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

2019 ◽  
Vol 9 (17) ◽  
pp. 3586 ◽  
Author(s):  
Hong Li ◽  
Jie Duan ◽  
Dengyue Zhang ◽  
Jinghui Yang
Keyword(s):  
Optimal Solution ◽  
Bat Algorithm ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Aggregation Model ◽  
Multi Objective ◽  
Model Based ◽  
Objective Model ◽  
Compromise Optimal Solution

Aggregation technology can integrate distributed energy resources (DERs) into resource aggregation (RA) to achieve efficient utilization of resources. This paper studies a DERs aggregation model to construct a RA. Firstly, considering the uncertainty of the output of distributed generation (DG), the characteristics of DG are analyzed and the daily eigenvalues are extracted. The contour coefficient is introduced and the improved K-means algorithm is used to cluster the daily eigenvectors to get the multiple probability scenarios in a single season. Then, in order to obtain a RA with lower daily average cost, better power generation characteristics and higher regional aggregation degree, the DERs aggregation model based on multi-scenario and multi-objective is established considering multiple constraints. To obtain a compromise optimal solution, the cellular bat algorithm based on fuzzy membership degree (FMD-CBA) is used to solve the model. Finally, the validity of the multi-scenario and multi-objective model in a single season is verified by an example.

Microgrids physics model-based fault location formulation: Analytic-based distributed energy resources effect compensation

2021 ◽  
Vol 195 ◽  
pp. 107178
Author(s):  
A.S. Bretas ◽  
C. Orozco-Henao ◽  
J. Marín-Quintero ◽  
O.D. Montoya ◽  
W. Gil-González ◽  
...  
Keyword(s):  
Fault Location ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Model Based ◽  
Physics Model

scholarly journals Multi-Objective Optimization and Dispatch of Distributed Energy Resources for Renewable Power Utilization Considering Time-of-Use Tariff

2021 ◽  
Vol 9 ◽  
Author(s):  
Qinhao Xing ◽  
Meng Cheng ◽  
Shuran Liu ◽  
Qianliang Xiang ◽  
Hailian Xie ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Vehicles ◽  
Energy Resources ◽  
Energy Utilization ◽  
Distributed Energy Resources ◽  
Multi Objective Optimization ◽  
Distributed Energy ◽  
Demand Forecast ◽  
Multi Objective ◽  
The Impact

The intermittency of wind and solar power generation brings risks to the safety and stability of the power system. In order to maximize the utilization of renewables, optimal control and dispatch methods of the Distributed Energy Resources including the generators, energy storage and flexible demand are necessary to be researched. This paper proposes an optimization and dispatch model of an aggregation of Distributed Energy Resources in order to facilitate the integration of renewables while considering the benefits for dispatchable resources under time-of-use tariff. The model achieves multi-objective optimization based on the constraints of day-ahead demand forecast, wind and solar generation forecast, electric vehicles charging routines, energy storage and DC power flow. The operating cost, the renewable energy utilization and the revenues of storages and electric vehicles are considered and optimized simultaneously through the min–max unification method to achieve the multi-objective optimization. The proposed model was then applied to a modified IEEE-30 bus case, demonstrating that the model is able to reconcile all participants in the system. Sensitivity analysis was undertaken to study the impact of initial states of the storages on the revenues to the resource owners.

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