Three‐level interactive energy management strategy for optimal operation of multiple virtual power plants considering different time scales

2020 ◽  
Vol 45 (1) ◽  
pp. 1069-1096
Author(s):  
Nan Li ◽  
Caixia Tan ◽  
Hongyu Lin ◽  
Xue Ma ◽  
Xiangcheng Zhang
Keyword(s):  
Energy Management ◽  
Time Scales ◽  
Management Strategy ◽  
Power Plants ◽  
Optimal Operation ◽  
Virtual Power ◽  
Energy Management Strategy ◽  
Virtual Power Plants ◽  
Different Time Scales

scholarly journals Systematic Categorization of Optimization Strategies for Virtual Power Plants

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6251
Author(s):  
Amit Kumer Podder ◽  
Sayemul Islam ◽  
Nallapaneni Manoj Kumar ◽  
Aneesh A. Chand ◽  
Pulivarthi Nageswara Rao ◽  
...  
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Power Distribution ◽  
Power Plants ◽  
Optimal Operation ◽  
Optimization Techniques ◽  
Virtual Power ◽  
Distributed Energy ◽  
Intelligent Technique ◽  
Virtual Power Plants

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

scholarly journals Electrified Powertrain with Multiple Planetary Gears and Corresponding Energy Management Strategy

Vehicles ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 341-356
Author(s):  
Daizy Rajput ◽  
Jose M. Herreros ◽  
Mauro S. Innocente ◽  
Joschka Schaub ◽  
Arash M. Dizqah
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Mode Selection ◽  
Optimal Operation ◽  
Fourth Generation ◽  
Selection Strategy ◽  
Energy Management Strategy ◽  
Planetary Gears

Modern hybrid electric vehicles (HEVs) like the fourth generation of Toyota Prius incorporate multiple planetary gears (PG) to interconnect various power components. Previous studies reported that increasing the number of planetary gears from one to two reduces energy consumption. However, these studies did not compare one PG and two PGs topologies at their optimal operation. Moreover, the size of the powertrain components are not the same and hence the source of reduction in energy consumption is not clear. This paper investigates the effect of the number of planetary gears on energy consumption under optimal operation of the powertrain components. The powertrains with one and two PGs are considered and an optimal simultaneous torque distribution and mode selection strategy is proposed. The proposed energy management strategy (EMS) optimally distributes torque demands amongst the power components whilst also controlling clutches (i.e., mode selection). Results show that increasing from one to two PGs reduces energy consumption by 4%.

scholarly journals Energy management of virtual power plants dependent on electro-economical model

2020 ◽  
Vol 11 (3) ◽  
pp. 643-649 ◽  
Author(s):  
Fatma El Zahraa Magdy ◽  
Doaa Khalil Ibrahim ◽  
Waheed Sabry
Keyword(s):  
Energy Management ◽  
Power Plants ◽  
Virtual Power ◽  
Virtual Power Plants

scholarly journals Optimal Operation Modes of Virtual Power Plants Based on Typical Scenarios Considering Output Evaluation Criteria

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2634 ◽  
Author(s):  
Jingjing Luo ◽  
Yajing Gao ◽  
Wenhai Yang ◽  
Yongchun Yang ◽  
Zheng Zhao ◽  
...  
Keyword(s):  
Power Plants ◽  
Clustering Algorithm ◽  
Evaluation Criteria ◽  
Operating Mode ◽  
Optimal Operation ◽  
Virtual Power ◽  
Model Case ◽  
Electricity Trading ◽  
Grid Connection ◽  
Virtual Power Plants

Stimulated by the severe energy crisis and the increasing awareness about the need for environmental protection, the efficient use of renewable energy has become a hot topic. The virtual power plant (VPP) is an effective way of integrating distributed energy systems (DES) by effectively deploying them in power grid dispatching or electricity trading. In this paper, the operating mode of the VPP with penetration of wind power, solar power and energy storage is investigated. Firstly, the grid-connection requirements of VPP according to the current wind and solar photovoltaic (PV) grid-connection requirements, and analyzed its profitability are examined. Secondly, under several typical scenarios grouped by a self-organization map (SOM) clustering algorithm using the VPP’s output data, a profit optimization model is established as a guideline for the VPP’s optimal operation. Based on this model, case studies are performed and the results indicate that this model is both feasible and effective.

An efficient method for energy management optimization control: Minimizing fuel consumption for hybrid vehicle applications

2019 ◽  
Vol 42 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Mohamed Elhedi Hmidi ◽  
Ines Ben Salem ◽  
Lilia El Amraoui
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Management Strategies ◽  
Hybrid Vehicle ◽  
Optimal Operation ◽  
Pollutant Emissions ◽  
Energy Management Strategy ◽  
The Impact

One of the main research areas of the automotive sector is energy consumption and the reduction of pollutant emissions. Therefore, the hybrid electrical vehicle Vehicle electrical hybrid (VEH) is a possible approach to improve the vehicle components or its architecture to maximize system efficiency. This vehicle benefits from levels of consumption and emission of pollutants lower than the thermal vehicle. The problem is then to find the right split power between the two hybrid sources, the internal combustion engine (ICE) and the electrical machines (EM) to minimize fuel consumption. These energy management strategies are the algorithms that achieve instant split power between the two sources in the hybrid electric vehicle (HEV) while controlling the battery state of charge (SOC), in order to improve the fuel economy and optimize the performance HEV. In this research, a parametric study on the impact of optimization of the energy management strategy on the optimal operation of the vehicle is presented. A hybrid vehicle model is described and rules-based energy management strategy is presented. Later these rules are optimized with an optimization algorithm based on Grey Wolf optimizer (GWO). It is a new meta-heuristic based on the population. The results of the simulation make it possible to deduce the impact of this optimal strategy of energy management on fuel consumption and CO2 emissions. The obtained results show that the optimal operation of the vehicle varies according to the best energy management strategies.

Risk-Constrained Optimal Energy Management for Virtual Power Plants Considering Correlated Demand Response

2019 ◽  
Vol 10 (2) ◽  
pp. 1577-1587 ◽  
Author(s):  
Zheming Liang ◽  
Qais Alsafasfeh ◽  
Tao Jin ◽  
Hajir Pourbabak ◽  
Wencong Su
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Power Plants ◽  
Virtual Power ◽  
Optimal Energy ◽  
Virtual Power Plants ◽  
Optimal Energy Management
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