Two-stage robust generation expansion planning considering long- and short-term uncertainties of high share wind energy

Abdalla, Omar H.; Smieee, Life; Adma, Maged A. Abu; Ahmed, Abdelmonem S.

doi:10.1016/j.epsr.2020.106618

Cited by 17 publications

(11 citation statements)

References 32 publications

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“…To model the uncertainties of renewable resources and load demand to some extent, representative days approach is deployed which different scenarios of normal monthly generation, one extreme scenario of monthly renewable actual generation, and one extreme scenario of monthly load demand are extracted using clustering approach, similar to other studies such as refs. [46], [47], [36], [43], [19], and [41]. To this end, to preserve the daily pattern of wind generation and load demand, 36 representative days for the target planning year are assumed.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Low‐carbon generation expansion planning considering flexibility requirements for hosting wind energy

Pourmoosavi

Amraee

2022

IET Generation Trans & Dist

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The operational flexibility of electric energy systems is one of the essential requirements for integrating a high share of renewable resources. The operational flexibility significantly impacts the mix of new power generation technologies. In this paper, a low‐carbon generation expansion planning (GEP) model is presented to investigate the impacts of flexibility requirements of power systems with a high share of wind energy. An improved clustered unit commitment (CUC) formulation is proposed to capture the flexibility limitation of thermal generating units fully. In this regard, clustered 10‐min ramp up/down limits for operational reserves, flexible‐ramp reserves, and contingency reserves, are introduced. The yearly variations of load and renewable generations preserving the chronological time correlations are included, considering 36 representative days obtained by the clustering approach. Besides, two types of BES devices are considered to investigate the role of BES in the provision of flexibility. The proposed flexible low‐carbon GEP model is formulated as a mixed‐integer programming model, and an optimal expansion plan is obtained using the CPLEX algorithm. By incorporating improved CUC formulation into the low‐carbon GEP model, more profound insight into power systems' flexibility requirement with high wind generation penetration is obtained.

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Section: Simulation Resultsmentioning

confidence: 99%

“…In ref. [47] a two-stage robust flexible GEP model is proposed to study the impacts of the short-term and long-term uncertainty of wind energy. Also, the correlations of different candidate wind sites are investigated.…”

Section: Flexible Low-carbon Gepmentioning

confidence: 99%

Low‐carbon generation expansion planning considering flexibility requirements for hosting wind energy

Pourmoosavi

Amraee

2022

IET Generation Trans & Dist

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“…On the other side, the short-term uncertainty was simulated based on the hourly variation of wind power as [34]. Added to that, reserve margin has been adopted to cope with the uncertainty effect [34], while additional capacities of Pump Hydro Storage (PHS) and Fast Gas Turbine (FGT) have been utilized to cope with short-term uncertainty problems [35]. The problem of short-term uncertainty was modeled using the autoregressive moving average model.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithm

Abou El-Ela,

El-Sehiemy,

Shaheen

et al. 2024

Neural Comput & Applic

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Robust reliability Generation Expansion Planning (GEP) turns out to be a crucial step for an efficient energy management system in a modern power grid, especially under renewable energy employment. The integration of all such components in a GEP model makes it a large-scale, nonlinear, and mixed-variable mathematical modeling problem. In this paper, the presence of wind energy uncertainty is analyzed. Both long and short-term uncertainties are incorporated into the proposed GEP model. The first step concerns the impact of long-term wind uncertainties through the annual variations of the capacity credit of two real sites in Egypt at Zafaranh and Shark El-ouinate. The second step deals with the short-term uncertainties of each wind site. The wind speed uncertainty of each wind site is modeled by probability distribution function. Then, wind power is estimated from the wind power curve for each wind site and Monte-Carlo Simulation is performed. Fast Gas Turbine and/or Pump Hydro Storage are incorporated to cope with short-term uncertainties. Sensitivity analysis is implemented for 3, 6, and 12 stages as short and long planning horizons to minimize the total costs with wind energy penetration and emission reduction over planning horizons. Also, a novel Honey Badger Algorithm (HBA) with model modifications such as Virtual Mapping Procedure, Penalty Factor Approach, and the Modified of Intelligent Initial Population Generation is utilized for solving the proposed GEP problem. The obtained results are compared with other algorithms to ensure the superior performance of the proposed HBA. According to the results of the applicable test systems, the proposed HBA performs better than the others, with percentage reductions over CSA, AO, BES, and PSO ranging up to 4.2, 2.72, 2.7, and 3.4%, respectively.

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“…Several large system plans that have been developed take renewable energy into account, such as one in Brazil [5], with a system size of 152 MW. In addition, planning for developing a 2,350 MW system with a 100 MW wind power plant penetration by considering seasonal variations has been discussed [6].…”

Section: Introductionmentioning

confidence: 99%

Pengembangan Sistem Kelistrikan Tanah Merah Mempertimbangkan Energi Baru Terbarukan dan Emisi CO2

Amrisal Kamal Fajri,

Sarjiya,

Lesnanto Multa Putranto

et al. 2023

JNTETI

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Sistem kelistrikan di wilayah Papua masih memiliki rasio elektrifikasi sebesar 94% dengan biaya pokok penyediaan (BPP) yang tinggi, yaitu Rp3.041/kWh. Selain itu, sistem kelistrikan yang ada masih terdiri atas banyak sistem kecil yang jumlahnya lebih dari seratus, dengan sebagian besar pembangkit berjenis diesel (pembangkit listrik tenaga diesel, PLTD). Salah satu sistem tersebut adalah wilayah Tanah Merah, yang memiliki populasi 19.136 jiwa dengan kebutuhan energi sebesar 6,89 GWh. Wilayah tersebut diproyeksikan akan mengalami pemekaran dan pertumbuhan populasi. Sebagai konsekuensinya, kebutuhan energi listrik akan meningkat. Oleh karena itu, perencanaan pengembangan sistem pembangkitan perlu dilakukan untuk memenuhi kebutuhan energi listrik yang tumbuh. Perencanaan pada daerah terpencil lazimnya dilakukan untuk durasi jangka pendek, yaitu untuk tahun 2025 hingga 2030, melalui proses optimisasi dari beberapa kandidat pembangkit yang diusulkan. Kandidat pembangkit yang diusulkan mempertimbangkan ketersediaan energi primer setempat, suplai gas dan BBM, dan ketersediaan teknologi. Optimisasi akan meminimalkan jumlah biaya dari pembangkit yang akan dipilih yang memiliki atribut berupa biaya investasi, operasi, pemeliharaan, bahan bakar, dan nilai sisa aset pada durasi perencanaan. Dalam melakukan perencanaan, pengurangan emisi gas rumah kaca sebesar 29% dan proporsi bauran energi sebesar 23% perlu dipertimbangkan, sesuai dengan kebijakan pemerintah. Oleh karena itu, dua skenario yang meliputi aspek keekonomian dan lingkungan dipertimbangkan dalam proses simulasi, yaitu skenario business as usual (BaU) dan skenario nationally determined contributions (NDC) untuk pembatasan emisi. Optimisasi dikembangkan berdasarkan mixed-integer linear programming (MILP) yang dilakukan pada perangkat lunak HOMER. Hasil simulasi yang diperoleh menunjukkan bahwa BPP pembangkitan untuk skenario BaU lebih ekonomis jika dibandingkan dengan skenario NDC, yaitu sebesar Rp2.559,8/kWh berbanding Rp3.104,64/kWh.

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Two-stage robust generation expansion planning considering long- and short-term uncertainties of high share wind energy

Cited by 17 publications

References 32 publications

Low‐carbon generation expansion planning considering flexibility requirements for hosting wind energy

Low‐carbon generation expansion planning considering flexibility requirements for hosting wind energy

Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithm

Pengembangan Sistem Kelistrikan Tanah Merah Mempertimbangkan Energi Baru Terbarukan dan Emisi CO2

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