Virtual Power Plant: New Solution for Managing Distributed Generations in Decentralized Power Systems

Author(s):  
Mohamad Amin Salmani ◽  
Arash Anzalchi ◽  
Soudeh Salmani
2021 ◽  
Vol 11 (3) ◽  
pp. 1282
Author(s):  
Qingwen Xu ◽  
Yongji Cao ◽  
Hengxu Zhang ◽  
Wen Zhang ◽  
Vladimir Terzija

Non-synchronous renewable energy sources (RESs) have strong volatility and low inertia, which brings about great challenges on the accommodation of RESs and the security and stability of power systems. This paper proposes a bi-level power system dispatch and control architecture based on the grid-friendly virtual power plant (GVPP), so as to accommodate RESs flexibly and securely. The typical dispatch and control system of the power system in China is presented, and the particular challenges stemming from non-synchronous RESs are analyzed. The functional requirements, concept, and fundamental design of the GVPP are provided, which is distinguished from traditional virtual power plants (VPPs) for its active participation in power system stability control. Based on the cloud platform, a bi-level dispatch and control architecture considering two objectives is established. First, in the inner level, the GVPP operates to promote the accommodation of RESs under normal condition. Then, from the perspective of out-level power systems, GVPPs serve as spinning reserves for power support under contingencies. Besides, the key problems to be solved in the development of the GVPP-based architecture are summarized. Although the architecture is proposed for the power system in China, it can be applied to any power systems with similar challenges.


2013 ◽  
Vol 448-453 ◽  
pp. 2695-2698
Author(s):  
Tian Ran Li ◽  
Yun Hu Luo ◽  
Lin Sun

Virtual Power Plant (VPP) is a new entity in power systems that manages a set of various distributed energy resources (DERs). One of the functions of VPP is to determine the allocation of reserve to solve the problem of renewable generation uncertainty. In this paper, the reserve resources of VPP are classified into non-renewable distributed generation (NRDG), energy storage device (ESD), interruptible load (IL) and reserve bought from the market (RBFM). Their complementary properties should be utilized to improve the economy of reserve allocation. An optimal coordination model for risk management of NRDG configuration of VPP reserve allocation is proposed. Simulation results are presented to validate that an optimal value of NRDG configuration should exist.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Jie Yu ◽  
Qizhi Feng ◽  
Yang Li ◽  
Jinde Cao

Virtual power plant (VPP) is an aggregation of multiple distributed generations, energy storage, and controllable loads. Affected by natural conditions, the uncontrollable distributed generations within VPP, such as wind and photovoltaic generations, are extremely random and relative. Considering the randomness and its correlation of uncontrollable distributed generations, this paper constructs the chance constraints stochastic optimal dispatch of VPP including stochastic variables and its random correlation. The probability distributions of independent wind and photovoltaic generations are described by empirical distribution functions, and their joint probability density model is established by Frank-copula function. And then, sample average approximation (SAA) is applied to convert the chance constrained stochastic optimization model into a deterministic optimization model. Simulation cases are calculated based on the AIMMS. Simulation results of this paper mathematic model are compared with the results of deterministic optimization model without stochastic variables and stochastic optimization considering stochastic variables but not random correlation. Furthermore, this paper analyzes how SAA sampling frequency and the confidence level influence the results of stochastic optimization. The numerical example results show the effectiveness of the stochastic optimal dispatch of VPP considering the randomness and its correlations of distributed generations.


Author(s):  
C.S. Ioakimidis ◽  
L. Oliveira ◽  
K.N. Genikomsakis ◽  
P. Ryserski

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