Optimal energy storage sizing using equivalent circuit modelling for prosumer applications (Part II)

Pham, Cong-Toan; Månsson, Daniel

doi:10.1016/j.est.2018.04.015

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…f -chart method for solar thermal energy [52]), to simple brute force approaches (e.g. [53,54]) to very sophisticated methods (e.g. [55][56][57]).…”

Section: Optimal Sizingmentioning

confidence: 99%

Development of a Decision-Making Framework for Distributed Energy Systems in a German District

Schmeling¹,

Schönfeldt²,

Klement³

et al. 2020

Preprint

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The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

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“…f -chart method for solar thermal energy [52]), to simple brute force approaches (e.g. [53,54]) to very sophisticated methods (e.g. [55][56][57]).…”

Section: Optimal Sizingmentioning

confidence: 99%

Development of a Decision-Making Framework for Distributed Energy Systems in a German District

Schmeling¹,

Schönfeldt²,

Klement³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The structure and parameters of optimal-fuzzy were tuned using a brute-force heuristic algorithm as the optimization method. The brute force algorithm has been successfully used as an optimization technique in other applications, and it is the best learning method based on a set of small number of inputs and outputs (Pham & Månsson, 2018). However, no previous studies have used brute force with fuzzy logic techniques to find the best solution or set a strategy EMS for BEVs.…”

Section: Introductionmentioning

confidence: 99%

Integrating Fuzzy Logic and Brute Force Algorithm in Optimizing Energy Management Systems for Battery Electric Vehicles

Abdulsalam Abulifa,

Che Soh,

Hassan

et al. 2024

JST

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The limited driving range of BEVs is the main challenge in developing zero-emission Battery Electric Vehicles (BEVs) to replace traditional fuel-based vehicles. This limitation necessitates an increase in battery energy while balancing the power supply and consumption requirements for the vehicle’s motor and auxiliaries, such as the Heating, Ventilation, and Air Conditioning (HVAC) system. This research proposes a solution to achieve more efficient control of HVAC consumption by integrating fuzzy logic techniques with brute-force algorithms to optimize the Energy Management System (EMS) in BEVs. The model was based on actual parameters, implemented using MATLAB-Simulink and ADVISOR software, and configured using a backward-facing design incorporating the technical specifications of a Malaysian electric car, the PROTON IRIZ. An optimal solution was proposed based on the Satisfaction Ratio (SR) and State of Charge (SoC) metrics to achieve the best system optimization. The results demonstrate that the optimized fuzzy EMS improved power consumption by 23.2% to 26.6% compared to a basic fuzzy EMS. The proposed solution significantly improves the driving range of BEVs.

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“…In [15], the authors investigate the self-consumption of Swedish single-family households/dwellings, providing a sensitivity analysis of PV installation and battery of different sizes. In [16], an optimal storage system sizing based on equivalent circuit modeling is proposed, where the main goal is to balance solar production and load demand. In [17], a technical approach based on the optimization of the selfsufficiency is proposed to size PV-battery systems.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Smart Charging and Battery Energy Storage System for a PV Prosumer with an EV

Calearo

Ziras

Sevdari

et al. 2021

2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)

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Battery energy storage systems (BESSs) for residential photovoltaic (PV) prosumers are becoming more popular with the reduction of battery prices, as a means of increasing self-consumption. When considering prosumers that also own an electric vehicle (EV), smart charging can also fulfill the same objective. This paper assesses the benefits of a PV prosumer with an EV under two options: installing a BESS or applying smart charging. Smart charging is applied with the goal of reducing energy imports by charging the EV when there is excess of production. The effect of using a BESS of varying inverter and storage size is also investigated, when operated under a simple energy import minimization logic. We use a yearly dataset of real 5-min measurements collected from a Danish household with a 6 kWp PV plant. The prosumer also owns a 62 kWh Nissan LEAF. We find that smart charging increases self-consumption from 29% to 54%, leading to yearly savings of 220 e . Through a sensitivity analysis we find that a BESS of 8 kWh / 2 kW yields similar yearly results. Given the approximately 20 times higher payback period of the BESS, we conclude that smart charging is economically much more attractive.

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Optimal energy storage sizing using equivalent circuit modelling for prosumer applications (Part II)

Cited by 11 publications

References 13 publications

Development of a Decision-Making Framework for Distributed Energy Systems in a German District

Development of a Decision-Making Framework for Distributed Energy Systems in a German District

Integrating Fuzzy Logic and Brute Force Algorithm in Optimizing Energy Management Systems for Battery Electric Vehicles

Comparison of Smart Charging and Battery Energy Storage System for a PV Prosumer with an EV

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