A bottom-up energy simulation framework to accurately compare PV module topologies under non-uniform and dynamic operating conditions

Manganiello, Patrizio; Baka, M.; Goverde, Hans; Borgers, Tom; Govaerts, Jonathan; Heide, Arvid van der; Voroshazi, Eszter; Catthoor, Francky

doi:10.1109/pvsc.2017.8366588

Cited by 6 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in [4], the snake-like structure ensures minimal additional resistance due to the added wiring, as compared to the wiring scheme of a standard module, while keeping a reasonable level of granularity. Indeed, as further shown in [5], snake topologies made of 60 6-inch cells perform very well under partial shading, leading to 60-80% additional energy generation compared to standard topologies. However, their losses under uniform conditions may be unacceptably high [5].…”

Section: Optimization Methodologymentioning

confidence: 73%

“…Indeed, as further shown in [5], snake topologies made of 60 6-inch cells perform very well under partial shading, leading to 60-80% additional energy generation compared to standard topologies. However, their losses under uniform conditions may be unacceptably high [5].…”

Section: Optimization Methodologymentioning

confidence: 73%

“…1, and (2) 120 6-inch halved cells, organized in a 12x10 matrix have been studied. Modules are modeled as described in [5]. The different instantiations to analyze have been selected according to the methodology described above.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Let's show the process of selection of feasible module instantiation for the specific case = {8,4,60}, that represents Snake modules made of 60 cells, with 8 cell-strings and 4 local converters. According to the design constraints described above, only three multisets verifying (1) can be created: Simulations have been performed using the framework presented in [5]. It allows for combination of measured weather data with simulated non-uniform and dynamic shading scenarios, so that realistic time-and spatially-varying operating scenarios are created.…”

Section: Optimization Methodologymentioning

confidence: 99%

See 3 more Smart Citations

Optimization Methodology for Reconfigurable PV Modules

Manganiello

Bosmalis

Baka

et al. 2018

2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC &Amp

Self Cite

View full text Add to dashboard Cite

Reconfigurable photovoltaic modules represent an effective solution to improve PV system resilience to partial shading. Indeed, the availability of different configurations increases energy generation under non-uniform conditions. However, the additional components that are active under uniform conditions lead to higher losses compared to equivalent static solutions. This paper presents a methodology for the design of optimized reconfigurable PV modules, balancing losses under uniform conditions and gain under partial shading. First, feasible reconfigurable module instantiations are selected given some design constraints. Then, the search space is further reduced by taking into account the typical operating conditions of the module. Finally, the best module layouts are chosen based on performance consideration. Results for a specific case study are presented to show the feasibility of the proposed methodology.

show abstract

Section: Optimization Methodologymentioning

confidence: 73%

Section: Optimization Methodologymentioning

confidence: 73%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Optimization Methodologymentioning

confidence: 99%

See 2 more Smart Citations

Optimization Methodology for Reconfigurable PV Modules

Manganiello

Bosmalis

Baka

et al. 2018

2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC &Amp

Self Cite

View full text Add to dashboard Cite

show abstract

“…This removes considerable amount of time for manual building model reconstruction using software such as SketchUp which generally requires detailed building floor plan and several days of work to reconstruct one building model. [44,45] Compared to another building model recreation approach where drone based photogrammetry is used, our method requires neither traveling nor drone operation skills, but it can still deliver highly accurate geo-referenced building models because the only inputs are LiDAR data and building footprints which are both freely available. [46] One of the main limitations of this methodology is that the building façade details cannot be properly modelled as shown in Figure 6.…”

Section: Reconstruction Of 3d Building Modelmentioning

confidence: 99%

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

et al. 2022

View full text Add to dashboard Cite

The Paris Agreement released in 2015 states that the global warming should be limited to 1.5 C. [1] In response to this agreement, the Dutch government issued the National Climate Agreement in 2019, and an ambitious goal was established where by 2030 the greenhouse gas emission must be reduced by 49% compared to 1990 levels. [2] It is also expected that 70% of the electricity generation will be covered by renewable energy sources by 2030 and become fully sustainable by 2050. To achieve this goal, a boost of green energy penetration in the energy system is required.Current energy distribution system is predominantly featured with centralized generator and monodirectional distribution network. This means that electricity is mainly produced in a giant power plant and transported through long-distance cables to reach consumer end. Unfortunately, the green future scenario cannot be simply achieved by replacing the conventional power plants with large green energy farms. One of the reasons lies in the fact that centralized paradigm lacks reliability because the entire grid can fail with the failure in central power plant. [3] Considering the intermittent nature of renewable energies, optimizing the energy system reliability will be even more challenging. Another argument against centralization is the power loss during long-distance transportation and distribution of electricity. [4] As a solution, decentralized green energy sources allow one to produce electricity locally. It distributes the responsibility of electricity generation over small-sized producers, and power loss as a result of transmission can also be effectively minimized because the generator is either on site or near-site. Meanwhile, given the fact that the majority people will be living in densely populated cities in the future, [5] developing decentralized renewable energy sources in urban environment will play a major role in the green energy transition.Delft University of Technology (TU Delft) is aiming for a climate-neutral campus by 2030. [6] Of all the renewable energy sources, photovoltaic (PV) is the most promising technology to fulfil this target. It can be integrated with most urban elements such as buildings, [7] roads, [8] and waterways, [9] without demanding additional urban space. [10] Currently, only 1.2 MWp of solar capacity is installed on campus buildings. [11] To reach TU Delft ambitious goal, the number of mounted PV panels needs to be drastically increased such that 50% of electricity generation on campus can be covered. Although PV technology is preferred due to its high compatibility, designing PV system in the urban environment is no easy task. Densely constructed cities restrict the incoming sunlight, and rich urban morphology including buildings, infrastructures and vegetations can cause complex shading patterns. Therefore, it is fundamental to understand the urban context such that available building surfaces can be

show abstract

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

et al. 2021

View full text Add to dashboard Cite

Photovoltaic (PV) technology is the most promising renewable energy source to be integrated on urban building surfaces. Modeling and simulating urban PV systems pose more challenges than the conventional ones installed in open field due to rich urban morphology. Herein, a comprehensive workflow to estimate urban solar PV potential is developed where TU Delft campus is used as a case study. This workflow only requires light detection and ranging data and building footprints as data inputs, and multiple levels of result can be delivered including accurate geo‐referenced 3D building models, annual solar irradiation map, annual DC/AC yield maps and classified roof segments according to the specific yield of mounted PV system. The study reports a total of ≈8.1 GWh year−1 of PV energy which can be collected from campus building roofs and facades. Given the total electricity demand on the entire campus being 82.6 GWh/year, this PV potential can cover roughly 10% of the current electricity demand. The results constitute an initial assessment of solar PV potential on TU Delft campus buildings that is currently being used to prioritize PV integration on buildings and accelerate the transition toward a climate‐neutral campus.

show abstract

A bottom-up energy simulation framework to accurately compare PV module topologies under non-uniform and dynamic operating conditions

Cited by 6 publications

References 16 publications

Optimization Methodology for Reconfigurable PV Modules

Optimization Methodology for Reconfigurable PV Modules

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

Contact Info

Product

Resources

About