Technical losses computation for short-term predictive management enhancement of grid-connected distributed generations

Kebir, Nisrine; Maâroufi, Mohamed

doi:10.1016/j.rser.2017.03.122

Cited by 9 publications

(5 citation statements)

References 33 publications

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“…The integration of DER into electric grids has emerged as a critical strategy for enhancing grid resilience, sustainability, and efficiency, with publications that address their impact on the grid dating back to the 1970s. The United States Public Utility Regulatory Policies Act (PURPA) [16] encouraged the development of renewable energy and cogeneration facilities by requiring electric utilities to purchase power from qualifying facilities, which included certain types of small-scale, decentralized power generation. This provision effectively incentivized the growth of customer-owned generation, as individuals or businesses could install renewable energy systems and sell excess electricity to utilities at favorable rates.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient Modeling of Distributed Energy Resources’ Impact on Electric Grid Technical Losses: A Dynamic Regression Approach

Aoun,

Adda,

Ilinca

et al. 2024

Energies

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Technical losses in electrical grids are inherent inefficiencies induced by the transmission and distribution of electricity, resulting in energy losses that can reach up to 40% of the generated energy. These losses pose significant challenges to grid operators regarding energy sustainability, reliability, and economic viability. Distributed Energy Resources (DERs) offer promising solutions to lower technical losses by decentralizing energy generation and consumption, reducing the need for long-distance transmission and optimizing grid operation. Hence, estimating the impact of DERs on grid technical losses becomes paramount for grid operators and planners. In response, this article proposes the application of regression modeling and nonlinear curve fitting algorithms to provide a more nuanced understanding and better characterize the intricate interplay between DER deployment and technical losses. Through a comprehensive case study based on more than 1080 computer simulations, we demonstrate the effectiveness of our proposed dynamic polynomial varying coefficient regression model in estimating the impact of DERs on technical losses within electrical grids. The proposed model offers a simple and effective methodology that allows grid operators to gain insights into the nonlinear dynamics of DER integration and make quicker and more informed decisions regarding grid management strategies, infrastructure investments, and policy interventions. Also, this research contributes to advancing the field of grid optimization by offering a simple equation that enhances our ability and haste to assess and mitigate technical losses in the context of an evolving energy landscape characterized by increasing DER adoption.

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Section: Literature Reviewmentioning

confidence: 99%

Efficient Modeling of Distributed Energy Resources’ Impact on Electric Grid Technical Losses: A Dynamic Regression Approach

Aoun,

Adda,

Ilinca

et al. 2024

Energies

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“…The equations used to forecast PVPS production and BESS SOC are defined in [6]. In what concerns the BG production, it is usually planned in advance by the producer.…”

Section: Algorithm Inputs Definitionmentioning

confidence: 99%

“…In what concerns the BG production, it is usually planned in advance by the producer. Regarding the method employed for load demand forecast, which represents the reference value of the MPC system, it has been introduced in [6]. The equations used in this method involve historical database, day type impact (special/ normal day) and weather conditions particularity.…”

Section: Algorithm Inputs Definitionmentioning

confidence: 99%

“…production is predicted-the PVPS production was calculated theoretically [6], assuming that temperature and irradiance forecast are perfect. In what concerns the power factor at the PCC of the PVPS, we considered it equal to the power factor at the instant t-1 for reactive energy computation.…”

Section: Scenario 3: Load Demand Prediction Is Perfect and Pvpsmentioning

confidence: 99%

“…Conversely, they ignored the impact of weather changes on forecast accuracies while building up their assumptions [4][5]. For the PVPS production prediction, a survey on the existing approaches to forecast solar irradiance has been done in [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Untitled

2019

JESTR

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The energy flow management in distribution networks started to worry grid operators since the challenge of exploiting natural resources such as solar irradiance and wind speed to produce electricity became a reality. Due to their intermittent nature, mismanagement of these resources can result in a severe bidirectional energy flow; likewise, notable imbalances between demand and generation in the electrical lines. Consequently, this may engender excessive energy losses and could violate electrical component characteristics. However, a predictive management of these resources can allow for the forecast of the different existing electrical device regulations beside the energy needed to be produced by conventional generations in a vertically-integrated system. For that purpose, we present in this paper a Model Predictive Control approach applied on a distribution feeder connected to renewable distributed generators and supplied by a High Voltage/Medium Voltage substation through transmission lines. We associated to this model a regulating algorithm for energy optimization and cost minimization. The control strategy outputs are the active and reactive energy predicted to be injected by the substation into the feeder. Finally, we evaluated the accurateness of the proposed method and we identified the parameters that affect its precision error.

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Development of a novel solar energy need index for identifying priority investment regions: a case study and current status in Turkey

Eroğlu

2021

Environ Dev Sustain

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Technical losses computation for short-term predictive management enhancement of grid-connected distributed generations

Cited by 9 publications

References 33 publications

Efficient Modeling of Distributed Energy Resources’ Impact on Electric Grid Technical Losses: A Dynamic Regression Approach

Efficient Modeling of Distributed Energy Resources’ Impact on Electric Grid Technical Losses: A Dynamic Regression Approach

Untitled

Development of a novel solar energy need index for identifying priority investment regions: a case study and current status in Turkey

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