Dispatch of wind-thermal power system by using aggregated outputs of virtual power plants

Author(s):  
Ming-yang Li ◽  
Jie Hou ◽  
Yu-guang Niu ◽  
Ji-zhen Liu
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Changyu Zhou ◽  
Guohe Huang ◽  
Jiapei Chen

In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.


2016 ◽  
Vol 8 (1) ◽  
pp. 71 ◽  
Author(s):  
Yajing Gao ◽  
Huaxin Cheng ◽  
Jing Zhu ◽  
Haifeng Liang ◽  
Peng Li

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1182
Author(s):  
Weilin Zhong ◽  
Junru Chen ◽  
Muyang Liu ◽  
Mohammed Ahsan Adib Murad ◽  
Federico Milano

The paper proposes a coordinated frequency control strategy for Virtual Power Plant (VPPs), with the inclusion of Distributed Energy Resource (DERs), e.g., Solar Photo-Voltaic Generation (SPVG), Wind Generator (WG) as well as Energy Storage System (ESS). The objective is to improve the short-term dynamic response of the overall power system. The robustness of the proposed control is evaluated through a Monte Carlo analysis and a detailed modeling of stochastic disturbances of loads, wind speed, and solar irradiance. The impact of communication delays of a variety of realistic communication networks with different bandwidths is also discussed and evaluated. The case study is based on a modified version of the WSCC 9-bus test system with inclusion of a VPP. This is modeled as a distribution network with inclusion of a variety of DERs.


Author(s):  
V.V. Okuneva ◽  
◽  
A.A. Agamirzoev ◽  
K.B. Korneev ◽  
◽  
...  

We consider one of the most promising technologies for solving the problem of balancing a system with distributed generation is a virtual substation. It is noted that using the technologies of distributed computing and the «Internet of things», it is possible to implement an effective mechanism for decentralized control of power system elements.


2020 ◽  
Vol 189 ◽  
pp. 106609 ◽  
Author(s):  
Weilin Zhong ◽  
Mohammed Ahsan Adib Murad ◽  
Muyang Liu ◽  
Federico Milano

2021 ◽  
Vol 13 (22) ◽  
pp. 12423
Author(s):  
Qingyou Yan ◽  
Xingbei Ai ◽  
Jinmeng Li

To improve the economic benefits of power systems in the process of achieving multi-energy complementation and decarbonization, this paper proposes a dispatching optimization model for virtual power plants (VPP) that considers carbon trading and green certificates. Firstly, the structure of the VPP system integrating wind and solar generators (WP and PV), power-to-gas (P2G), carbon capture power plants (CCPP) and price-based demand response (PBDR) is established. Secondly, the two-way interactive trading models among the VPP, carbon trading and green certification market are constructed. Then, the dispatching optimization model of the VPP is constructed. Finally, the numerical example is solved and analyzed by the chaotic particle swarm optimization algorithm, which verifies the rationality and effectiveness of the new model. The results show that: (1) when the VPP considers the CCPP-P2G, the cost of the system is reduced by USD 2550.48, while the CO2 emissions are reduced by nearly 50%; (2) the addition of PBDR reduces the CO2 emissions of the thermal power unit, which has reduced the cost of carbon tax by nearly 27.8%, further reducing the cost of the VPP; (3) the introduction of the carbon trading and green certificate market has reduced the operating cost of the VPP by nearly 22.24%.


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