Demand side management in Brazil: Brief history, lessons learned, status, challenges, and trends

Oliveira, Victor; Tenfen, Daniel; Fernandes, Rubipiara Cavalcante

doi:10.1016/j.rser.2023.113437

Cited by 8 publications

(3 citation statements)

References 69 publications

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“…The following part demonstrates the effectiveness of the proposed scheme by applying the standard IEEE 33-bus network for a variety of units. There are four DG units, two combined heat and power (CHP) agents, one WT agent, and one PV agent in the MG, and it has been linked to the utility by buses [1,20]. Figure 10 depicts a revised 33-bus IEEE MG, capable of buying or selling energy.…”

Section: Implementing the Suggested Scheme On The Standard 33-bus Iee...mentioning

confidence: 99%

“…Different distributed energy resources (DERs) can be integrated with a smart microgrid (MG) to address such problems. MGs consist of various loads and energy storage systems, as well as renewable and small-scale dispatchable energy systems like microturbines (MTs), photovoltaic (PV), wind turbines (WTs), diesel engine generators (DEs), fuel cell (FCs), and so on [1,2]. An important part of the smart grid system is the MG's energy production manner.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [1] applied four types of optimization methods in order to optimize MG: direct quest, particle swarm optimization, lambda logic, and iteration. Ref.…”

Section: Introductionmentioning

confidence: 99%

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The Innovative Research on Sustainable Microgrid Artwork Design Based on Regression Analysis and Multi-Objective Optimization

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One of the most vital issues in electrical systems involves optimally operating microgrids (MGs) using demand-side management (DSM). A DSM program lowers utility operational costs in one sense but also needs policies that encourage financial incentives in the other. The present study formulates the optimum functioning of MGs using DSM in the form of a problem of optimization. DSM considers load shifting to be a viable option. There are operational limitations and executive limitations that affect the problem, and its objective function aims at minimizing the overall operational prices of the grid and the load-shifting prices. The major problem has been solved using an improved butterfly optimization scheme. Furthermore, the suggested technique was tested in various case studies that consider types of generation unit, load types, unit uncertainties, grid sharing, and energy costs. A comparison was made between the suggested scheme and various algorithms on the IEEE 33-bus network to demonstrate the proficiency of the suggested scheme, showing that it lowered prices by 57%.

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Section: Implementing the Suggested Scheme On The Standard 33-bus Iee...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Domesticating energy flexibility. Learning from great britain’s 2022–2023 demand flexibility service

Mihalache,

Hampton,

Darby

2024

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Demand-response is essential for balancing electricity grids with increasing proportions of intermittent renewable sources of generation. Harnessing the potential for demand-response in domestic settings could deliver widespread benefits for electricity systems and householders. This study applies domestication theory to a major national domestic electricity demand-response programme in Great Britain, exploring how participants integrate demand-response sessions into their everyday routines. The study uses empirical data from twenty-five participants who completed diaries reflecting on their experience of taking part in thirteen demand-response sessions scheduled over a five-month period in winter 2022–23. The study identifies and analyses five pathways for domesticating demand-response, making recommendations to support system-actors in boosting and sustaining the adoption of demand-response. The study concludes that designing electricity demand-response programmes, as a staple of secure low-carbon energy systems, will need to take full account of users’ non-financial motivations, previous experiences of demand-response, and access to enabling technology.

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Robust energy management through aggregation of flexible resources in multi-home micro energy hub

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Demand side management in Brazil: Brief history, lessons learned, status, challenges, and trends

Cited by 8 publications

References 69 publications

The Innovative Research on Sustainable Microgrid Artwork Design Based on Regression Analysis and Multi-Objective Optimization

The Innovative Research on Sustainable Microgrid Artwork Design Based on Regression Analysis and Multi-Objective Optimization

Domesticating energy flexibility. Learning from great britain’s 2022–2023 demand flexibility service

Robust energy management through aggregation of flexible resources in multi-home micro energy hub

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