Day Ahead Optimal Dispatch Schedule in a Smart Grid Containing Distributed Energy Resources and Electric Vehicles

Fotopoulou, Maria; Rakopoulos, Dimitrios C.; Blanas, Orestis

doi:10.3390/s21217295

Cited by 27 publications

(14 citation statements)

References 48 publications

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“…The azimuth is the compass angle of the sun, which moves from east to west over daytime, and the zenith is the angle of the sun looking up from the horizon or ground level (it varies throughout the day, roughly 0° at sunrise, 90° at midday, and 180° at sunset) [13]. In some countries, this method could allow cost reduction in terms of locating additional solar panels to increase the output since it could improve the electricity generation around 30-82% more than the fixed-angle PV system [11,14]. Furthermore, when combined with other renewable generators (e.g., wind turbines) and energy storage devices (e.g., batteries or electric vehicles), it can become an excellent model to improve the economic dispatch and provide a good energy management system that is able to minimize the grid energy costs [15,16].…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

et al. 2022

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Solar photovoltaic (PV) energy systems are one of the most widely deployed renewable technologies in the world. The efficiency of solar panels has been studied during the last few decades, and, to date, it has not been possible to displace the production of energy using crystalline silicon wafer-based technology whose efficiency has reached values around 26.1%. Moreover, using solar tracking PV systems has become a feasible alternative to increase the electric output of PV silicon technologies instead of using the conventional fixed PV installation on a flat or sloping surface. The following study has compared fixed and dual-axis sun-tracking PV panels in order to quantify the enhancement associated with the amount of energy harvested when using dual-axis tracking PV systems in the city of Manta, located in a coastal region of Ecuador. In order to carry out this study, an IoT monitoring system based on Raspberry Pi3 and Arduino platforms was used. Measurements of solar radiation (W/m2), light intensity (Lux), temperature (°C), short-circuit current (A), and open-circuit voltage (V) were taken every minute for both systems. The results prove that the dual-axis tracking PV system produces, on average, 19.62% more energy than the static PV system. These results present an 8.62% energy increase with respect to a previous study carried out in an equatorial region with similar characteristics to those of the city of Manta, where a one-axis tracking PV system was used.

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Section: Introductionmentioning

confidence: 99%

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

et al. 2022

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“…The adaptability and resilience of a microgrid (MG) are two of the desired features due to the multiple operational scenarios that the system can meet [1]. Because of this, the control requirements and strategies to perform local balancing and to maximize their benefits have led the MGs to fulfill a wide range of functionalities, such as power flow control, voltage and frequency regulation, among others [2][3][4]. In this way, the choice of control structure is important for the stable operation of microgrids, which is achieved by means of different control levels, also known as hierarchical controls [2].…”

Section: Introductionmentioning

confidence: 99%

“…For the islanded case, grid-forming controls, for example the droop control, are required to regulate the frequency and voltage of the microgrid [5]; however, these controls usually require the introduction of a secondary control to eliminate the steadystate errors [3]. On the other hand, the tertiary control is used to decide the operating point of each distributed generation unit (DG), i.e., energy management systems (EMS) [4], depending on the grid requirements and available energy. Therefore, the primary and secondary controls in microgrids are continually optimized by using upper control layers, such that, the operational objectives are continuously achieved in a reliable manner [3,6].…”

Section: Introductionmentioning

confidence: 99%

Stability Boundary Analysis of Islanded Droop-Based Microgrids Using an Autonomous Shooting Method

2022

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This paper presents a stability analysis for droop-based islanded AC microgrids via an autonomous shooting method based on bifurcation theory. Shooting methods have been used for the periodic steady-state analysis of electrical systems with harmonic or unbalanced components with a fixed fundamental frequency; however, these methods cannot be directly used for the analysis of microgrids because, due to the their nature, the microgrids frequency has small variations depending on their operative point. In this way, a new system transformation is introduced in this work to change the droop-controlled microgrid mathematical model from an non-autonomous system into an autonomous system. By removing the explicit time dependency, the steady-state solution can be obtained with a shooting methods and the stability of the system calculated. Three case studies are presented, where unbalances and nonlinearities are included, for stability analysis based on bifurcation analysis; the bifurcations indicate qualitative changes in the dynamics of the system, thus delimiting the operating zones of nonlinear systems, which is important for practical designs. The model transformation is validated through time-domain simulation comparisons, and it is demonstrated through the bifurcation analysis that the instability of the microgrid is caused by supercritical Neimark–Sacker bifurcations, and the dynamical system phase portraits are presented.

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“…By optimizing the charge/discharge profiles of the vehicle to grid (V2G) at a parking lot, microgrids can effectively handle and monitor V2G while maximizing the economic revenue and the satisfaction of vehicles stakeholders [ 1 , 2 ]. Due to the recent technological advances, governmental incentives, and modern battery development, EVs have been resurged.…”

Section: Introductionmentioning

confidence: 99%

Heuristic Greedy Scheduling of Electric Vehicles in Vehicle-to-Grid Microgrid Owned Aggregators

Abdel-Hakim

Abo‐Elyousr

2022

Sensors

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In on-grid microgrids, electric vehicles (EVs) have to be efficiently scheduled for cost-effective electricity consumption and network operation. The stochastic nature of the involved parameters along with their large number and correlations make such scheduling a challenging task. This paper aims at identifying pertinent innovative solutions for reducing the relevant total costs of the on-grid EVs within hybrid microgrids. To optimally scale the EVs, a heuristic greedy approach is considered. Unlike most existing scheduling methodologies in the literature, the proposed greedy scheduler is model-free, training-free, and yet efficient. The proposed approach considers different factors such as the electricity price, on-grid EVs state of arrival and departure, and the total revenue to meet the load demands. The greedy-based approach behaves satisfactorily in terms of fulfilling its objective for the hybrid microgrid system, which is established of photovoltaic, wind turbine, and a local utility grid. Meanwhile, the on-grid EVs are being utilized as an energy storage exchange location. A real time hardware-in-the-loop experimentation is comprehensively conducted to maximize the earned profit. Through different uncertainty scenarios, the ability of the proposed greedy approach to obtain a global optimal solution is assessed. A data simulator was developed for the purposes of generating evaluation datasets, which captures uncertainties in the behaviors of the system’s parameters. The greedy-based strategy is considered applicable, scalable, and efficient in terms of total operating expenditures. Furthermore, as EVs penetration became more versatile, total expenses decreased significantly. Using simulated data of an effective operational duration of 500 years, the proposed approach succeeded in cutting down the energy consumption costs by about 50–85%, beating existing state-of-the-arts results. The proposed approach is proved to be tolerant to the large amounts of uncertainties that are involved in the system’s operational data.

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Day Ahead Optimal Dispatch Schedule in a Smart Grid Containing Distributed Energy Resources and Electric Vehicles

Cited by 27 publications

References 48 publications

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

Stability Boundary Analysis of Islanded Droop-Based Microgrids Using an Autonomous Shooting Method

Heuristic Greedy Scheduling of Electric Vehicles in Vehicle-to-Grid Microgrid Owned Aggregators

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