scholarly journals Coordinated Control of Virtual Power Plants to Improve Power System Short-Term Dynamics

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1182
Author(s):  
Weilin Zhong ◽  
Junru Chen ◽  
Muyang Liu ◽  
Mohammed Ahsan Adib Murad ◽  
Federico Milano
Keyword(s):  
Power System ◽  
Communication Networks ◽  
Power Plants ◽  
Frequency Control ◽  
Energy Resource ◽  
Test System ◽  
Virtual Power ◽  
Short Term ◽  
Virtual Power Plants ◽  
The Impact

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.

Impact of Virtual Power Plants on Power System Short-Term Transient Response

2020 ◽  
Vol 189 ◽  
pp. 106609 ◽  
Author(s):  
Weilin Zhong ◽  
Mohammed Ahsan Adib Murad ◽  
Muyang Liu ◽  
Federico Milano
Keyword(s):  
Power System ◽  
Transient Response ◽  
Power Plants ◽  
Virtual Power ◽  
Short Term ◽  
Virtual Power Plants

scholarly journals Planning of Electric Power Systems Considering Virtual Power Plants with Dispatchable Loads Included: An Inexact Two-Stage Stochastic Linear Programming Model

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Changyu Zhou ◽  
Guohe Huang ◽  
Jiapei Chen
Keyword(s):  
Linear Programming ◽  
Power System ◽  
Electric Power ◽  
Power Supply ◽  
Power Plants ◽  
Electricity Demand ◽  
Virtual Power ◽  
Stochastic Linear Programming ◽  
Two Stage ◽  
Virtual Power Plants

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.

scholarly journals Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Rakkyung Ko ◽  
Sung-Kwan Joo
Keyword(s):  
Renewable Energy ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Mixed Integer ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distributed Energy Resource ◽  
Stochastic Mixed Integer Programming ◽  
Virtual Power Plants

Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method.

scholarly journals Short term energy forecasting techniques for virtual power plants

2016 ◽  
Author(s):  
Sharon Ravichandran ◽  
Vijayalakshmi A ◽  
K. Shanti Swarup ◽  
Haile-Selassie Rajamani ◽  
Prashant Pillai
Keyword(s):  
Power Plants ◽  
Virtual Power ◽  
Short Term ◽  
Energy Forecasting ◽  
Virtual Power Plants ◽  
Term Energy ◽  
Forecasting Techniques

Microgrids and virtual power plants: Concepts to support the integration of distributed energy resources

2008 ◽  
Vol 222 (7) ◽  
pp. 731-741 ◽  
Author(s):  
D Pudjianto ◽  
C Ramsay ◽  
G Strbac
Keyword(s):  
Power Plants ◽  
Test System ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Ancillary Service ◽  
Virtual Power ◽  
Distributed Energy ◽  
Virtual Power Plants ◽  
Efficient Integration ◽  
Cost Efficient

This article presents the concepts of the microgrid and the virtual power plant (VPP) as vehicles to facilitate cost-efficient integration of distributed energy resources (DERs) into the existing power system. These concepts were designed to enhance the system value and the controllability of DER and to provide frameworks for the development of interfaces among energy and ancillary service resources, system operators, and energy market participants. Through aggregation, DER access to energy markets is facilitated, and DER-based system support and ancillary services can be provided. By enabling this additional functionality, it is envisaged that system performance measured in the form of energy efficiency, power quality, security, and economic operation can be improved. In this paper, the technical and commercial functionality facilitated through the microgrid and VPP concepts is described. The paper concludes with case studies demonstrating the application of the concepts on a test system.

scholarly journals Mixed Integer Quadratic Programming Based Scheduling Methods for Day-Ahead Bidding and Intra-Day Operation of Virtual Power Plant

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1410 ◽  
Author(s):  
Rakkyung Ko ◽  
Daeyoung Kang ◽  
Sung-Kwan Joo
Keyword(s):  
Quadratic Programming ◽  
Power Systems ◽  
Power Plants ◽  
Power Grids ◽  
Mixed Integer ◽  
Virtual Power ◽  
Integer Quadratic Programming ◽  
Virtual Power Plants ◽  
Mixed Integer Quadratic Programming ◽  
The Impact

As distributed energy resources (DERs) proliferate power systems, power grids face new challenges stemming from the variability and uncertainty of DERs. To address these problems, virtual power plants (VPPs) are established to aggregate DERs and manage them as single dispatchable and reliable resources. VPPs can participate in the day-ahead (DA) market and therefore require a bidding method that maximizes profits. It is also important to minimize the variability of VPP output during intra-day (ID) operations. This paper presents mixed integer quadratic programming-based scheduling methods for both DA market bidding and ID operation of VPPs, thus serving as a complete scheme for bidding-operation scheduling. Hourly bids are determined based on VPP revenue in the DA market bidding step, and the schedule of DERs is revised in the ID operation to minimize the impact of forecasting errors and maximize the incentives, thus reducing the variability and uncertainty of VPP output. The simulation results verify the effectiveness of the proposed methods through a comparison of daily revenue.

Short-Term Forecasting of Uncertain Parameters for Virtual Power Plants

2021 ◽  
Author(s):  
Mahdi Abbasi ◽  
Amirabbas Asadi ◽  
Seifeddine BenElghali ◽  
Mohamed Zerrougui
Keyword(s):  
Power Plants ◽  
Uncertain Parameters ◽  
Virtual Power ◽  
Short Term ◽  
Virtual Power Plants ◽  
Short Term Forecasting
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