Multi-objective optimal energy management of microgrids including plug-in electric vehicles with the vehicle to grid capability for energy resources scheduling

Abstract

As more battery electric vehicles and plug-in hybrid electric vehicles are connected to the microgrid, plug-in electric vehicles have a major impact on the microgrid. This paper proposes a multi-objective optimization energy management model including plug-in electric vehicles and other distributed generations. By analyzing the powertrain structure of different kinds of plug-in electric vehicles, the engine fuel consumption model, the charging model, the discharge model, and the battery state of charge model of plug-in electric vehicle in microgrids are given. The proposed model considers the plug-in electric vehicle battery state of charge constraints to prevent the battery from overcharging and over-discharging and gives the state of charge curve in microgrids. Simultaneously, an improved gray wolf algorithm, introducing optimization control factors and greedy strategies to better balance the mining and exploration capabilities of the gray wolf algorithm, is proposed to solve this multi-objective optimization energy management model. Compared with particle swarm optimization and traditional gray wolf algorithm, the improved algorithm further improves the accuracy and convergence speed. Besides, the improved algorithm is applied to three scheduling schemes, and the results show that plug-in hybrid electric vehicles have more advantages in energy economy in some special cases.

A Review on Vibrations in Electric and Hybrid Electric Vehicles

“…When switching from fifth to sixth gear, the seat-track acceleration amplitude was reduced by 24.11% Park et al [98] The beating idle vibrations in a vehicle were investigated in this study to evaluate changes in ride comfort to the amplitude ratio of two vibrations with similar frequencies and their beating frequency When the amplitude ratios between the beating vibrations were larger, ride comfort at most frequencies was weakened. When the pulse frequency fell below the 1e 4 Hz level, more discomfort was observed. When the beating vibrations had an amplitude ratio of 0.8 and a beating frequency between 1.0 and 2.0 Hz, the discomfort was 3.8 dB higher than sinusoidal single-frequency vibrations Hou et al [99] In order to efficiently extend the frequency spectrum and collect vehicle-induced vibration from various vibration peaks, three distinct types of four sub-module multi-frequency electromagnetic vibration energy harvesters (EM-VEHs) were built in this study.…”

“…Electric vehicles propelled by electric traction motors do not directly use any petroleum fuel, are quieter in operation, and require less maintenance and running costs [2]. In EVs, an electrically run motor known as a traction motor develops the vehicle's propulsion power according to the load requirements [3,4]. Comparing the cost analysis of electric vehicles with that of ICE vehicles, EVs get cheaper in every kilometre driven.…”

A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids

“…As previously stated in the paper, artificial intelligence-mainly machine and deep learning-is used in forecasting. As highlighted in the following papers [106][107][108][109][110][111][112][113][114][115][116][117][118], artificial intelligence, in particular artificial neural networks and fuzzy/neuro-fuzzy systems, can also be used in the management of MGs and NMGs. These papers are highlighted in the followings in order to give to the reader an overview on how AI is used in the domain.…”

“…The method shows good performance by reducing system costs. In [118], Jiao et al propose a multi-objective optimization energy management model for MGs with plug-in EVs and distributed generators. An improved gray wolf algorithm is proposed to solve this model.…”

Multi-microgrids system’s resilience enhancement

“…Hence, the most important challenge is making these microgrids efficiently cooperate and exchange power in case of system resilience [15]. Hence, this paper addresses this issue to smooth the progress of the DES' implementation [16], [17]. The principle of the multiagent system (MAS) has gained more use in recent years even for the management of centralized power systems or of the decentralized management and control strategy for distributed microgrids [18]- [20].…”