Stochastic Optimal Dispatch of Virtual Power Plant considering Correlation of Distributed Generations

Yu, Jian; Feng, Qizhi; Li, Yang; Cao, Jinde

doi:10.1155/2015/135673

Cited by 7 publications

(5 citation statements)

References 13 publications

(17 reference statements)

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“…The specific equations of these copula functions are presented in Appendix A . In this study, the Euclidean distance (

), which is a non-probabilistic measure of goodness of approximation with the advantage of simple calculation [ 25 , 26 ], was used to evaluate the performance of each selected copula function. The value of

was 0.042, 0.0411, 0.2037, 0.0402, 0.2037, and 0.3232 corresponding to the above copula functions.…”

Section: Applicationmentioning

confidence: 99%

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Sun

Singh

et al. 2019

Entropy

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Allocation and management of agricultural water resources is an emerging concern due to diminishing water supplies and increasing water demands. To achieve economic, social, and environmental goals in a specific irrigation district, decisions should be made subject to the changing water supply and water demand—the two critical random parameters in agricultural water resources management. This paper presents the foundations of a systematic framework for agricultural water resources management, including determination of distribution functions, joint probability of water supply and water demand, optimal allocation of agricultural water resources, and evaluation of various schemes according to agricultural water resources carrying capacity. The maximum entropy method is used to estimate parameters of probability distributions of water supply and demand, which is the basic for the other parts of the framework. The entropy-weight-based TOPSIS method is applied to evaluate agricultural water resources allocation schemes, because it avoids the subjectivity of weight determination and reflects the dynamic changing trend of agricultural water resources carrying capacity. A case study using an irrigation district in Northeast China is used to demonstrate the feasibility and applicability of the framework. It is found that the framework works effectively to balance multiple objectives and provides alternative schemes, considering the combinatorial variety of water supply and water demand, which are conducive to agricultural water resources planning.

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“…The specific equations of these copula functions are presented in Appendix A . In this study, the Euclidean distance (

was 0.042, 0.0411, 0.2037, 0.0402, 0.2037, and 0.3232 corresponding to the above copula functions.…”

Section: Applicationmentioning

confidence: 99%

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Sun

Singh

et al. 2019

Entropy

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show abstract

“…random inputs defined in the same probability space as w. As shown in [254], models of the form (6) are fairly general and they cover a variety of stochastic hybrid systems that commonly emerge in engineering systems. Most of the existing results in VPPs using stochastic models have focused on economic dispatch problems [255], [256]. However, as the set of analytical tools for the study of SHDS of the form ( 6) is further developed, we expect to see more realistic mathematical models of VPPs that incorporate the natural stochastic and non-smooth behaviors in the fast dynamics of the closed-loop system.…”

Section: D: Stochastic Hybrid Systems Framework In Vppsmentioning

confidence: 99%

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

et al. 2023

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Virtual Power Plants (VPPs) have emerged as a modern real-time energy management architecture that seeks to synergistically coordinate an aggregation of renewable and non-renewable generation systems to overcome some of the fundamental limitations of traditional power grids dominated by synchronous machines. In this survey paper, we review the different existing and emerging feedback control mechanisms and architectures used for the real-time operation of VPPs. In contrast to other works that have mostly focused on the optimal dispatch and economical aspects of VPPs in the hourly and daily time scales, in this paper we focus on the dynamic nature of the system during the faster sub-hourly time scales. The virtual (i.e., software-based) component of a VPP, combined with the power plant (i.e., physics-based) components of the power grid, make VPPs prominent examples of cyber-physical systems, where both continuous-time and discrete-time dynamics play critical roles in the stability and transient properties of the system. We elaborate on this interpretation of VPPs as hybrid dynamical systems, and we further discuss open research problems and potential research directions in feedback control systems that could contribute to the safe development and deployment of autonomous VPPs.INDEX TERMS Smart grids, renewable energy, virtual power plant, feedback control, multi-agent hybrid dynamical systems.

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“…In [25], a two-stage distributed robust optimization (DRO) method was investigated to solve the uncertainties of wind power for the VPP. In [26], an operational optimization model considering the correlation of random variables for the VPP was developed, and an SO method was combined with the sample average approximation method to address the uncertainties of distributed power. In [27], a two-stage DRO approach was presented considering multiple uncertainties of electricity price and wind power for the VPP.…”

Section: Introductionmentioning

confidence: 99%

Distributed Cooperative Optimal Operation of Multiple Virtual Power Plants Based on Multi-Stage Robust Optimization

Cheng,

Li,

Yang

2024

Sustainability

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This paper develops a distributed cooperative optimization model for multiple virtual power plant (VPP) operations based on multi-stage robust optimization and proposes a distributed solution methodology based on the combination of the alternating direction method of multipliers (ADMMs) and column-and-constraint generation (CCG) algorithm to solve the corresponding optimization problem. Firstly, considering the peer-to-peer (P2P) electricity transactions among multiple VPPs, a deterministic cooperative optimal operation model of multiple VPPs based on Nash bargaining is constructed. Secondly, considering the uncertainties of photovoltaic generation and load demand, as well as the non-anticipativity of real-time scheduling of VPPs in engineering, a cooperative optimal operation model of multiple VPPs based on multi-stage robust optimization is then constructed. Thirdly, the constructed model is solved using a distributed solution methodology based on the combination of the ADMM and CCG algorithms. Finally, a case study is solved. The case study results show that the proposed method can realize the optimal scheduling of renewable energy in a more extensive range, which contributes to the promotion of the local consumption of renewable energy and the improvement of the renewable energy utilization efficiency of VPPs. Compared with the traditional deterministic cooperative optimal operation method of multiple VPPs, the proposed method is more resistant to the risk of the uncertainties of renewable energy and load demand and conforms to the non-anticipativity of real-time scheduling of VPPs in engineering. In summary, the presented works strike a balance between the operational robustness and operational economy of VPPs. In addition, under the presented works, there is no need for each VPP to divulge personal private data such as photovoltaic generation and load demand to other VPPs, so the security privacy protection of each VPP can be achieved.

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Stochastic Optimal Dispatch of Virtual Power Plant considering Correlation of Distributed Generations

Cited by 7 publications

References 13 publications

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

Distributed Cooperative Optimal Operation of Multiple Virtual Power Plants Based on Multi-Stage Robust Optimization

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