scholarly journals The Effect of a Renewable Energy Certificate Incentive on Mitigating Wind Power Fluctuations: A Case Study of Jeju Island

2019 ◽  
Vol 9 (8) ◽  
pp. 1647
Author(s):  
Woong Ko ◽  
Jaeho Lee ◽  
Jinho Kim

As renewable energy penetration in power systems grows, adequate energy policies are needed to support the system’s operations with flexible resources and to adopt more sustainable energies. A peak-biased incentive for energy storage systems (ESS) using the Korean renewable portfolio standard could make power system operations more difficult. For the first time in the research, this study evaluates the effect of imposing a renewable energy certificate incentive in off-peak periods on mitigating wind power fluctuations. We design a coordinated model of a wind farm with an ESS to model the behavior of wind farm operators. Optimization problems are formulated as mixed integer linear programming problems to test the implementation of revenue models under Korean policy. These models are designed to consider additional incentives for discharging the ESS during off-peak periods. The effects of imposing the incentives on wind power fluctuations are evaluated using the magnitude of the renewable energy certificate (REC) multiplier.

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5377
Author(s):  
Abdullah Al-Shereiqi ◽  
Amer Al-Hinai ◽  
Mohammed Albadi ◽  
Rashid Al-Abri

Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the available renewable energy resources as a fuel-saver simply to reduce fossil-fuel consumption. This is related mainly to the inherently variable and non-dispatchable nature of renewable energy resources, which poses a threat to power system reliability and requires utilities to maintain power-balancing reserves to match the supply from renewable energy resources with the real-time demand levels. Thus, further efforts are needed to mitigate the risk that comes with integrating renewable resources into the electricity grid. Hence, an integrated strategy is being created to determine the optimal size of the hybrid wind-solar photovoltaic power systems (HWSPS) using heuristic optimization with a numerical iterative algorithm such that the output fluctuation is minimized. The research focuses on sizing the HWSPS to reduce the impact of renewable energy resource intermittency and generate the maximum output power to the grid at a constant level periodically based on the availability of the renewable energy resources. The process of determining HWSPS capacity is divided into two major steps. A genetic algorithm is used in the initial stage to identify the optimum wind farm. A numerical iterative algorithm is used in the second stage to determine the optimal combination of photovoltaic plant and battery sizes in the search space, based on the reference wind power generated by the moving average, Savitzky–Golay, Gaussian and locally weighted linear regression techniques. The proposed approach has been tested on an existing wind power project site in the southern part of the Sultanate of Oman using a real weather data. The considered land area dimensions are 2 × 2 km. The integrated tool resulted in 39 MW of wind farm, 5.305 MW of PV system, and 0.5219 MWh of BESS. Accordingly, the estimated cost of energy based on the HWSPS is 0.0165 EUR/kWh.


Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.


2019 ◽  
Vol 11 (16) ◽  
pp. 4424 ◽  
Author(s):  
Chunning Na ◽  
Huan Pan ◽  
Yuhong Zhu ◽  
Jiahai Yuan ◽  
Lixia Ding ◽  
...  

At present time, China’s power systems face significant challenges in integrating large-scale renewable energy and reducing the curtailed renewable energy. In order to avoid the curtailment of renewable energy, the power systems need significant flexibility requirements in China. In regions where coal is still heavily relied upon for generating electricity, the flexible operations of coal power units will be the most feasible option to face these challenges. The study first focused on the reasons why the flexible operation of existing coal power units would potentially promote the integration of renewable energy in China and then reviewed the impacts on the performance levels of the units. A simple flexibility operation model was constructed to estimate the integration potential with the existing coal power units under several different scenarios. This study’s simulation results revealed that the existing retrofitted coal power units could provide flexibility in the promotion of the integration of renewable energy in a certain extent. However, the integration potential increment of 20% of the rated power for the coal power units was found to be lower than that of 30% of the rated power. Therefore, by considering the performance impacts of the coal power units with low performances in load operations, it was considered to not be economical for those units to operate at lower than 30% of the rated power. It was believed that once the capacity share of the renewable energy had achieved a continuously growing trend, the existing coal power units would fail to meet the flexibility requirements. Therefore, it was recommended in this study that other flexible resources should be deployed in the power systems for the purpose of reducing the curtailment of renewable energy. Furthermore, based on this study’s obtained evidence, in order to realize a power system with high proportions of renewable energy, China should strive to establish a power system with adequate flexible resources in the future.


Author(s):  
Johan S. Obando ◽  
Gabriel González ◽  
Ricardo Moreno

The high integration of wind energy in power systems requires operating reserves to ensure the reliability and security in the operation. The intermittency and volatility in wind power sets a challenge for day-ahead dispatching in order to schedule generation resources. Therefore, the quantification of operating reserves is addressed in this paper using extreme values through Monte-Carlo simulations. The uncertainty in wind power forecasting is captured by a generalized extreme value distribution to generate scenarios. The day-ahead dispatching model is formulated as a mixed-integer linear quadratic problem including ramping constraints. This approach is tested in the IEEE-118 bus test system including integration of wind power in the system. The results represent the range of values for operating reserves in day-ahead dispatching.


2018 ◽  
Vol 64 ◽  
pp. 06009
Author(s):  
Matsuhashi Ryuji ◽  
Yoshioka Tsuyoshi

Renewable power sources are increasing mainly because of economic institutions such as renewable portfolio standard or feed-in tariff program. In Japan, the feed-in tariff program triggered explosive growth of photovoltaic systems because of its high tariff level. Although mass introduction of photovoltaic systems certainly contributes to reduce CO2 emissions, it causes instability issues in power systems. One of the most serious issues is management of imbalances resulting from forecast errors in photovoltaic outputs. On the other hand, power-to-gas technologies are attracting our attention, since these technologies could convert surplus of renewable energy to other energy carriers. In particular, hydrogen is efficiently produced from electricity using electrolysis. We could use hydrogen to manage the imbalances by the system, in which uncertain parts of photovoltaic outputs are used to produce hydrogen. In this paper, we propose a coproduction system of electricity and hydrogen to reduce the imbalances. For this purpose, a novel mathematical model is developed, in which we determine the structure of the coproduction system with a mixed integer linear programming method. Evaluated results indicated that the coproduction system is economical under appropriate capacity of the electrolyzer.


Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1333 ◽  
Author(s):  
Diego Francisco Larios ◽  
Enrique Personal ◽  
Antonio Parejo ◽  
Sebastián García ◽  
Antonio García ◽  
...  

The complexity of power systems is rising mainly due to the expansion of renewable energy generation. Due to the enormous variability and uncertainty associated with these types of resources, they require sophisticated planning tools so that they can be used appropriately. In this sense, several tools for the simulation of renewable energy assets have been proposed. However, they are traditionally focused on the simulation of the generation process, leaving the operation of these systems in the background. Conversely, more expert SCADA operators for the management of renewable power plants are required, but their training is not an easy task. SCADA operation is usually complex, due to the wide set of information available. In this sense, simulation or co-simulation tools can clearly help to reduce the learning curve and improve their skills. Therefore, this paper proposes a useful simulator based on a JavaScript engine that can be easily connected to any renewable SCADAs, making it possible to perform different simulated scenarios for novel operator training, as if it were a real facility. Using this tool, the administrators can easily program those scenarios allowing them to sort out the lack of support found in setting up facilities and training of novel operator tasks. Additionally, different renewable energy generation models that can be implemented in the proposed simulator are described. Later, as a use example of this tool, a study case is also performed. It proposes three different wind farm generation facility models, based on different turbine models: one with the essential generation turbine function obtained from the manufacturer curve, another with an empirical model using monotonic splines, and the last one adding the most important operational states, making it possible to demonstrate the usefulness of the proposed simulation tool.


Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 171 ◽  
Author(s):  
Hua Zhou ◽  
Huahua Wu ◽  
Chengjin Ye ◽  
Shijie Xiao ◽  
Jun Zhang ◽  
...  

With the rapid growth of renewable energy generation, it has become essential to give a comprehensive evaluation of renewable energy integration capability in power systems to reduce renewable generation curtailment. Existing research has not considered the correlations between wind power and photovoltaic (PV) power. In this paper, temporal and spatial correlations among different renewable generations are utilized to evaluate the integration capability of power systems based on the copula model. Firstly, the temporal and spatial correlation between wind and PV power generation is analyzed. Secondly, the temporal and spatial distribution model of both wind and PV power generation output is formulated based on the copula model. Thirdly, aggregated generation output scenarios of wind and PV power are generated. Fourthly, wind and PV power scenarios are utilized in an optimal power flow calculation model of power systems. Lastly, the integration capacity of wind power and PV power is shown to be able to be evaluated by satisfying the reliability of power system operation. Simulation results of a modified IEEE RTS-24 bus system indicate that the integration capability of renewable energy generation in power systems can be comprehensively evaluated based on the temporal and spatial correlations of renewable energy generation.


2013 ◽  
Vol 391 ◽  
pp. 271-276
Author(s):  
Peng Li ◽  
Ning Bo Wang ◽  
De Zhi Chen ◽  
Xiao Rong Zhu ◽  
Yun Ting Song

Increasing penetration level of wind power integration has a significant impact on low-frequency oscillations of power systems. Based on PSD-BPA simulation software, time domain simulation analysis and eigenvalue analysis are employed to investigate its effect on power system low-frequency oscillation characteristic in an outward transmitting thermal generated power bundled with wind power illustrative power system. System damping enhances markedly and the risk of low-frequency oscillation reduce when the generation of wind farm increase. In addition, dynamic reactive power compensations apply to wind farm, and the simulation result indicates that it can improve dynamic stability and enhance the system damping.


2015 ◽  
Vol 93 ◽  
pp. 239-248 ◽  
Author(s):  
Songyan Wang ◽  
Ning Chen ◽  
Daren Yu ◽  
Aoife Foley ◽  
Lingzhi Zhu ◽  
...  

2014 ◽  
Vol 536-537 ◽  
pp. 470-475
Author(s):  
Ye Chen

Due to the features of being fluctuant, intermittent, and stochastic of wind power, interconnection of large capacity wind farms with the power grid will bring about impact on the safety and stability of power systems. Based on the real-time wind power data, wind power prediction model using Elman neural network is proposed. At the same time in order to overcome the disadvantages of the Elman neural network for easily fall into local minimum and slow convergence speed, this paper put forward using the GA algorithm to optimize the weight and threshold of Elman neural network. Through the analysis of the measured data of one wind farm, shows that the forecasting method can improve the accuracy of the wind power prediction, so it has great practical value.


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