Optimal Design of Biomass Combined Heat and Power System Using Fuzzy Multi-Objective Optimisation: Considering System Flexibility, Reliability, and Cost

Asni, Tommy; Andiappan, Viknesh

doi:10.1007/s41660-020-00137-4

Cited by 13 publications

(9 citation statements)

References 44 publications

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“…By transferring to linear programming sub‐problem drives, the sensitivity analysis of candidate Pareto solutions was done for the selection of new solutions with robustness requirements. Asni and Andiappan 33 have performed a multiple objective fuzzy optimization mode for synthesizing the ideal biomass CHP design assuming the system cost, flexibility, and dependability. Inspired by the concept of reliability emphasis, the presented work expressed dependability linearly unlike the complex, nonlinear expressions created in the past.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

Multiobjective optimization model for renewable energy sources and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems

Elango¹,

Arumugam²,

Umasankar³

2022

Intl J of Energy Research

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Summary This article proposes a multiobjective optimization model for renewable energy sources (RESs) and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems (CCHP). The hybrid CCHP system contains turbine, photovoltaic/thermal collectors, cooler/heater, supply setup, battery, and tank storage. The proposed hybrid method is the joint implementation of Garra Rufa Fish Optimization (GRFO) and Student Psychology Optimization Algorithm (SPOA); hence, it is named GRFO‐SPOA approach. An energy converters energy‐hub model along storage devices considers the properties of component of off‐design. The uncertainty of solar radiation together with building loads is exhibited at parametric manner and probability distributions. Assuming the uncertainty with system reliability and hybrid CCHP is enhanced to attain the feasible energetic, economic, and environmental benefit utilizing the GRFO‐SPOA method. To predict a new set, the GRFO‐SPOA method utilizes current datasets in the uncertainty modeling. The decision variables involves capacity of gas turbine and photovoltaic/thermal collectors, capacity of battery with water storing tank, and operational ratio of heat pump. The proposed method is implemented in MATLAB/Simulink; its efficiency is analyzed with other existing methods, like GA, SSA, and TSA technique. Once the confidence level of the system diminishes as of 0.99 to 0.50, the hybrid CCHP likened with traditional separate production system saves on average 13.7% of main energy and lessens 80% of acid gas emissions carbonic. The annual value saving rate is decreased because the confidence level of the system decreases and the uncertainty maximizes. The sensitivity analysis of the economist frontiers is executed on key economic parameters; therefore, it is obtained as an outcome of annual value saving rate is very sensitive to the value of fossil fuels, and the value of inversion of the star collectors has a stronger impact than that of turbine. The fist‐order statistical evaluation parameters, like mean, median, and SD, at 100 iterations for proposed technique is 0.61038, 0.5317, and 0.00543. Computation time utilizing 100, 150, 200, 250, and 500 trails of proposed technique is 48.1740 seconds, 51.2133 seconds, 71.0483 seconds, 60.00126 seconds, and 57.80132 seconds.

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Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

Multiobjective optimization model for renewable energy sources and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems

Elango¹,

Arumugam²,

Umasankar³

2022

Intl J of Energy Research

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“…Many techniques exist to address these utility issues, but most of them inject the harmonics into the supply system due to improper switching techniques. Also, in most of the locations at the utility end, these techniques are not available, resulting in excess energy consumption (Asni and Andiappan 2020). Harmonics are electromagnetic pollution that results in severe consequences for electrical systems (Jain et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-Based Optimization of Static Var Compensator–Injected Harmonics and System Currents of an Unbalanced Distribution Network

Bagwan

Korachagaon

Mulla

2021

Process Integr Optim Sustain

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In power distribution network, more and more people are worried about equipment failures and malfunctions caused by fluctuating loads and system harmonics due to poor power quality. The presence of harmonics can shorten the equipment's service life. There is a strong link between the energy use and the environment. Major part of power demand is supplied from thermal power stations which produce more carbon emissions as the power plant uses more fuel to generate the electricity. The effective utilization of transformer capacity is achieved by minimizing system losses and improving voltage regulation in the distribution system. Many techniques are used to address this issue, ranging from several power factor correction systems to passive and active harmonic filtering. Although distribution static compensator (DSTATCOM) is a perfect solution to solve this problem, they are expensive and have more complexity as a view against static var compensators (SVCs). This study aims to provide optimal approach for SVC switching in unbalanced operation of the distribution networks. In present work, the SVC is arranged in thyristor binary switched capacitors (TBSC)-thyristor-controlled reactor (TCR) configuration. The capacitor banks are set in binary sequence, and the optimal size reactor is decided. The TCR in SVC inherently generates the harmonics. The fuzzy logic approach is used to solve this non-linearity by determining the optimal triggering delay angle of the thyristor in TCR. This results in significant reduction in harmonics injected by the SVC. The strategy is appealing to improve efficiency of power distribution networks and thereby save natural resources required to generate electricity from thermal power stations.

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“…Nowadays, CHP plants are a widely used commercial technology [8]. Different alternative fuels [9][10], like biomass [11] and hydrogen [12], are decreasing the environmental impact of these devices [13] [14].…”

Section: Introductionmentioning

confidence: 99%

How residential CHPs could be integrated in renewable energy communities’ incentive schemes

et al. 2021

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The present work aims to investigate the integration into renewable energy communities (REC) schemes of micro and mini- Combined Heat and Power (CHP) plants. In detail, it has been evaluated the minimum self-consumption (SC) share needed to even out the revenues coming from the energy efficiency certificates (EECs). In order to establish a SC based tariff for CHP plants a correlation between SC share and the tariff value has been assessed for different commercial plants. A 70% of SC share has been set as a minimum target, which is related to incentive rates of 53 and 39.5 €/MWh, for mini and micro-CHPs, respectively. These values are about 65% lower than the current tariffs set by ARERA (Italian Regulatory Authority for Energy, Networks and Environment) to reward the renewable energy SC. A real building and two CHP plants have been considered as reference case studies. A dynamic simulation has been carried out in order to analyse the proposed incentive scheme in a real application. Starting from a 3-D BIM model, the energy flows have been calculated over one year period. Finally, it has been demonstrated how a SC based tariff can significantly reduce the share of injected electricity into the grid, also promoting the thermal carrier sharing. In so doing, the renewable energy sources intermittency can be easily mitigated and balanced, avoiding additional burdens on public expenditure.

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Optimal Design of Biomass Combined Heat and Power System Using Fuzzy Multi-Objective Optimisation: Considering System Flexibility, Reliability, and Cost

Cited by 13 publications

References 44 publications

Multiobjective optimization model for renewable energy sources and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems

Multiobjective optimization model for renewable energy sources and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems

Fuzzy-Based Optimization of Static Var Compensator–Injected Harmonics and System Currents of an Unbalanced Distribution Network

How residential CHPs could be integrated in renewable energy communities’ incentive schemes

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