Analysis of Photovoltaic Carrying Capacity of Distribution Network Based on Voltage Sensitivity

Zhang, Xiaolin; Cheng, Xuke; Fu, Yao; Zhang, Jiabin; Gong, Xiaowei; Zhao, Qingsong

doi:10.1109/ccdc.2019.8833186

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…(3) Constraints: The total available urban roof area is limited to the total selected and assumed productive rooftop area; The PV module production capacity is limited in China 69 ; The selfsufficiency of RA is 100% at most to avoid oversupply; The energy penetration potential of RPV, which means the ratio of the total electricity output of renewable energy units to the annual load demand (Table S5), is limited to keep the stability of power system (50% at most) [70][71][72] ; The total GHG mitigation is greater than zero.…”

Section: Multi-objective Optimization For Allocation Of Ra and Rpvmentioning

confidence: 99%

Optimal use of urban rooftops can synergize food and energy production objectives

Hu,

Yang,

et al. 2024

Preprint

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Urban rooftop agriculture (RA) and photovoltaics (RPV) offer sustainable solutions for energy-food systems in cities but compete for limited rooftop space. We explore the potential benefits (provisioning, economic, and environmental) and allocation strategy of RA and RPV across 13 million buildings in 124 Chinese cities, considering building height, age, function, rooftop type and occupation, and regional productivity. We found that RA yields superior economic benefits, while RPV excels in cradle-to-grave greenhouse gas emission reduction benefits. Prioritizing either RA or RPV compromises 70–100% of the above benefits brought by the other. An optimized allocation to maximize the overall benefits would retain >55% of their potential, meeting 14% (mean, 0.5–99% across cities) of urban vegetable needs and 5% (0.5–27% across cities) of the electricity needs. Such a scenario requires allocating 54% (varied 4–99% across cities) of the flat rooftop area to RA, and all remaining rooftops to RPV. Together, the productivity from rooftop RA and RPV are equivalent to 2.3×103 km2 of cropland and 86 Mt of coal, contribute 1.5% of the national GDP and reduce 1.6% of national greenhouse gas emissions (account for 0.1–33% of city levels), requiring considerable water (up to 18% of urban residential water use) and material demand (e.g., totalling 9 kt silver). By elucidating the benefits and resource costs of rooftop utilization, our findings can support synergetic decision-making to meet multiple sustainability goals in diverse cities.

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Section: Multi-objective Optimization For Allocation Of Ra and Rpvmentioning

confidence: 99%

Optimal use of urban rooftops can synergize food and energy production objectives

Hu,

Yang,

et al. 2024

Preprint

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“…The DPV maximum access capacity model is an optimization problem under multidimensional constraints. Among them, literature [4] establishes a dual objective function of maximum capacity and minimum line loss and considers power constraints, node voltage constraints, the line carrying capacity constraints, DPV capacity constraints, and reverse tide constraints, so as to establish the maximum access capacity optimization model and calculate the optimal value through an improved booster algorithm; literature [5] establishes a distributed PV siting and capacity optimization model for medium-and low-voltage distribution networks and uses the medium-voltage distribution networks. Literature [6] establishes the maximum access capacity model of DPV grid connection and calculates the model based on the annual time series simulation of the genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Calculation Method of Hosting Capacity for Distributed Grid-connected Photovoltaic Based on IGWO

Xie

Tang²

2023

J. Phys.: Conf. Ser.

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In recent years, the distribution grid has been taking more and more risks due to the large-scale access of distributed photovoltaics (DPV), including potential problems such as voltage overrun and tidal current reversal, which seriously threaten grid security. Therefore, studying the maximum access capacity of distributed photovoltaics in the distribution grid is a research need nowadays. In this paper, we first establish a distributed PV grid-connected optimization operation model for distribution networks, taking into account multi-dimensional constraints such as voltage, load capacity, and active power, and then propose a grey wolf optimization based on particle swarm and Bernoulli chaos mapping, using chaos mapping initialization population, nonlinear convergence factor, and position update idea in the particle swarm algorithm to increase the initial population diversity and solution accuracy. Then, we use the improved grey wolf optimization algorithm (IGWO) as the basis for solving the maximum access capacity of distributed PV for distribution networks. Finally, simulations are conducted on the IEEE-33 node system to exemplify the previously developed model and algorithm.

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A Method of Calculating the Accessible Capacity of Distributed Photovoltaic in a Distribution Network Considering Capacity Ratio

Fang

Gao

et al. 2023

2023 IEEE 3rd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)

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Analysis of Photovoltaic Carrying Capacity of Distribution Network Based on Voltage Sensitivity

Cited by 3 publications

References 3 publications

Optimal use of urban rooftops can synergize food and energy production objectives

Optimal use of urban rooftops can synergize food and energy production objectives

Calculation Method of Hosting Capacity for Distributed Grid-connected Photovoltaic Based on IGWO

A Method of Calculating the Accessible Capacity of Distributed Photovoltaic in a Distribution Network Considering Capacity Ratio

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