Improving sustainability development in energy planning and optimisation

Nemet, Andreja; Klemeš, Jiří Jaromír; Duić, Neven; Yan, Jinyue

doi:10.1016/j.apenergy.2016.10.111

Cited by 19 publications

(6 citation statements)

References 65 publications

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“…On the other hand, if optimization takes place for a supply chain, individual technologies are often simplified and considered as black box operations. More examples for optimizing biomass-based energy production can be found in [20].…”

Section: Biomass-based Energy Supplymentioning

confidence: 99%

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Éles,

Heckl,

Cabezas

2024

Energies

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In this work, a modeling technique utilizing the P-Graph framework was used for a case study involving biomass-based local energy production. In recent years, distributed energy systems gained attention. These systems aim to satisfy energy supply demands, support the local economy, decrease transportation needs and dependence on imports, and, in general, obtain a more sustainable energy production process. Designing such systems is a challenge, for which novel optimization approaches were developed to help decision making. Previous work used the P-Graph framework to optimize energy production in a small rural area, involving manure, intercrops, grass, and corn silage as inputs and fermenters. Biogas is produced in fermenters, and Combined Heat and Power (CHP) plants provide heat and electricity. A more recent result introduced the concept of operations with flexible inputs in the P-Graph framework. In this work, the concept of flexible inputs was applied to model fermenters in the original case study. A new implementation of the original decision problem was made both as a Mixed-Integer Linear Programming (MILP) model and as a purely P-Graph model by using the flexible input technique. Both approaches provided the same optimal solution, with a 31% larger profit than the fixed input model.

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Section: Biomass-based Energy Supplymentioning

confidence: 99%

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Éles,

Heckl,

Cabezas

2024

Energies

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“…Increasing uncertainty in energy flow in power grids today is due to intermittent production of renewable resources and time-varying load (Ashfaq and Ianakiev, 2018;Ludin et al, 2018;Liu et al, 2019;Peng et al, 2019;Sun et al, 2019). Therefore, power grids are facing a period of change caused by many issues such as reliability (Schienbein and DeSteese, 2002;Islam et al, 2015) and expansion of the power system (Carrano et al, 2007), power quality improvement (Short, 2018), load growth management (Das et al, 2013a;Hossain et al, 2015;Van Der Stelt et al, 2018;Mousavi et al, 2019), penetration of renewable resources (Das and Alam, 2012;Das et al, 2013b;Das et al, 2016;Yan et al, 2017), and minimization of greenhouse gas emission (Mazumder et al, 2014;Nemet et al, 2016). Incorporating battery energy storage (BES) in the distribution system is rapidly increasing to provide many benefits to environmental, technical, and economic issues (Das et al, 2018a;Das et al, 2018b).…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of a wind turbine and battery energy storage systems in distribution networks based on the modified BES-optimizer

Kamel

Abdel-Mawgoud²,

Alrashed³

et al. 2023

Front. Energy Res.

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Recently, incorporating renewable energy resources (RERs) like wind turbines (WTs) in a distribution network is rapidly increased to meet the load growth. However, distribution networks have been facing many challenges to withstand the intermittent output power of RERs. Battery energy storage (BES) is used with RERs to smoothly inject the output power to the grid by RERs. Therefore, this paper proposes an effective strategy for optimal allocation of WT and BES in RDS to decrease the total system losses. In addition, a modified bald eagle search (BES-optimizer) is proposed to obtain the preferable allocations of WT and BES simultaneously in the radial distribution system (RDS) considering the probabilistic distribution of the WT and load demand. IEEE 69-bus RDS is utilized as a test system. Based on the obtained results, installing WTs with BES gives better results than installing WTs alone in the RDS. However, the proposed algorithm proved its efficiency to obtain the best global results compared with other well-known techniques.

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“…Though conventional energy sources are primary sources due to accessibility and amplitude [5], a change is evident and needed as the global need for energy is estimated to continuously grow [4] [7] [8]. Despite the fact that the global energy sector is exceptionally complex and challenging to balance due to economic, environmental, political, and social dynamics [9], the use of renewable energy sources has grown, and for example, in 2017, 17.5% of the energy consumed in the EU was derived from renewable energy sources [10].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of a Renewable Energy System for Rural Electrification

David¹,

Uzorka²,

Makeri³

2022

JPEE

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Anaerobic digestion systems have been implemented on a number of rural farms all over the world as manure management solutions. Electricity and heating are also provided by means of such systems. In these systems, biomass waste is anaerobically digested to produce biogas, which is then burned in a boiler or an engine generator set to generate heat or power, depending on the system. The size and method of operation of a cattle waste-to-energy conversion system that would yield the highest revenue for a specific number of cattle are calculated in this study. An optimization method for Tabu Search is applied. The best answer is determined after several top-notch ones have been produced. The efficiency of a system for converting cattle waste into energy will help to increase rural electricity in Uganda.

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Improving sustainability development in energy planning and optimisation

Cited by 19 publications

References 65 publications

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Optimal allocation of a wind turbine and battery energy storage systems in distribution networks based on the modified BES-optimizer

Optimisation of a Renewable Energy System for Rural Electrification

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