Optimal operation of energy hubs integrated with electric vehicles, load management, combined heat and power unit and renewable energy sources

Li, Ruihua; SaeidNahaei, Sanam

doi:10.1016/j.est.2021.103822

Cited by 31 publications

(16 citation statements)

References 28 publications

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“…The unpredictability of the generation of new forms of energy, which is caused by the variable levels of solar and wind power throughout the day, is the only thing standing in the way of their widespread use. In the research (Li and SaeidNahaei 2022), an optimal load dispatching design for an energy storage unit was examined. This was done with the goal of lowering the total costs associated with operating the energy hub, such as the costs associated with CO 2 emission.…”

Section: Control Mechanisms For Charging and Discharging The Batterymentioning

confidence: 99%

“…In addition, the strategy that is described takes into consideration the DR methods in great detail. In Li and SaeidNahaei (2022), three possible schedules are investigated, each of which has distinct charge/discharge and DR characteristics. The data, shown both numerically and graphically, suggest that using a strategy that coordinates charging and discharging of EVs is the most efficient way to lower total costs.…”

Section: Control Mechanisms For Charging and Discharging The Batterymentioning

confidence: 99%

See 1 more Smart Citation

Can electric vehicles be an alternative for traditional fossil-fuel cars with the help of renewable energy sources towards energy sustainability achievement?

et al. 2022

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The use of conventional fossil-fuel vehicles in the transportation industry contributes to climate change. The energy producing sector has actually adjusted its strategy to utilize more renewable energy to satisfy the energy demand as a result of this change in strategy. The use of electric vehicles (EVs) in the transportation network has also helped to reduce pollution from the energy industry. However, the distribution network would be placed under a lot of stress if a lot of EVs are attached to it, which might cause a number of problems and worries. However, several initiatives have been made in this direction to help find answers to these issues. The contribution of this review article is that, a number of the benefits of using the employed EVs techniques for the purpose of utilizing renewable energy sources (RESs) towards the accomplishment of a sustainable energy goal for a green environment in the so foreseeable have been highlighted; aiming to provide a larger variety of readers insights and suggestions for future research development. There have been a number of studies that have recommended various ideas and strategies for a reliable renewable energy supply. Their findings have been published in scientific journals. But the relationship between RESs and EVs in terms of energy efficiency is still needed to be further investigated to shorten such a gap in order to assess how EVs can help RESs achieve energy sustainability. Besides, the purpose of this study is to identify and assess the most recent advances and methodologies in the field. It's been possible to use numerous EV technologies to help with various problems and challenges, including the need for quick EV charging stations. However, there is a worry over the viability and applicability of EV-applied technologies that are ideally suited towards greater and more efficient usage of RESs in order to either attain or contribute to energy sustainability. In this article, we will discuss a variety of EV technologies that have been used in the past and contributed to the development of RESs. The method has applied the PRISMA 2020 strategy for inclusion and exclusion criteria. Also, the method has used specific keyword related to the topic including "electric vehicles" and "renewable energy sources". It is found that EVs can be an effective alternative for currently used fossil-fuel vehicles due to a set of reasons highlighted in this review including fast EV charging stations, efficient design for PV solar panels, and effective utilization of RESs.

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Section: Control Mechanisms For Charging and Discharging The Batterymentioning

confidence: 99%

Section: Control Mechanisms For Charging and Discharging The Batterymentioning

confidence: 99%

Can electric vehicles be an alternative for traditional fossil-fuel cars with the help of renewable energy sources towards energy sustainability achievement?

et al. 2022

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“…• day-ahead based approaches: [1]- [3], [7], [8], [10]- [25], [46]- [48], [50], [52], [55]; • deterministic approaches: [7]- [9], [13], [15], [17], [18], [20], [21], [26]- [35], [42], [44]- [46], [49]- [57]; • uncertainties management/stochastic approaches: [1],…”

Section: Related Workmentioning

confidence: 99%

“…[3], [10]- [19], [21], [23], [26]- [29], [34], [36]- [41], [44], [47]- [50], [52], [53], [55], [56]; • EV and V2G based approaches: [2], [7]- [9], [14], [15], [19], [23], [24], [31], [32], [35], [36], [49], [51]; • RES and/or ESS based approaches: [1]- [3], [7]- [42],…”

Section: Related Workmentioning

confidence: 99%

Smart District Energy Management With Cooperative Microgrids

2022

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This paper faces the energy management problem of cooperative microgrids in a smart energy district. In particular, the aim of the research work is to propose an innovative optimization model to solve the problem of energy management in a district composed of several microgrids, taking into account uncertainties of key parameters. In this context, the objective of the paper is threefold: i) maximize the use of energy purchased at the day-ahead market; ii) minimize the need of additional and expensive energy in realtime iii) optimize the integration of renewable energy sources (RES), energy storage systems (ESS) and electric vehicle (EV) batteries in the microgrid. To these goals, the District Energy Management System (DEMS), i.e. the central controller of the district, must balance the microgrids energy demand with the optimal integration of RES, ESS and the batteries of EVs that are seen as movable storage devices shared among buildings. Moreover, the energy surplus can be sold back to the main power grid. The DEMS problem is solved by two approaches. In the first approach, the energy demand, the RES production and the costs are known and a linear programming problem is formalized and solved by the DEMS. In addition, a second approach is proposed in order to address the parameters uncertainty and is formalized as a stochastic linear programming problem. The optimization problems solutions provide the optimal strategy to schedule the charging and discharging operations of the storage systems and the electric vehicle batteries. A simulation case study demonstrates the benefits of the proposed approaches for the smart district.

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“…The ESS placement is presented in [24] based on residential buildings by considering the mutual benefits of investors and users. Optimal load dispatch from the energy hub to reduce the total costs of the energy hub, i.e., exploitation and emission costs, is presented in [25]. The presented energy hub consists of combined heat and power (CHP), PV, wind turbine (WT), and EV.…”

Section: Costmentioning

confidence: 99%

Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

Zhang¹,

Yang²,

Li³

2022

Energy Engineering

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Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering the electric vehicles and demand response in smart homes. In this way, large power stations that work with fossil fuels will no longer be developed. The current study modeled and evaluated the performance of a smart house in the presence of electric vehicles (EVs) with bidirectional power exchangeability with the power grid, an energy storage system (ESS), and solar panels. Additionally, the solar RES and ESS for predicting solar-generated power prediction uncertainty have been considered in this work. Different case studies, including the sales of electrical energy resulting from PV panels' generated power to the power grid, time-variable loads such as washing machines, and different demand response (DR) strategies based on energy price variations were taken into account to assess the economic and technical effects of EVs, BESS, and solar panels. The proposed model was simulated in MATLAB. A hybrid particle swarm optimization (PSO) and gravitational search (GS) algorithm were utilized for optimization. Scenario generation and reduction were performed via LHS and backward methods, respectively. Obtained results demonstrate that the proposed model minimizes the energy supply cost by considering the stochastic time of use (STOU) loads, EV, ESS, and PV system. Based on the results, the proposed model markedly reduced the electricity costs of the smart house.

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Optimal operation of energy hubs integrated with electric vehicles, load management, combined heat and power unit and renewable energy sources

Cited by 31 publications

References 28 publications

Can electric vehicles be an alternative for traditional fossil-fuel cars with the help of renewable energy sources towards energy sustainability achievement?

Can electric vehicles be an alternative for traditional fossil-fuel cars with the help of renewable energy sources towards energy sustainability achievement?

Smart District Energy Management With Cooperative Microgrids

Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

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