-critical components such as power devices and capacitors are considered. The results reveal that the variation in the PV array sizing can considerably deviate the reliability performance and lifetime expectation of PV inverters, especially for those installed in Denmark, where the average solar irradiance level is relatively low. In that case, a certain design margin in term of reliability is required to ensure high-reliable operation of PV inverters.

Sizing of PV array in a DC nano-grid for isolated households after alteration in time of consumption

DC Nano-grids are increasingly employed in rural areas to create net zero energy homes. This paper evolves a simple approach for commoners and a rigorous analytical approach for experts, for designing a DC Nano-grid. The first method directly obtains the size of the PV panels based on highest monthly average consumption in a year, irradiation and ambient temperature. The second method uses particle swarm optimization (PSO) technique and it is based on a detailed cost equation with all design variables. In both the methods, sizing of PV array is attempted after an appropriate time shifting of loads. It has been established that such alteration of the time of consumption brings down the cost of storage system. The complete procedure for the optimal sizing of DC Nano-grid system by both the methods has been demonstrated for a locality in India. It has been established that sizing of the PV array using intuitive method is adequate for designing a DC Nano-grid in a rural area.

Optimum sizing and performance modeling of Solar Photovoltaic (SPV) water pumps for different climatic conditions

Abstract In this study, effect of irradiance and temperature variations on water output of Solar Photovoltaic (SPV) water pumps has been analyzed. A methodology has been proposed for the performance optimization of SPV pumps based on height of water table and operating point of the pump using most frequent conditions (MFC) of a site. The selection of optimum array sizing for a pump has been done based on the occurrence of desirable input power and subsystem efficiency at MFC. The effect of different array configurations on the performance of water pump using PVsyst software has also been studied. Most of pumps studied, are operating in the average subsystem efficiency range of 40–50%. AC submersible pumps are performing more efficiently and giving higher throughputs at 50 m head than DC submersible pump. Around 30 m head, 2 hp submersible DC pumps are performing better than 2 hp submersible AC pumps. AC pumps are showing subsystem efficiency in the range of 28–65% whereas DC pumps efficiency is in the range of 38–60%. For the performance optimization of SPV water pumping systems in real operating conditions, the MFC of radiation and temperature, water table height variations and operating point of a pump can be considered.

A surrogate-model assisted approach for optimising the size of tidal turbine arrays

The new and costly nature of tidal stream energy extraction technologies can lead to narrow margins of success for a project. The design process is thus a delicate balancing act – to maximise the energy extracted, while minimising cost and risk. Scenario specific factors, such as site characteristics, technological constraints and practical engineering considerations greatly impact upon both the appropriate number of turbines to include within a tidal current turbine array (array size), and the individual locations of those turbines (turbine micro-siting). Both have been shown to significantly impact upon the energy yield and profitability of an array.The micro-siting arrangement for a given number of turbines can significantly influence the power extraction of a tidal farm. Until the layout has been optimised (a process which may incorporate turbine parameters, local bathymetry and a host of other practical, physical, legal, financial or environmental constraints) an accurate forecast of the yield of that array cannot be determined. This process can be thought of as ‘tuning’ an array to the proposed site to maximise desirable outcomes and mitigate undesirable effects.The influence of micro-siting on the farm performance means that determining the optimal array size needs to be coupled to the micro-siting process. In particular, the micro-siting needs to be repeated for any new trial array size in order to be able to compare the performance of the different farm sizes. Considering the large number of design variables in the micro-siting problem (which includes at least the positions of each turbine) it becomes clear that algorithmic optimisation is a key tool to rigorously determine the optimal array size and layout.This paper proposes a nested optimisation approach for solving the array size and layout problem. The core of this approach consists of two nested optimisation procedures. The ‘outer’ optimisation determines the array size. At each ‘outer’ iteration the power extracted by N turbines is found via a separate optimisation of their micro-siting on the proposed site. The ‘inner’ optimisation is treated as a computationally expensive black-box solver, mapping array size to power (and additionally returning the optimal micro-siting design). This forms the basis of a practical approach to the array sizing problem based on Bayesian optimisation, in which a surrogate model is built and used to maximise the utility of each evaluation made by the solver.This paper introduces and reports on the implementation of this novel surrogate-assisted array design approach which, coupled with a simple financial model is demonstrated through optimisation of array size for two test scenarios to maximise the financial return on the array for the developer.

Optimal placement and sizing of wind / solar based DG sources in distribution system

Proper placement and sizing of Distributed Generation (DG) in distribution system can obtain maximum potential benefits. This paper proposes quantum particle swarm algorithm (QPSO) based wind turbine generation unit (WTGU) and photovoltaic (PV) array placement and sizing approach for real power loss reduction and voltage stability improvement of distribution system. Performance modeling of wind and solar generation system are described and classified into PQ\\PQ (V)\\PI type models in power flow. Considering the WTGU and PV based DGs in distribution system is geographical restrictive, the optimal area and DG capacity limits of each bus in the setting area need to be set before optimization, the area optimization method is proposed . The method has been tested on IEEE 33-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method.

Operation and Maintenance Cost Effect on Optimal Sizing of PV Array and Battery for a Grid-Connected House

Operation and Maintenance Cost Effect on Optimal Sizing of PV Array and Battery for a Grid-Connected House

Effects of load estimation error on small-scale off-grid photovoltaic system design, cost and reliability

The proliferation of off-grid photovoltaic (PV) systems is rapidly increasing in the least developed countries. The sizing of system components—primarily PV panels and batteries—is critically influenced by the expected daily load. However, accurately estimating incipient electrical load of rural consumers is fraught with challenges. Load estimation error is propagated through the design phase, potentially resulting in a system that is unduly expensive or fails to meet reliability targets. This article investigates the effects of daily load estimation error on system design, cost and reliability. Load and insolation data from seven off-grid systems in Malawi were collected. The systems were redesigned using three different intuitive design approaches considering different levels of load estimation error, ranging from ±90% of the actual measured load. The cost of each design is estimated from in-country prices. The reliability of each design is determined from an hourly simulation using the measured data. The results show that PV array and battery sizing scale proportionately with load estimation error and that the cost of load over-estimation is approximately US$1.92 to US$6.02 per watthour, whereas under-estimation can precipitously degrade reliability. A cost-versus-reliability analysis shows that for the Malawi systems, on average 46% of the PV and battery costs are used to improve the simulated hourly reliability from 99% to 100%. Moreover, the results point to the challenges with intuitive design approaches, showing that consideration of average load alone can lead to over- or under-designed systems.

A New Chessboard Placement and Sizing Method for Capacitors in a Charge-Scaling DAC by Worst-Case Analysis of Nonlinearity

Charge scaling data converters include a binary-weighted capacitor array in their structure. New methods for the placement and sizing of capacitor arrays with increased ratio accuracy and improved converter linearity are presented in this paper. A new model of statistical variation is used, which takes into account both spatial correlation between devices and device area. This is combined with a novel analytical model for the linearity metrics of a charge scaling digital-to-analog converter. Minimizing the variance of the linearity metrics directs a new chessboard placement method for the capacitor array. Chessboard placement is shown to be superior to the state of the art in consideration of both random and systematic mismatch. The new analytical model is then used to develop a flow for capacitor array sizing.