Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor

Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor

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In order to cater for fluctuating energy demand, power plants are designed either as base power plant or peak power plant. The advantage of base power plant is that due to its constant power generation, the power plant has a higher efficiency. To optimize and design a power plant, many previous study has been conducted. Among the studies, Power Pinch tool named Electric System Cascade Analysis (ESCA) was applied to design an optimal power system. ESCA analysis is conducted by assuming that the power plant generates constant power as it is more efficient. However, further analysis using ESCA shows that with a minimal power plant capacity would result in a trade-off that the energy storage system would be larger and leads to higher energy charging and discharging tendency (result in higher energy lost). Considering the time change of heat rate with the corresponding load factor, this study incorporates new algorithm for flexible power generation into the existing ESCA methodology. To validate the new algorithm, an off-grid distributed energy generation system is mathematically modelled and solved. The result from the new algorithm is compared with that of the mathematical model. The comparison of optimal generator capacity shows a difference of 5.71%. The similarity of the result hence validates that the new algorithm is suitable.

In order to cater for fluctuating energy demand, power plants are designed either as base power plant or peak power plant. The advantage of base power plant is that due to its constant power generation, the power plant has a higher efficiency. To optimize and design a power plant, many previous study has been conducted. Among the studies, Power Pinch tool named Electric System Cascade Analysis (ESCA) was applied to design an optimal power system. ESCA analysis is conducted by assuming that the power plant generates constant power as it is more efficient. However, further analysis using ESCA shows that with a minimal power plant capacity would result in a trade-off that the energy storage system would be larger and leads to higher energy charging and discharging tendency (result in higher energy lost). Considering the time change of heat rate with the corresponding load factor, this study incorporates new algorithm for flexible power generation into the existing ESCA methodology. To validate the new algorithm, an off-grid distributed energy generation system is mathematically modelled and solved. The result from the new algorithm is compared with that of the mathematical model. The comparison of optimal generator capacity shows a difference of 5.71%. The similarity of the result hence validates that the new algorithm is suitable.

Electric System Cascade Analysis (ESCA); Generation flexibility; Heat rate; Mathematical model; Energy management; Energy resources; Mathematical models; Cascade analysis; Distributed energies; Energy storage systems; Fluctuating energy; Generation flexibilities; Generator capacity; Heat rate; Higher efficiency; Economic and social effects

Electric System Cascade Analysis (ESCA); Generation flexibility; Heat rate; Mathematical model; Energy management; Energy resources; Mathematical models; Cascade analysis; Distributed energies; Energy storage systems; Fluctuating energy; Generation flexibilities; Generator capacity; Heat rate; Higher efficiency; Economic and social effects

Liu, W.H.; Lee, M.Y.; Hashim, H.; Lim, J.S.; Klemeš, J.J.; Wan Alwi, S.R.; Idris, A.M.; Ho, W.S.

2020

01.01.2019

Elsevier Ltd

ELSEVIER SCIENCE BV, SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS

INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS

Energy Procedia

1876-6102

Energy Procedia

158

Thajské království

4190

4197

8