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Efficient Renewable Energy Integration Technology in Low Voltage Networks

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 15 January 2025 | Viewed by 5354

Special Issue Editors


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Guest Editor
AAU Energy, Aalborg University, 9220 Aalborg, Denmark
Interests: low voltage distribution network; voltage regulation; RES integration; distributed energy storage systems; distributed control and optimization

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Guest Editor
Center for Research on Microgrids (CROM), AAU Energy, Aalborg University, 9220 Aalborg, Denmark
Interests: microgrids; distributed generation systems; paralleled inverters; control strategy; internet of things (IoT); PV converters; small signal stability; energy management system
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Special Issue Information

Dear Colleagues,

The integration of renewable energy resources (RES) into low-voltage distribution networks (LVDNs) is a pivotal aspect of the ongoing energy transition, driven by the goals of sustainability and decarbonization. This transition, while promising, poses a set of formidable challenges.

Voltage instability arises from the intermittent nature of RES, particularly solar and wind, necessitating advanced voltage regulation mechanisms to maintain grid stability within prescribed bounds. Power quality concerns stem from the inherent variability in renewable generation, warranting vigilant power quality monitoring and the implementation of measures to mitigate waveform distortions and harmonics, ensuring adherence to established standards.

The resilience and reliability of low-voltage grids face new complexities with the integration of variable RES. Dynamic grid management strategies are imperative to accommodate fluctuating RES generation, ensuring consistent power supply and effective response to unforeseen disturbances.

Furthermore, the surge in distributed RES integration can exacerbate distribution network congestion, primarily in areas with high concentrations of renewable generation. Effectively managing this congestion requires grid upgrades, demand response strategies, and innovative market-based solutions to optimize resource allocation and alleviate bottlenecks.

These challenges require a holistic approach that encompasses technological advancements, grid modernization, sophisticated control systems, and supportive regulatory frameworks. The purpose of this Special Issue is to provide a platform for knowledge exchange and publication of research related to efficient RES integration in low voltage networks to facilitate the transition toward a cleaner, highly resilient, and sustainable energy landscape.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  1. Interactions between Home-MG/Mini-MG and LVDN;
  2. Voltage regulation/control of LVDN with RES;
  3. Energy storage technology and management for renewable integration;
  4. Power quality control and improvement in low-voltage distribution network with high proportion of RES;
  5. Intelligent control and coordination for self-healing, autonomy and self-organization of LVDN;
  6. Accurate power forecasting of distributed renewable generation in LVDNs.

We look forward to receiving your contributions.

Dr. Wenfa Kang
Dr. Yajuan Guan
Prof. Dr. Juan C. Vasquez
Guest Editors

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Keywords

  • low voltage distribution network
  • renewable energy resources
  • distributed energy storage systems
  • electrical vehicles
  • voltage regulation
  • power quality enhancement
  • home microgrids/mini-microgrids
  • Intelligent algorithms
  • Power forecasting

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Published Papers (4 papers)

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Research

14 pages, 688 KiB  
Article
Stochastic Optimal Operation of SOP-Assisted Active Distribution Networks with High Penetration of Renewable Energy Sources
by Hongtao Li, Zijin Li, Bo Wang and Kai Sun
Sustainability 2024, 16(13), 5808; https://doi.org/10.3390/su16135808 - 8 Jul 2024
Viewed by 790
Abstract
This paper introduces a mixed-integer convex model for optimizing the scheduling of soft open points (SOPs) integrated with energy storage (ES) in active distribution networks (ADNs) with high proportions of photovoltaic sources, designed to ensure zero risk of constraint violations. A stochastic optimization [...] Read more.
This paper introduces a mixed-integer convex model for optimizing the scheduling of soft open points (SOPs) integrated with energy storage (ES) in active distribution networks (ADNs) with high proportions of photovoltaic sources, designed to ensure zero risk of constraint violations. A stochastic optimization model for ADNs is proposed to maximize the benefits of SOPs while simultaneously minimizing system power losses, SOP power losses, voltage deviations, PV power curtailment, battery energy storage system (BESS) operation cost, and utility power purchase. Uncertainties in PV generation and load demand are considered by Monte Carlo simulation and k-means technologies. Finally, simulation cases from a 21-bus distribution network show that the curtailment of PV sources is minimized and the power fluctuations of the BESS are reduced in comparison to the case without SOP. Constraints in the nodal voltages, power outputs, energy balance, and power flow are all satisfied. Full article
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16 pages, 2302 KiB  
Article
Two-Layer Optimization Strategy of Electric Vehicle and Air Conditioning Load Considering the Benefit of Peak-to-Valley Smoothing
by Sichen Shi, Peiyi Wang, Zixuan Zheng and Shu Zhang
Sustainability 2024, 16(8), 3207; https://doi.org/10.3390/su16083207 - 11 Apr 2024
Cited by 1 | Viewed by 1099
Abstract
To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load [...] Read more.
To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behavior of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples show that the proposed two-layer optimization method can take advantage of the complementarity of air conditioning and electric vehicles to improve the income of load aggregators. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model. Full article
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13 pages, 3447 KiB  
Article
Optimal Capacity Model for Battery Swapping Station of Electric Taxis: A Case Study in Chengdu
by Siyu Xie, Guangyan Wang, Yiyi Zhang, Bo Li and Junhui Zhao
Sustainability 2024, 16(4), 1676; https://doi.org/10.3390/su16041676 - 18 Feb 2024
Viewed by 1324
Abstract
Battery swapping station (BSS) technology can provide electric taxis (ETs) with more economical and high-efficiency operating services. However, the battery-swapping market needs to be more organized due to unpredictable swapping periods for ETs, resulting in more requirements for batteries of BSSs needing multiple [...] Read more.
Battery swapping station (BSS) technology can provide electric taxis (ETs) with more economical and high-efficiency operating services. However, the battery-swapping market needs to be more organized due to unpredictable swapping periods for ETs, resulting in more requirements for batteries of BSSs needing multiple batteries simultaneously. To address these challenges, this paper first analyzed two operation patterns of taxis to estimate the demand for swapping ETs. Then, an optimal capacity model of BSS is proposed to optimize the battery capacity of BSSs to meet the swapping demand of ETs. Finally, a genetic algorithm (GA) is utilized to solve the proposed model. The real operating data of taxis with GPS routes in Chengdu city are used as a case study to validate the proposed method. The results show that the proposed method could obtain the optimal battery capacity of a BSS and improve the economic benefits of BSSs. Full article
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19 pages, 5797 KiB  
Article
Capacity Value Assessment for a Combined Power Plant System of New Energy and Energy Storage Based on Robust Scheduling Rules
by Sicheng Wang and Weiqing Sun
Sustainability 2023, 15(21), 15327; https://doi.org/10.3390/su152115327 - 26 Oct 2023
Cited by 5 | Viewed by 1251
Abstract
With the rapid increase in new energy penetration, the uncertainty of the power system increases sharply. We can smooth out fluctuations and promote the more grid-friendly integration of new energy by combining it with energy storage. This paper proposes an evaluation method for [...] Read more.
With the rapid increase in new energy penetration, the uncertainty of the power system increases sharply. We can smooth out fluctuations and promote the more grid-friendly integration of new energy by combining it with energy storage. This paper proposes an evaluation method for assessing the value of a combined power plant system of new energy and energy storage using robust scheduling rules. Firstly, the k-means clustering algorithm is improved by using the elbow method in order to generate typical scenarios that can be used for the operation optimization of the combined power plant system of new energy and energy storage. Then, a two-stage robust optimization model of the combined power plant system of new energy and energy storage with a min–max–min structure is constructed according to the uncertainty of new energy. In this model, the operation constraints and coordinated control of wind–solar–thermal–storage units are considered. By constructing the uncertainty set of the new energy output, the overall operating cost of the system is minimized and uncertainty adjustment parameters are introduced to flexibly adjust the conservatism of the scheduling rules. Furthermore, based on the column and constraint generation algorithm and strong duality theory, the original problem can be decomposed into a master problem and subproblems with mixed integer linear characteristics for an alternating solution, so as to obtain the optimal solution of the original problem, and finally obtain the robust scheduling rule with the lowest operating cost under the worst scenario. Finally, based on the wind and solar power output curves and the output of each unit under the robust scheduling rules, combined with the value estimation method of the combined power plant system of new energy and energy storage, the value of the combined power plant system of new energy and energy storage is evaluated. Through the establishment of models and example analysis, it is proven that raising the quantity of the grid-connected power generated with new energy will cause an increase in the volatility of the power system; it will also bring considerable benefits to new energy plants, and the energy storage can improve the stability of the system. The above can provide references for the subsequent energy storage configuration in the planning of a combined power plant system of new energy and energy storage. Full article
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