Optimal Sizing of Energy Storage Devices in Isolated Wind-Diesel Systems Considering Load Growth Uncertainty

Nguyen-Hong, Nhung; Nguyen-Duc, Huy; Nakanishi, Yoshinobu

doi:10.1109/tia.2018.2802940

Cited by 65 publications

(21 citation statements)

References 32 publications

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“…The appearance of the test bench is shown in Figure 7. The test bench consists of the following parts: (1 and 2) DGS and wind turbine simulators based on an asynchronous variable frequency drive and an alternator, (3) a DGS based on a gasoline ICE and synchronous generator, (4) connecting terminals for connecting a wind turbine, (5) an accumulator battery, (6) a programmable logic controller, (7) an autonomous inverter, (8)…”

Section: Experimental Studies and Discussionmentioning

confidence: 99%

Economy Mode Setting Device for Wind-Diesel Power Plants

et al. 2020

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The article is devoted to the problem of reducing fuel consumption in a diesel generator set (DGS) as a part of a wind-diesel power plant (WDPP). The object of the research is a variable speed DGS. The goal is to develop the WDPP intelligent control system, providing an optimal shaft speed of an internal combustion engine (ICE). The basis of the intelligent control system is an economy mode setting device (EMSD), which controls the fuel supply to the ICE. The functional chart of EMSD has been presented. The main EMSD blocks contain a controller and an associative memory block. The associative memory block is a software model of an artificial neural network that determines the optimal shaft speed of the ICE. An algorithm for the WDPP intelligent control system has been developed and tested using the WDPP Simulink model. The EMSD prototype has been created, and its research has been conducted. Dependences of the change in specific and absolute fuel consumption on the load power have been obtained for two 4 kW DGS: with constant rotation speed and variable rotation speed DGS with EMSD. It has been established that the use of EMSD in the mode of low loads allow one to reduce fuel consumption by almost 30%. The error in determining the optimal engine speed using EMSD prototype is not more than 15%.

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Section: Experimental Studies and Discussionmentioning

confidence: 99%

Economy Mode Setting Device for Wind-Diesel Power Plants

et al. 2020

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“…The purpose of the ESS installation is to utilize as much wind power as possible and to mitigate the uncertainty in demand and wind speed. The optimal size of an ESS taking into account the relevant wind scenarios and the annual load growth factor was analyzed in our previous work [26]. The ESS helps balance the fluctuation in wind power, increase the wind penetration level, and also provide FFR as a supplementary service.…”

Section: Study Systemmentioning

confidence: 99%

“…Note that Equations (19) and (26) in the optimization formulation limit the power output of each DG. This explains why the number of hours with six DGs in operation in Case 2 is more than that in Case 1b.…”

Section: Case 2: Optimal Scheduling Problem Considering Frequency Crimentioning

confidence: 99%

“…The reason for this is that the frequency nadir constraint in Equation (26) is formulated as a probabilistic constraint with a risk level of 5%. On the other hand, Equation (26) shows that a longer response time requires a lower power output from each DG or more DGs in operation to provide enough kinetic energy; consequently, increasing the ESS power rating is necessary. It can be seen from Table 4 that when the response time is 200 ms, the power rating of the ESS must be larger than 600 kW to maintain the frequency nadir above 49.2 Hz, whereas an ESS with rated power 400 kW is acceptable if the response time is 100 ms.…”

Section: Impact Of Ess Size and Response Timementioning

confidence: 99%

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Optimal Scheduling of an Isolated Wind-Diesel-Energy Storage System Considering Fast Frequency Response and Forecast Error

Nguyen-Hong

Nakanishi

2019

Energies

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Nowadays, the hybrid wind–diesel system is widely used on small islands. However, the operation of these systems faces a major challenge in frequency control due to their small inertia. Furthermore, it is also difficult to maintain the power balance when both wind power and load are uncertain. To solve these problems, energy storage systems (ESS) are usually installed. This paper demonstrates the effectiveness of using ESS to provide Fast Frequency Response (FFR) to ensure that the frequency criteria are met after the sudden loss of a generator. An optimal day-ahead scheduling problem is implemented to simultaneously minimize the operating cost of the system, take full advantage of the available wind power, and ensure that the ESS has enough energy to provide FFR when the wind power and demand are uncertain. The optimization problem is formulated in terms of two-stage chance-constrained programming, and solved using a Modified Sample Average Approximation (MSAA) algorithm—a combination of the traditional Sample Average Approximation (SAA) algorithm and the k-means approach. The proposed method is tested with a realistic islanded power system, and the effects of the ESS size and its response time is analyzed. Results indicate that the proposed model should perform well under real-world conditions.

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“…According to [5], it is proved theoretically that HESS can make full use of the complementary advantages of battery and SC, improve the output performance of ESS and prolong the service life of battery, reducing the life cycle cost of ESS. By now, many research has been conducted on the optimal configuration and control methods for HESS [19][20][21] but only a few research on energy management and coordinated control for MG wit HESS. Reference [22] proposed a two-layer energy management framework for HESS composed of battery and SC and incorporated the battery cycle charge and discharge life loss into the model.…”

Section: Introductionmentioning

confidence: 99%

An Improved Multi-Timescale Coordinated Control Strategy for Stand-Alone Microgrid with Hybrid Energy Storage System

et al. 2018

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Abstract:A scientific and effective coordinated control strategy is crucial to the safe and economic operation of a microgrid (MG). With the continuous improvement of the renewable energy source (RES) penetration rate in MG, the randomness and intermittency of its output lead to the increasing regulation pressure of the conventional controllable units, the increase of the operating risk of MG and the difficulty in improving the operational economy. To solve the mentioned problems and take advantage of hybrid energy storage system (HESS), this study proposes a multi-time scale coordinated control scheme of "day-ahead optimization (DAO) + intraday rolling (IDR) + quasi-real-time correction (QRTC) + real-time coordinated control (RTCC)." Considering the shortcomings of existing low prediction accuracy of distributed RES and loads, the soft constraints such as unit commitment scheduling errors and load switching scheduling errors are introduced in the intraday rolling model, allowing the correction of day-ahead unit commitment and load switching schedule. In the quasi-real-time coordinated control, an integrated criterion is introduced to decide the adjustment priority of the distributed generations. In the real-time coordinated control, the HESS adopts an improved first order low pass filtering algorithm to adaptively compensate the second-level unbalanced power. Compared with the traditional coordinated control strategy, the proposed improved model has the advantages of good robustness and fast solving speed and provides some guidance for the intelligent solution for stable and economic operation of stand-alone MG with HESS.

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Optimal Sizing of Energy Storage Devices in Isolated Wind-Diesel Systems Considering Load Growth Uncertainty

Cited by 65 publications

References 32 publications

Economy Mode Setting Device for Wind-Diesel Power Plants

Economy Mode Setting Device for Wind-Diesel Power Plants

Optimal Scheduling of an Isolated Wind-Diesel-Energy Storage System Considering Fast Frequency Response and Forecast Error

An Improved Multi-Timescale Coordinated Control Strategy for Stand-Alone Microgrid with Hybrid Energy Storage System

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