A two-stage Microgrid cost optimization considering distribution network loss and voltage deviation

Gao, Jie; Chen, Jiajia; Cai, Ying; Zeng, Shuaibo; Peng, Ke

doi:10.1016/j.egyr.2019.11.072

Cited by 12 publications

(5 citation statements)

References 6 publications

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“…In [ 22 ], a Mixed Linear Programming (MILP) problem-based power management system was presented to investigate the operating behavior of MGs and reduce power losses. To identify the optimum size of MG a, a two-stage MG scheduling mechanism is suggested based on the group search optimizer (GSO) algorithm in [ 23 ]. The system stability index (SSI) is suggested to choose the MG’s location in the IEEE 33-bus distribution systems.…”

Section: Introductionmentioning

confidence: 99%

Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer

Tukkee,

bin Abdul Wahab,

binti Mailah

et al. 2024

PLoS ONE

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Recently, global interest in organizing the functioning of renewable energy resources (RES) through microgrids (MG) has developed, as a unique approach to tackle technical, economic, and environmental difficulties. This study proposes implementing a developed Distributable Resource Management strategy (DRMS) in hybrid Microgrid systems to reduce total net percent cost (TNPC), energy loss (Ploss), and gas emissions (GEM) while taking the cost-benefit index (CBI) and loss of power supply probability (LPSP) as operational constraints. Grey Wolf Optimizer (GWO) was utilized to find the optimal size of the hybrid Microgrid components and calculate the multi-objective function with and without the proposed management method. In addition, a detailed sensitivity analysis of numerous economic and technological parameters was performed to assess system performance. The proposed strategy reduced the system’s total net present cost, power loss, and emissions by (1.06%), (8.69%), and (17.19%), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. This study gives a more detailed plan for evaluating the effectiveness of hybrid Microgrid systems from a technical, economic, and environmental perspective.

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Section: Introductionmentioning

confidence: 99%

Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer

Tukkee,

bin Abdul Wahab,

binti Mailah

et al. 2024

PLoS ONE

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“…Researchers worldwide are paying more attention to the use of DG units in radial distribution networks because they can minimise power losses, improve voltage stability, save money, and use renewable energy in a cost-effective way [6]. Different methods have been developed to find the best location and size for DG units, using both classical and meta-heuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement and sizing of DG Units Using LCA Algorithm

Benkhetta,

Rouina,

Necira

2024

EAI Endorsed Trans Energy Web

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The motivation of this paper is to present an approach that relies on the league championship algorithm (LCA) to determine the most effective number, placement, and size of distributed generations (DG) within distribution systems. The primary objective of this approach is to minimize the losses of the power system, as well as to enhance the voltage profiles and stability index of the voltage. The optimal location of the DG units is determined through the use of the Loss Sensitivity Factor (LSF), while the optimal size of the DG units is found through the use of LCA. The IEEE 33-bus and 69-bus radial distribution systems were both tested to validate the proposed method, and the results obtained from LCA were compared to those of other methods found in the literature. The simulated results have shown that the LCA method proposed in this paper is highly effective and performs exceptionally well when addressing the problem of optimal location and sizing of DG units in radial networks.

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“…Currently, most collaborative optimisation models of "SGLS" are established based on power grid loss, system operation cost, renewable energy consumption etc. To ensure safe and reliable operation of the system, the influence of the SGLS interaction on grid loss and voltage deviation is considered; however, the economy of the system is ignored [20,21]. The scheduling model aims to maximise the utilisation rate of renewable energy and realise full-time collaborative optimisation of the SGLS [22].…”

Section: Introductionmentioning

confidence: 99%

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Huang

Liu³

2023

IET Generation Trans & Dist

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The multi‐scale flexibility coordination of multiple storages is a key technology to enhance the diversified regulation ability of the power system. This paper first considers the interaction mechanism of multi‐type storage peak regulation time sequences based on the Euclidian distance, dynamic time warping distance, and storage correlation distance. A matching index was proposed to consider the temporal correlation, overall distribution characteristics, and dynamic characteristics of the net load and energy storage. The multitype storage coordination mode, including battery storage, pumped storage, and electric vehicles, was formulated, and a collaborative optimal scheduling system architecture of source‐grid‐load‐storage (SGLS) was constructed. To attain a low‐carbon economy, a collaborative optimal scheduling model of SGLS considering the dynamic time‐series complementarity of multiple energy storage systems was constructed. The Nash equilibrium theory was used to achieve friendly interaction among the source, grid, load, and storage. Then, an improved transfer reinforcement learning algorithm for SGLS was proposed, which used reinforcement learning and transfer learning algorithms combined with K‐means clustering and dual‐structure experience pool technology. The test results of actual regional power grid data indicated that the proposed strategy can effectively reduce the economic and carbon treatment costs of the system and improve the absorption capacity of renewable energy.

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A two-stage Microgrid cost optimization considering distribution network loss and voltage deviation

Cited by 12 publications

References 6 publications

Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer

Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer

Optimal Placement and sizing of DG Units Using LCA Algorithm

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

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