Grid-Connected Wind Power Plants: A Survey on the Integration Requirements in Modern Grid Codes

Wu, Yuan‐Kang; Chang, Shih-Ming; Mandal, Paras

doi:10.1109/icps.2019.8733382

Cited by 30 publications

(17 citation statements)

References 11 publications

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“…These frequency and voltage issues may cause the wave energy farm to not be compliant with the grid codes of the transmission system operators (TSOs) and, hence, make wave energy farms not suitable for being included in the electricity generation mix of a country [8]. In [12,13] an introduction about the study on grid compliance and standardization of renewable generation and other energy systems connected to the power grid is provided. In [13][14][15][16][17] the grid codes of different countries (European and non-European) and the corresponding projects about renewable power are compared and summarized.…”

Section: Introductionmentioning

confidence: 99%

“…In [12,13] an introduction about the study on grid compliance and standardization of renewable generation and other energy systems connected to the power grid is provided. In [13][14][15][16][17] the grid codes of different countries (European and non-European) and the corresponding projects about renewable power are compared and summarized. The impact of grid code regulations on stability is also analyzed.…”

Section: Introductionmentioning

confidence: 99%

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Dimensioning Methodology of an Energy Storage System Based on Supercapacitors for Grid Code Compliance of a Wave Power Plant

et al. 2021

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The aim of this paper is to present a methodology for dimensioning an energy storage system (ESS) to the generation data measured in an operating wave energy generation plant connected to the electric grid in the north of Spain. The selection criterion for the ESS is the compliance of the power injected into the grid with a specific active-power ramp-rate limit. Due to its electrical characteristics, supercapacitor (SC) technology is especially suitable for this application. The ESS dimensioning methodology is based on a mathematical model, which takes into account the power generation system, the chosen ramp-rate limit, the ESS efficiency maps and electrical characteristics. It allows one to evaluate the number of storage cabinets required to satisfy the needs described, considering a compromise between the number of units, which means cost, and the reliability of the storage system to ensure the grid codes compliance. Power and energy parameters for the ESS are obtained from the calculations and some tips regarding the most efficient operation of the SC cabinets, based on a stepped switching strategy, are also given. Finally, some conclusions about the technology selection will be updated after the detailed analysis accomplished.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dimensioning Methodology of an Energy Storage System Based on Supercapacitors for Grid Code Compliance of a Wave Power Plant

et al. 2021

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“…In [24,25], grid codes about wind power integration around the world including grid codes of Denmark, Ireland, the U.K., Germany, Spain, China, the U.S., Canada, and other countries have been reviewed and compared. The most important aspects of these grid codes are concerning frequency regulation, fault ride through, ramping rate, market balancing, etc.…”

Section: Introductionmentioning

confidence: 99%

Energy Quality: A Definition

Zhang

Yan

2020

IEEE Open J. Power Energy

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In literature, variations and distortions, and interruptions of voltages (or voltage waveforms) and currents (or current waveforms) have been considered in the framework of power quality (or voltage quality). With the massive penetration of renewable energy into power systems, variations including fluctuations and intermittences of output powers of these renewable sources are of great concerns. It is evidenced that with the high penetration of renewable energy, variations of renewable energy have increased the costs of UK's balancing markets by 39% in this spring and summer [26]. Therefore, there are needs to introduce a technical framework, namely, 'energy quality' to (a) define the quality of power waveforms; (b) propose measures/indices to characterize the variations (fluctuations and intermittences) of powers and power flows; (c) present methods to improve energy quality. Finally, research directions of energy quality are highlighted to encourage more R&D as well as international collaborations in terms of standards and grid code developments.

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“…These constraints are imposed by TSO to ensure that the operation of the WF system does not affect the stability of the power system as well as to support the power system in emergency cases [22]- [24]. There are two grid-code constraints that are often considered in the operation of WF systems, including the requirements for limited power and reserve power [23], [24]. Firstly, the output power of the WF system is bounded by a maximum output power (i.e.…”

Section: B Introduction To Grid-code Constraintsmentioning

confidence: 99%

“…Additionally, these studies [14]- [17] have not considered grid-code constraints from transmission system operators (TSOs). This can lead to several negative impacts on the security and stability of the power system [22], [23].…”

mentioning

confidence: 99%

Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach

Bui

Nguyen

2020

IEEE Access

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In the conventional operation of a wind farm (WF) system, the operation point of each wind turbine generator (WTG) is determined to capture maximum energy individually using maximum power point tracking (MPPT) algorithm. However, this operation strategy might not ensure the maximum output power of WF due to wake effect among WTGs. Therefore, this paper develops a multi-agent-based cooperative learning strategy among WTGs using deep reinforcement learning to enhance the overall efficiency of WF by minimizing the wake effect. WTG agents are learnable units and they interact with others as an extensive-form game based on a cooperative model to achieve a common goals (i.e. maximum output power of the WF). In this game, WTG agents carry out their actions sequentially and measure a common reward which is used to update the knowledge of all agents. During the training process, WTG agents use different deep neural networks (DNNs) to improve their actions for achieving the higher reward in the long run by optimizing the weights of DNNs in each learning step. After the training process, WTG agents are able to determine optimal set-points with different input information to minimize the wake effect and to maximize the output power of the WF. Moreover, an operation strategy for the entire WF system is proposed to ensure that the WF always complies with grid-code constraints from transmission system operators, including the requirement of limited power and reserve power. In order to show the effectiveness of the proposed method, a comparison between the results using the proposed method and the conventional MPPT method is also presented in different cases, and the results show that the proposed method can increase the output power of the WF in the range of 1.99% to 4.11% with different layouts.

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Grid-Connected Wind Power Plants: A Survey on the Integration Requirements in Modern Grid Codes

Cited by 30 publications

References 11 publications

Dimensioning Methodology of an Energy Storage System Based on Supercapacitors for Grid Code Compliance of a Wave Power Plant

Dimensioning Methodology of an Energy Storage System Based on Supercapacitors for Grid Code Compliance of a Wave Power Plant

Energy Quality: A Definition

Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach

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