Enhancing DC microgrid performance through machine learning-optimized droop control

A machine learning-based optimized droop method is suggested here to simultaneously reduce the production cost (PC) and power line losses (PLL) for a class of direct current (DC) microgrids (MGs). Traditionally, a communication-less technique known as the hybrid droop method has been employed to decrease PC and PLL in DC MGs. However, achieving the desired reduction in either PC or PLL requires arbitrary adjustments of weighting coefficients for each distributed generator in the conventional hybrid droop method. To address this challenge, this paper introduces a systematic approach that capitalizes on the benefits of artificial intelligence to accurately predict both the PC and PLL in a DC MG. Furthermore, an optimization technique relying on the gradient descendent method is employed to independently optimize both PC and PLL for each scenario. The effectiveness of the proposed method is confirmed through a comparative study with classical and hybrid droop coordination schemes under various scenarios such as rapid load changes.© 2024 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivsLicense, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.fi=vertaisarvioitu|en=peerReviewed

Inactivation of Coliforms in Sludge Through Cavitation Phenomena by Ultrasonic Waves

Background: One of the most challenging and critical processes in wastewater treatment is sludge treatment. This study aimed to investigate the effects of low frequency ultrasound and high level of energy on inactivation rate of total coliform of sludge and ascertain the optimal operating parameters of the ultrasound waves.Methods: In this research, the density of ultrasound (W/mL) and time (minutes) were investigated. The effect of these parameters on the inactivation of total coliform in sludge was also investigated.Results: The results revealed that the optimum operating time and ultrasound density were 30 minutes and 2.5 W/mL, respectively. Also, the frequency of 20 kHz of total coliform removal rate in these conditions was 99.44% .Conclusion: Ultrasound waves as well as micro and nano bubbles could remove total coliform and decontaminate the sludge, thereby incrementing the rate of treatment

Spatiotemporal and estimation of washed out seaweeds biomass in Sistan and Baluchistan coasts

In order to studing and determination of Seaweed biomass in the Oman Sea coast (Sistan & Baluchestan Province), according to obtained reasults and experiments and observations on seaweed studies in 15 years ego, Beris, Chabahar, Pozm and Tang were high density zones and Jood and Lipar were low density zones in west and east of chabahar respectively that were selected for study stations. Total length of sistan and balochistan coasts from Gwatr area with geografical position 25˚ 10′ N & 61˚ 30′ E to Mydani with geografical position 25˚ 24′ N & 59˚ 5′ E were 354.3 Km. Among this length, 54.6 Km were rocky coast and 299.7 Km were sandy coast. Among this, 18.2 Km were high density zone and 281.5 Km were low density zone. Washout Seaweeds area in intertidial zones determind by measuring and recording of geographic positions by meter and GPS, then were obtained 2 transects determind with equal distance in high density area and 1 transects in low density for monthly sampling. The length of these transects were 100 meter and cross of Each transects were seaweed washed out average. The transects divided to 10 bluck and sampling were done randomly monthly from 5 bluck or 50 persent. The samples were transfered to the lab and the weight of each species was obtained after being cleaned, and separating. The biomass of each species per area unit and in the total area was obtained after determing the average weight of species and also determind geografical position by GPS. In relation to this project were done water sampling for recording of fisical chemistry factors. Total data for analysis recorded in this computer. During this research 9 species were collected. Among these seaweeds, 2 species green algea (composed of 2 families and 2 orders), 6 species brown algae (composed of 3 families and 3 orders) and 1 species red algae were identified. Wet biomass of Sargassum in the total area of Sistan & Baluchestan coasts were 445.9 ton in 2012. Among this biomas, 269.1 ton (%60.35) high density area (Beris 112 ton or %25.11, Pozm 83.7 ton or %18.76, Chabahar 59 ton or %13.22 and Tang 14.5 ton or %3.26) and low density zone 176.8 ton (%39.65). Monthly average were estimated about 74.3 ton (high density zone 44.9 and low density zone 29.5 ton). The maximum biomass was obtained 270.4 ton (high density zone 155.5 and low density zone 114.9 ton) in Azar and minimum biomass was obtained 3.5 ton in Esfand. At last, were suggested, This project were done in persian gulf coasts nessesery