Stochastic Performance Assessment and Sizing for a Hybrid Power System of Solar/Wind/Energy Storage

Arabali, A.; Ghofrani, M.; Etezadi-Amoli, M.; Fadali, M. Sami

doi:10.1109/tste.2013.2288083

Cited by 204 publications

(105 citation statements)

References 22 publications

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“…Generally, a Weibull distribution can be used to imitate the stochastic wind speed v [6]. The probability density function (PDF) for wind speed v is described as (1): where k and c are, respectively, the shape parameter and the scale parameter of the wind speed distribution. According to the historical data of wind speed v, these two indices can be estimated.…”

Section: Output Uncertainty Of Wind Generatorsmentioning

confidence: 99%

“…The extensive penetration of renewable-type distributed generators (DGs) (e.g., wind and PV) in distribution networks could bring many benefits to the grid, as they are alternative to conventional generators [1,2]. However, the randomness of these DGs could cause some critical risks to security and economy aspects of distribution systems, such as power quality and stability, fault level, and the value of load curtailment, which impose challenges when planning distribution systems [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Gong¹,

Lei²,

Qiao³

et al. 2017

Sustainability

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Abstract:The intermittency and variability of permeated distributed generators (DGs) could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices-EENS (expected energy not supplied), PLC (probability of load curtailment), EFLC (expected frequency of load curtailment), and SI (severity index)-were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs' output power, an improved PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

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Section: Output Uncertainty Of Wind Generatorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Gong¹,

Lei²,

Qiao³

et al. 2017

Sustainability

View full text Add to dashboard Cite

show abstract

“…Although these clean energies provide significant contributions and opportunities, the unpredictable nature [3] of these resources has posed serious challenges to power systems [4,5]. In the context of remote HPS, the greatest obstacle is to maintain power balance, because the adjustable capacity depends merely on REGs and batteries [6].…”

Section: Introductionmentioning

confidence: 99%

“…The stochastic nature of the REGs has been investigated with several probabilistic and chronological methods. The autoregressive moving average (ARMA) is utilized to model the uncertainties of wind generation, photovoltaic (PV) power, and load in [3,7,8]. However, methods for parameters estimation of ARMA are always somewhat cumbersome.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing for Wind/PV/Battery System Using Fuzzy c-Means Clustering with Self-Adapted Cluster Number

Liu

Chen

Huang³

et al. 2017

International Journal of Rotating Machinery

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Integrating wind generation, photovoltaic power, and battery storage to form hybrid power systems has been recognized to be promising in renewable energy development. However, considering the system complexity and uncertainty of renewable energies, such as wind and solar types, it is difficult to obtain practical solutions for these systems. In this paper, optimal sizing for a wind/PV/battery system is realized by trade-offs between technical and economic factors. Firstly, the fuzzy -means clustering algorithm was modified with self-adapted parameters to extract useful information from historical data. Furthermore, the Markov model is combined to determine the chronological system states of natural resources and load. Finally, a power balance strategy is introduced to guide the optimization process with the genetic algorithm to establish the optimal configuration with minimized cost while guaranteeing reliability and environmental factors. A case of island hybrid power system is analyzed, and the simulation results are compared with the general FCM method and chronological method to validate the effectiveness of the mentioned method.

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“…In the methodology, K-clustering algorithm divides wind turbines in inner grid into k-groups and then Minimum Spanning Tree (MSP) algorithm links wind turbines to each other based on the objective that total length of cables used for the connection of wind turbines in each group is minimized [2], [3]. Using local search method [4], the exploration is performed about diverse combinations made by the number of groups and the number of wind turbines belonging to each group. Alternatives generated by K-clustering and MST algorithms are evaluated in terms of total length of cables or total investment cost, and optimal configuration is finally selected.…”

mentioning

confidence: 99%

Study on Designing for Inner Grid of Offshore Wind Farm

Shin¹,

Kim²,

Kim³

2015

JOCET

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Abstract-Wind power is one of the widely used renewable resources and it is connected to power system steadily. In recent years, wind power is developed in the form of large-scale wind farm at offshore, which is composed of dozens or hundreds of wind turbines. In inner grid of wind farm, wind turbines are connected to each other through cable, and there are a wide variety of configurations depending on how to connect wind turbines. Due to difficult and expensive construction activity at sea, the problem to connect optimally wind turbines is very important. In order to solve the problem, this paper introduces a methodology based on the k-clustering algorithm, minimum spanning tree (MSP) algorithm and local search method. K-clustering is applied to divide wind turbines into k-groups, and MSP algorithm is used to link wind turbines in each group with the objective that total length of cables is minimized. Optimal configuration is determined by local search method which explores diverse combinations depending on the number of groups and the number of wind turbines in each group. The case studies show that the proposed methodology can be utilized usefully for designing inner grid of offshore wind farm.Index Terms-Offshore wind farm, inner grid, k-clustering algorithm, minimum spanning tree, local search method. I. INTRODUCTIONWind power is a widely used renewable energy and is increased steadily. In particular, it is being developed as large-scale wind farm as the related technology and economics are advanced [1]. In order to gather more wind energy and to avoid environment problems and construction concerns such as securing the installation site, the recent wind power is developed at offshore. Compared with onshore wind farm, offshore wind farm (OWF) has some advantages, and it has also crucial disadvantages which are more expensive investment and maintenance costs caused by the difficulty of geographical access. Namely, since OWF operators have a considerable burden on investment, it is important to design optimal configuration for wind farm. Therefore, this paper investigates for optimal configuration of inner grid among components making up offshore wind farm. In the methodology, K-clustering algorithm divides wind turbines in inner grid into k-groups and then Minimum Spanning Tree (MSP) algorithm links wind turbines to each other based on the objective that total length of cables used for the connection of wind turbines in each group is minimized [2], [3]. Using local search method [4], the exploration is performed about diverse combinations made by the number of groups and the number of wind turbines belonging to each group. Alternatives generated by K-clustering and MST algorithms are evaluated in terms of total length of cables or total investment cost, and optimal configuration is finally selected. The rest of the paper is organized as follows; in Section II, typical compositions of OWF and layouts of inner grid are described. In Section III, the methodology including k-clustering, MST algorithms and local s...

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Stochastic Performance Assessment and Sizing for a Hybrid Power System of Solar/Wind/Energy Storage

Cited by 204 publications

References 22 publications

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Optimal Sizing for Wind/PV/Battery System Using Fuzzy c-Means Clustering with Self-Adapted Cluster Number

Study on Designing for Inner Grid of Offshore Wind Farm

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