IoT driven framework based efficient green energy management in smart cities using multi-objective distributed dispatching algorithm

2021 ◽  
Vol 88 ◽  
pp. 106567
Author(s):  
Zhang Xiaoyi ◽  
Wang Dongling ◽  
Zhang Yuming ◽  
Karthik Bala Manokaran ◽  
A. Benny Antony
2021 ◽  
Vol 13 (14) ◽  
pp. 7865
Author(s):  
Mohammed Mahedi Hasan ◽  
Nikos Avramis ◽  
Mikaela Ranta ◽  
Andoni Saez-de-Ibarra ◽  
Mohamed El Baghdadi ◽  
...  

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Deyaa Ahmed ◽  
Mohamed Ebeed ◽  
Abdelfatah Ali ◽  
Ali S. Alghamdi ◽  
Salah Kamel

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.


2022 ◽  
Vol 307 ◽  
pp. 118241
Author(s):  
Mohamed Lotfi ◽  
Tiago Almeida ◽  
Mohammad S. Javadi ◽  
Gerardo J. Osório ◽  
Cláudio Monteiro ◽  
...  

2021 ◽  
pp. 2141004
Author(s):  
Lingling Zhu ◽  
Jie Fangi Shi ◽  
Yi Hai Shi ◽  
Hai Peng Xu ◽  
A. Shanthini ◽  
...  

Energy is now seen as a significant resource that develops abundant on the world economy, with short supply and development. A study found that renewable energy systems are needed to prevent shortages. Hence, all the focus in this study to decrease electricity consumption and reduce the overall completion times for a regular console in green technology networks was an efficient and scalable production genomic solution. A Renewable green energy resources smart city (RGER-SC) framework is proposed that used a multi-target evolutionary algorithm was hybridized to be effective and calculated arithmetically in this study. This work deals with fostering renewable energy incorporation by adjusting federal charges to increase the energy accounting practitioners. Besides, this report analyses the timely generation of delay-tolerant demands and the maintenance of district heating at network infrastructure. In comparison, capacity differentials between consumers and information centres are considered and evaluated using the Renewable green energy resources smart city (RGER-SC) framework for energy conservation and controlled task management at an industrial level.


2018 ◽  
Vol 61 ◽  
pp. 00014
Author(s):  
Lluc Canals Casals ◽  
Lucía Igualada ◽  
Cristina Corchero

Smart buildings are a key element to walk towards smart cities and grids. Nonetheless, there are several degrees of intelligence. A first step is to incorporate commercial self-consumption solutions in buildings so they can manage the energy from local renewable power generators. A second step is to substitute this commercial solutions with an optimized Energy Management System (EMS) to reduce the electricity bill at the end of the month. Further. This EMS may contribute to stabilize and improve the quality and emissions of the electricity grid by offering some energy flexibility to the electricity system in favour of decentralization. This study compares the battery aging between buildings that count with an EMS to optimize the electricity bill under three scenarios in contrast to those that have a simple self-consumption kit. Lithium ion battery lifespan is estimated by means of an electric equivalent battery circuit model that runs on Matlab and simulates its behaviour through time. Moreover, this study evaluates the distribution of the battery costs regarding its use, observing that batteries controlled by simple self-consumption kits have longer lifespan because they are underused, ending up in higher calendar aging costs than the ones that are controlled by EMS.


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