A Distributed Energy Resources Aggregation Model Based on Multi-Scenario and Multi-Objective Methodology

Li, Hong; Duan, Jie; Zhang, Dengyue; Yang, Jianguo

doi:10.3390/app9173586

Cited by 6 publications

(3 citation statements)

References 21 publications

(22 reference statements)

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“…However, as summarized in Table 1, the peak shaving optimization scheduling models in the above research are usually and mainly established for centralized and utility-scale PV, energy storage, and wind power, and there are few research studies focusing on the DGs in peak shaving. Moreover, due to the small capacity, large number, random location of DGs, applying the above method in scheduling for each DG participating in peak shaving directly will lead to problems, such as difficulty in solving, explosion of variable dimensions, and hard in convergence of the solution results [18].Clustering partition provides a new way to deal with a large number of scattered DGs [19,20], and the cluster algorithm is one of the commonly used methods, such as K-means, self-organizing mappings, fuzzy C-means, and agglomerative hierarchical clustering [21][22][23]. Through the cluster methods, the corresponding aggregation model can be obtained, so that the roughly adjustable capacity of each cluster can be estimated, and this value is often fixed.…”

Section: Introductionmentioning

confidence: 99%

Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism

Li¹,

Wang³

et al. 2022

Energies

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As one of the power auxiliary services, peak shaving is the key problem to be solved in the power grid. With the rapid development of DGs, the traditional peak shaving scheduling method for centralized adjustable energy is no longer applicable. Thus, this paper proposes two-layer optimization methods of allocating the peak shaving task for DGs. Layer 1 mainly proposes four evaluation indexes and the peak shaving priority sequence can be obtained with modified TOPSIS, then the DG cluster’s task is allocated to the corresponding DGs. On the basis of dynamic evaluation and the self-renewal mechanism, layer 2 proposes a peak shaving optimization model with dynamic constraints which assigns peak shaving instructions to each cluster. Finally, the effectiveness of the method is verified by using the real DGs data of a regional power grid in China based on the MATLAB simulation platform. The results demonstrate that the proposed methods can simply the calculation complexity by ranking the DGs in the peak shaving task and update the reliable aggregate adjustable power of each cluster in time to allocate more reasonably.

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Section: Introductionmentioning

confidence: 99%

Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism

Li¹,

Wang³

et al. 2022

Energies

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“…Furthermore, DERs in Germany are currently officially capable of providing SRL (Sekundärregelliestung) and TRL (Tertiärregelliestung), as long as the DER passes the prequalification tests with the same technical criteria required for the conventional resources. One of the major types of DER participating in both systems consists of BESS and non-dispatchable renewables, as a BTMG (behind-the-meter-generator) coordinated together [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Integrated DA Coordination of DER Considering Reliability Constraints for Participation in the Renewable Energy Certificate Market in South Korea: A Case Study in a DER Complex

Lee

2021

Applied Sciences

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Due to the penetration of renewable energy sources increasing in South Korea, problems related to system reliability have been emerging. Thus, localized control methods have also been gaining attention as one of the measures. However, due to the AOs (asset owners) lacking management experience of coordinating resources between the BESS (battery energy storage system) and the renewable device, there have been multiple issues related to damages caused by fire. Thus, the governmental reliability committee in South Korea has recently mandated an order adding reliability constraints to the SoC (state of charge) management and incentives for the AOs to follow the reliability constraints as specified, despite concerns from the AOs that the order possibly reduces their revenues. Thus, this study provides a structured analysis, for the first time, on how the incentive and the reliability constraints influence and interact with each other in coordinated operating schemes between BESSs and renewables as integrated scheduling systems. In the base case, the current scheduling method was applied. In case 1, profit maximization was introduced to confirm the effectiveness of the structured operation. In case 2, a reliability constraint was added, and a reliability constraint with incentives was added in case 3 to confirm the effects thereafter on the revenue streams.

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“…With the deterioration of the environment and the frequent occurrence of energy problems, new energy research is being actively conducted in various fields to achieve sustainable energy development, and distributed power sources are combined with the power grid to improve the energy structure [1,2]. Distributed power generation has the characteristics of volatility, randomness, and a small amount of power trading; therefore, it does not have the conditions to participate in the competition in wholesale, futures, and contract markets.…”

Section: Introductionmentioning

confidence: 99%

Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model

Geng

Tan

et al. 2019

Processes

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The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form wind storage joint ventures to participate in power market competition. At the same time, middlemen are introduced, constructing an upper-level game model (considering power producers and wind storage joint ventures) that forms equilibrium results of bidding competition in the wholesale and power distribution markets. Based on the equilibrium result of the upper-level model, a lower model is constructed to distribute the profits from wind storage joint ventures. The profits of each wind storage joint venture, wind power supplier, and pumped storage power station are obtained by the Nash negotiation and the Shapely value method. Finally, a case study is conducted. The results show that the wind storage joint ventures can improve the economics of the system. Further, the middlemen can smooth the rapid fluctuation of power price in the distribution and wholesale market, maintaining a smooth and efficient operation of the electricity market. These findings provide information for the design of an electricity market competition mechanism and the promotion of new energy power generation.

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A Distributed Energy Resources Aggregation Model Based on Multi-Scenario and Multi-Objective Methodology

Cited by 6 publications

References 21 publications

Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism

Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism

Integrated DA Coordination of DER Considering Reliability Constraints for Participation in the Renewable Energy Certificate Market in South Korea: A Case Study in a DER Complex

Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model

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