Coordinated power management and control of renewable energy sources based smart grid

Malla, Siva Ganesh; Malla, Jagan Mohana Rao; Malla, Priyanka; Ramasamy, Sreekanth; Doniparthi, Satish Kumar; Sahu, Manoj Kumar; Subudhi, Pravat Kumar; Awad, Hilmy

doi:10.1515/ijeeps-2021-0113

Cited by 43 publications

(9 citation statements)

References 28 publications

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“…On 12 appliances, the current and planned hybrid models were used to improve power usage for numerous homes. The proposed methods (HGWA) performed better than the existing mechanisms (ACO [11], MILP, ILP and NILP [12,13], respectively) proposed approach. An efficient way to schedule home appliances is with HGWA.…”

Section: Contributionsmentioning

confidence: 90%

Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

Irfan¹,

Hassan²,

Althobiani³

et al. 2023

Computer Systems Science and Engineering

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The smart grid has enabled users to control their home energy more effectively and efficiently. A home energy management system (HEM) is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy. Here, we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm (GWA) and Harmony Search Algorithms (HSA). Moreover, a fusion initiated on HSA and GWA operators is used to optimize energy intake. Furthermore, many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge. Hybridization has proven beneficial in achieving numerous objectives simultaneously, decreasing the peak-to-average ratio and power prices. Widespread MATLAB simulations are cast-off to evaluate the routine of the anticipated method, Harmony GWA (HGWA). The simulations are for a multifamily housing complex outfitted with various cool gadgets. The simulation results indicate that GWA functions better regarding cost savings than HSA. In reputes of PAR, HSA is significantly more effective than GWA. The suggested method reduces costs for single and ten-house construction by up to 2200.3 PKR, as opposed to 503.4 in GWA, 398.10 in HSA and 640.3 in HGWA. The suggested approach performed better than HSA and GWA in PAR reduction. For single-family homes in HGWA, GWA and HSA, the reduction in PAR is 45.79%, 21.92% and 20.54%, respectively. The hybrid approach, however, performs better than the currently used nature-inspired techniques in terms of Cost and PAR.

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Section: Contributionsmentioning

confidence: 90%

Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

Irfan¹,

Hassan²,

Althobiani³

et al. 2023

Computer Systems Science and Engineering

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“…However, these authors did not consider RES at different locations, implying that all sources are connected to common AC/DC buses with respective converters. A smart distribution grid architecture with a network of Microgrids, presenting a cost-optimal model, has been proposed [27], and a smart grid connecting RES at various locations with an implemented battery management system has been established [28]. A novel smart grid control alongside a battery energy management system (BEMS), aiming to provide reliable and high-quality power to multiple load buses.…”

Section: Related Workmentioning

confidence: 99%

Design and control of LSTM-ANN controllers for an efficient energy management system in a smart grid based on hybrid renewable energy sources

Wesley,

Babu,

Kumar

2024

Eng. Res. Express

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Many isolated locations, including hilly areas, remote sites, and military camps, lack feasible access to the main power grid. In these conditions, locally established Microgrids can provide the necessary power supply. However, to meet the demands of these isolated areas, numerous individual Microgrids are required. Although some of these Microgrids might be integratable, geographical constraints may preclude full integration. Under these circumstances, the establishment of a smart grid – integrating multiple Microgrids with a battery management system – can potentially solve many power supply issues. A smart grid control system paired with a centralized battery management system is proposed in this paper. The system considers the use of multiple renewable energy sources at various locations for stable and reliable power generation. The proposed method incorporates a long short-term memory (LSTM)-based artificial neural network (ANN) to ensure a stable, high-quality power supply at different load buses. Additionally, this work introduces an artificial intelligence-based operating system designed to maintain energy management under various conditions. To enhance voltage quality, a 7-level aligned multilevel inverter is incorporated into the system. As compared with PI and Fuzzy controllers, the proposed method with LSTM-ANN controller is improved the power quality under sudden changes in the system which are also presented in results. The effectiveness of the proposed energy management system (EMS) is verified by using a hardware-in the-loop approach with OPAL-RT modules, yielding realistic results.

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“…This new grid can replace the existing one, which is manual that lacks any connection between the technology and the electricity supplier (Reka et al 2021). SGs enable more effective management of energy resources by using digital technology to monitor changes in the supply and demand of power in real-time (Malla et al 2022). The global adoption of SG aims to decrease emissions from conventional sources, increase energy efficiency and guarantee consistent availability of renewable energy.…”

Section: Secure Smart Grids (Sgs)mentioning

confidence: 99%

Review on smart grids and renewable integration: An artificial intelligence-powered perspective

Nagappan,

Chaudhary,

Doda

et al. 2024

Multidiscip. Rev.

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Micro-grids have been rising as a component of the smart grid (SG), power management systems and integrating renewable energy sources (RES). The integration of various distributed components such as modern measuring facilities, connectivity and electric transportation, are causing an exciting change in the grid around the world. The purpose of this transformation is to advance the subsequent power systems’ dependability, renewable energy management and security. In this study, we offer a systematic review of innovative (artificial intelligence AI) approaches for supporting diverse demands in a distributed SG. In particular, we examine the way that artificial approaches can help with the integration of RES, SG and power management. We also address how AI can contribute to enhancing the general social welfare of the SG, considering it encompasses a variety of consumers, including energy producers, industries and consumption. Lastly, we provide additional studies for the significant coordination, along with the integration of autonomous separated devices that highlight several unresolved issues and future directions, to construct an incredible SG.

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Coordinated power management and control of renewable energy sources based smart grid

Cited by 43 publications

References 28 publications

Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

Design and control of LSTM-ANN controllers for an efficient energy management system in a smart grid based on hybrid renewable energy sources

Review on smart grids and renewable integration: An artificial intelligence-powered perspective

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