scholarly journals Supervisory Power Coordination Scheme to Mitigate Power Curtailment in the Application of a Microgrid

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1998
Author(s):  
Heesang Ko ◽  
Gihoon Kim ◽  
Yanghyun Nam ◽  
Kyungsang Ryu
Keyword(s):  
Electricity Market ◽  
Wind Farm ◽  
Voltage Regulation ◽  
Power Balance ◽  
Simulation Studies ◽  
Virtual Power ◽  
Dc Voltage ◽  
Coordination Scheme ◽  
Farm Operators ◽  
System Configurations

There are cases where the output of renewable eappennergy (RE) is curtailed due to an increase in the share of RE. Typically, wind power (WP) is curtailed due to oversupply and low loads at midnight. However, there are cases where the output of WP is limited during the daytime due to the increase in the share of photovoltaics (PV). In the current electricity market, as the share of PV is increased, the curtailments of WP will be increased further, which will add to the difficulties experienced by wind farm operators. This paper proposes a supervisory power coordination scheme. The main purposes are to prevent the penetration of extra power from REs into the grid; thus, the curtailments can be prevented. In order to make it feasible, the proposed scheme is to design a grid-connected microgrid system to be operated only in response to loads and virtual power plant (VPP) requests. The effectiveness of the proposed scheme was verified by simulation studies conducted in the MATLAB/Simulink environment. The verification was conducted based on the voltage criteria, such as the AC voltage regulation between ±6% of the rated AC voltage, the DC voltage regulation between ±10% of the rated DC voltage, the power balance according to variations in the loads, and VPP requests for power. The simulation showed that the proposed scheme is feasible and justifiable, not only to mitigate the power curtailment problem but also to apply different system configurations.

Optimizing Synergy of Utility-Scale Wind and Pumped-Hydro Storage

2013 ◽  
Author(s):  
A. Singh ◽  
F. Wolff ◽  
N. Chokani ◽  
R. S. Abhari
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Power Plants ◽  
Wind Farm ◽  
Renewable Energy Sources ◽  
Electricity Production ◽  
Decision Algorithm ◽  
Wind Power Plants ◽  
Farm Operators ◽  
Storage Facilities

The increased penetration of wind-generated electricity exposes wind farm operators to market risks of a balanced supply in the transmission grid. In order to reduce the risks and to gain financial advantage for wind farm operators, the use of pumped hydro storage to adjust the delivery schedule of energy is proposed. An approach that systematically and rapidly addresses the economic, infrastructural, geographic and meteorological factors relevant to wind power plants and pumped hydro storage over large areas is required. An integrated Geographic Information System-based tool is developed to identify, on the scale of a country, wind power plants and pumped hydro storage facilities. Further, a decision algorithm that has inputs of the forecasted and actual wind energy productions, and the day-ahead and intraday electricity market prices is also developed to optimise the use of pumped hydro storage. This approach is demonstrated for Germany, with the target of increasing electricity production from renewable energy sources. A countrywide portfolio of wind power plants that meets the increased electricity production target, and existing and potential pumped hydro storage facilities are identified. By optimizing the use of pumped hydro storage, it is shown that wind farm operators can achieve a 2–4% gain on the Internal Rate of Return on investments. The improved financial performance with the use of pumped hydro storage increases the attractiveness for investments in the wind power sector and mitigates the adverse effects of the variability in the dispatch of wind-generated electricity.

scholarly journals A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Riccardo De Blasis ◽  
Giovanni Batista Masala ◽  
Filippo Petroni
Keyword(s):  
Markov Model ◽  
Electricity Market ◽  
Wind Farm ◽  
Central Italy ◽  
High Order ◽  
Distribution Model ◽  
Spot Price ◽  
Model Parameters ◽  
Price Series ◽  
Cross Correlations

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.

scholarly journals A Diode-MMC AC/DC Hub for Connecting Offshore Wind Farm and Offshore Production Platform

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3759
Author(s):  
Kai Huang ◽  
Lie Xu ◽  
Guangchen Liu
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Offshore Wind ◽  
System Control ◽  
Dc Voltage ◽  
Offshore Wind Power ◽  
Offshore Production ◽  
Production Platform ◽  
In Series ◽  
Dc Voltage Control

A diode rectifier-modular multilevel converter AC/DC hub (DR-MMC Hub) is proposed to integrate offshore wind power to the onshore DC network and offshore production platforms (e.g., oil/gas and hydrogen production plants) with different DC voltage levels. The DR and MMCs are connected in parallel at the offshore AC collection network to integrate offshore wind power, and in series at the DC terminals of the offshore production platform and the onshore DC network. Compared with conventional parallel-connected DR-MMC HVDC systems, the proposed DR-MMC hub reduces the required MMC converter rating, leading to lower investment cost and power loss. System control of the DR-MMC AC/DC hub is designed based on the operation requirements of the offshore production platform, considering different control modes (power control or DC voltage control). System behaviors and requirements during AC and DC faults are investigated, and hybrid MMCs with half-bridge and full-bridge sub-modules (HBSMs and FBSMs) are used for safe operation during DC faults. Simulation results based on PSCAD/EMTDC validate the operation of the DR-MMC hub.

Optimal participation of a virtual power plant in electricity market considering renewable energy: A deep learning-based approach

2021 ◽  
Vol 26 ◽  
pp. 100448
Author(s):  
Saleh Sadeghi Gougheri ◽  
Hamidreza Jahangir ◽  
Mahsa A. Golkar ◽  
Ali Ahmadian ◽  
Masoud Aliakbar Golkar
Keyword(s):  
Renewable Energy ◽  
Deep Learning ◽  
Power Plant ◽  
Electricity Market ◽  
Virtual Power ◽  
Virtual Power Plant

scholarly journals Value-Centric Approaches to Design, Operations, and Maintenance of Wind Turbines

2013 ◽  
Author(s):  
Madhur A. Khadabadi ◽  
Karen B. Marais
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Farm ◽  
Net Present Value ◽  
Operating Cost ◽  
Optimal Level ◽  
Two Dimensions ◽  
Alternative View ◽  
Operations And Maintenance ◽  
Farm Operators

Wind turbine maintenance is emerging as an unexpectedly high component of turbine operating cost and there is an increasing interest in managing this cost. Here, we present an alternative view of maintenance as a value-driver, and develop an optimization algorithm to maximize the value delivered by maintenance. We model the stochastic deterioration of the turbine in two dimensions: the deterioration rate, and the extent of deterioration, and view maintenance as an operator that moves the turbine to an improved state in which it can generate more power and so earn more revenue. We then use a standard net present value (NPV) approach to calculate the value of the turbine by deducting the costs incurred in the installation, operations and maintenance from the revenue due to the power generation. The application of our model is demonstrated using several scenarios with a focus on blade deterioration. We evaluate the value delivered by implementing blade condition monitoring systems (CMS). A higher fidelity CMS allows the blade state to be determined with higher precision. With this improved state information, an optimal maintenance strategy can be derived. The difference between the value of the turbine with and without CMS can be interpreted as the value of the CMS. The results indicate that a higher fidelity (and more expensive) condition monitoring system (CMS) does not necessarily yield the highest value, and, that there is an optimal level of fidelity that results in maximum value. The contributions of this work are twofold. First, it is a practical approach to wind turbine valuation and operation that takes operating and market conditions into account. This work should therefore be useful to wind farm operators and investors. Second, it shows how the value of a CMS can be explicitly assessed. This work should therefore be useful to CMS manufacturers and wind farm operators.

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