Solving convex and non-convex static and dynamic economic dispatch problems using hybrid particle multi-swarm optimization

Nawaz, Aamir; Mustafa, Ehtasham; Saleem, Nasir; Khattak, Muhammad Irfan; Shafi, Muhammad; Malik, Abdul

doi:10.17559/tv-20150720093711

Cited by 1 publication

(1 citation statement)

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“…This research only considers coupling in the time domain through ramp rates constraints Equations ( 41) and (42). Ramp rates state what is the maximum possible change in a unit output over a period, where RU g represents the upper ramp rate limit of generators when generation must be increased due to an increase in load and RD g represents down ramp rate limit of generators when generation must decrease due to a decrease in load, P g,t is the current generation of the unit and P g,t−1 is the previous generation of the unit [35]. In addition, the operational constraints on the thermal units are given in where P min g is the minimum Active power generated by thermal unit and P max g (43).…”

Section: Dynamic Economic Dispatch (Ded)mentioning

confidence: 99%

Optimal Management of Seasonal Pumped Hydro Storage System for Peak Shaving

et al. 2023

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Power demand varies on a daily and seasonal basis. Responding to changing demands over time is challenging for energy suppliers as it causes expensive power plants to operate in high-demand seasons, usually summer, increasing the cost of electricity. Peak load shaving makes the load curve flatten by reducing the peak load and shifting it to times of lower demand, hence reducing the operation of expensive power plants. Hence, there is a need for large-scale and long-term ESS to store energy in the time of low-demand seasons for future utilization in the highest-demand ones. In this work, an energy management system (EMS) is developed to optimally manage a grid-connected pumped hydro storage (PHS) for peak shaving. The proposed model incorporates a dynamic economic dispatch (DED) over a study period of one year; hence, a DC power flow analysis considering transmission constraints is utilized to ensure a fast load flow estimation and a manageable simulation time. The framework can be adopted to assess the long-term profitability of PHS-utilizing GAMS as an optimization tool. Further, to draw conclusions that would suit the characteristics of the demand pattern. This analysis is essential to motivate the construction of new seasonal PHS plants due to the high construction costs they are identified with, especially in geographical areas where this technology is not yet considered or is hard to construct. The simulation results demonstrate that integrating 1500 MWh PHS reduced the operation of expensive thermal units by 1224 MWh annually. Further, a reduction in operation costs was recorded after integrating a PHS unit that ranged from 2.6 M to 22 M USD/year, depending on the storage capacity.

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Section: Dynamic Economic Dispatch (Ded)mentioning

confidence: 99%