Selecting Representative Days for Capturing the Implications of Integrating Intermittent Renewables in Generation Expansion Planning Problems

Poncelet, Kris; Höschle, Hanspeter; Delarue, Erik; Virag, Ana; Drhaeseleer, William

doi:10.1109/tpwrs.2016.2596803

Cited by 252 publications

(173 citation statements)

References 23 publications

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“…Depending on the storage medium, ESSs are categorised either as mechanical, chemical, or electrical storage systems . A survey of the literature shows that few studies have integrated ESS in GEP models …”

Section: Environmental Considerationsmentioning

confidence: 99%

“…220 A survey of the literature shows that few studies have integrated ESS in GEP models. 51,54,62,65,67,115,211,213,218,[221][222][223][224] The inclusion of ESS technologies in GEP models creates a challenge because most GEP models make use of load duration curves. However, in order to capture the operational details of the ESS, a chronological load data is inevitable.…”

Section: Application Of Ess In Gepmentioning

confidence: 99%

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A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

2019

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Summary Generation expansion planning (GEP) is a power plant mix problem that identifies what, where, when, and how new generating facilities should be installed and when old units be retired over a specific planning horizon. GEP ensures that the quantity of electricity generated matches the electricity demand throughout the planning horizon. This kind of planning is of importance because most production and service delivery is dependent on availability of electricity. Over the years, the traditional GEP approaches have evolved to produce more realistic models and new solution algorithms. For example, with the agitation for green environment, the inclusion of renewable energy plants and energy storage in the traditional GEP model is gradually gaining attention. In this regards, a handful of research has been conducted to identify the optimal expansion plans based on various energy‐related perspectives. The appraisal and classification of studies under these topics are necessary to provide insights for further works in GEP studies. This article therefore presents a comprehensive up‐to‐date review of GEP studies. Result from the survey shows that the integration of demand side management, energy storage systems (ESSs), and short‐term operational characteristics of power plants in GEP models can significantly improve flexibility of power system networks and cause a change in energy production and the optimal capacity mix. Furthermore, this article was able to identify that to effectively integrate ESS into the generation expansion plan, a high temporal resolution dimension is essential. It also provides a policy discussion with regard to the implementation of GEP. This survey provides a broad background to explore new research areas in order to improve the presently available GEP models.

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Section: Environmental Considerationsmentioning

confidence: 99%

Section: Application Of Ess In Gepmentioning

confidence: 99%

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

2019

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“…Some authors use a heuristic method, choosing one day for each season or one day in each season for the week and for the weekend. Others have proposed methods that involve optimizing both the number and clustering of RPs to minimize the difference between the load duration curve and the approximate one created by the RPs [10], [11]. There has also been debate about the optimal length for RPs.…”

Section: B Literature Reviewmentioning

confidence: 99%

Enhanced Representative Days and System States Modeling for Energy Storage Investment Analysis

Tejada-Arango

Domeshek

Wogrin

et al. 2018

IEEE Trans. Power Syst.

107

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This paper analyzes different models for evaluating investments in energy storage systems (ESS) in power systems with high penetration of renewable energy sources. First of all, two methodologies proposed in the literature are extended to consider ESS investment: a unit commitment model that uses the "system states" (SS) method of representing time; and another one that uses a "representative periods" (RP) method. Besides, this paper proposes two new models that improve the previous ones without a significant increase of computation time. The enhanced models are the "system states reduced frequency matrix" model which addresses short-term energy storage more approximately than the SS method to reduce the number of constraints in the problem, and the "representative periods with transition matrix and cluster indices" (RP-TM&CI) model which guarantees some continuity between representative periods, e.g., days, and introduces long-term storage into a model originally designed only for the short term. All these models are compared using an hourly unit commitment model as benchmark. While both system state models provide an excellent representation of long-term storage, their representation of short-term storage is frequently unrealistic. The RP-TM&CI model, on the other hand, succeeds in approximating both shortand long-term storage, which leads to almost 10 times lower error in storage investment results in comparison to the other models analyzed.Index Terms-Energy storage systems, power system planning, power system modeling, system states, representative days.

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“…They are simulated under the same conditions over 12 days, divided in 24 periods and simulated independently. These days are selected to be representative of one year [10], [11], based on the time series of aggregated active and reactive production and consumption of the distribution system. To simulate the tap changer of the HV/MV transformer, the voltage at the MV side is considered constant.…”

Section: A Test Systemmentioning

confidence: 99%

Effect of voltage constraints on the exchange of flexibility services in distribution networks

Mathieu

Frédéric

Ernst

et al. 2018

2018 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

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Abstract-Many possibilities exist to organise exchanges of flexibility within a distribution system. In this paper, we call such a possibility an interaction model. The DSIMA (Distribution System Interaction Model Analysis) testbed allows one to compare quantitatively candidate interaction models by simulating a distribution system with actors taking decisions to maximise their own profit or minimise their costs. The original testbed focused on establishing the procedures to exchange information between actors and used a network flow model considering only active power. This paper extends DSIMA with a linear approximation of the power flow equations, the line limits and the voltage constraints. This linear flow model is compared to a network flow model by simulating three different interaction models governing the exchange of flexibility services within a Belgian distribution system. Results show that changing the network model may significantly impact the quantitative results obtained from the simulations.

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Selecting Representative Days for Capturing the Implications of Integrating Intermittent Renewables in Generation Expansion Planning Problems

Cited by 252 publications

References 23 publications

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

Enhanced Representative Days and System States Modeling for Energy Storage Investment Analysis

Effect of voltage constraints on the exchange of flexibility services in distribution networks

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