The Successful Integration of Industrial Owned Cogeneration into the Bulk Power Systems of Regulated Utilities

1986 ◽  
Vol PER-6 (12) ◽  
pp. 8-8
2021 ◽  
Author(s):  
Jordan Kern ◽  
Nathalie Voisin ◽  
Sean Turner ◽  
Hongxiang Yan ◽  
Konstantinos Oikonomou

<p>Given the wide range of institutional and market contexts in which hydroelectric dams are operated, determining the value added from improvements in hydrologic forecasts is a challenge. Many previous examples of hydrologic forecasts being used to optimize hydropower production strategies at dams focus on a single reservoir system or watershed, with a key assumption that the marginal value of hydropower production is exogenously-defined (dams are ‘price takers’ in markets for electricity that exhibit no market power). In some cases, this may accurately reflect current institutional boundaries and decision making processes. However, with increased attention being paid to how more coordinated grid management strategies, including management of hydropower assets, could facilitate deep integration of renewable energy, it is critical to understand how the use of improved hydrologic forecasts could produce wider grid-scale benefits, including  lower costs and emissions. In this study, we quantify the value of streamflow forecasts to a centralized power system operator in charge of coordinating sub-weekly operations of hydropower assets, using the Western U.S. as a case study. We propagate flow forecasts through realistic models of reservoir operations and models of bulk power systems/wholesale electricity markets. Our results shed light on how the value of flow forecasts to grid operations can vary across regions and power systems. They also highlight the potential for conflicts between firm-specific objectives (profit maximization) and system-wide objectives (minimization of costs and emissions) when determining value added from hydrologic forecasts.  </p>


Islanding detection is a necessary function for grid connected distributed generators. Usually, islanding detection methods can be classified as two catalogues: remote detecting methods and local detecting methods. Most of them have limitation and defects when they are applied in photovoltaic power stations. Recently synchronous phasor measuring units (PMU) is proposed to be applied for islanding detecting. Although the islanding detection method is supposed to be applied for traditional bulk power systems, it is also suitable for renewable generation power plants. To do this islanding detection will be implemented on central management unit of photovoltaic power station instead of on grid-tied inverters as traditionally. In implementing, the criteria of this method and the threshold of algorithm are needed to be optimized. This paper develops a test device which can optimize PMU-based islanding detection technology to validate the proposed islanding detection method applying in PV station. Then using simulation to discuss how to set a reasonable threshold for the researched islanding detection method applied in PV stations. Finally the paper provides a platform for the algorithm optimization.


2020 ◽  
Vol 10 (17) ◽  
pp. 5964 ◽  
Author(s):  
Tej Krishna Shrestha ◽  
Rajesh Karki

Renewable energy resources like wind generation are being rapidly integrated into modern power systems. Energy storage systems (ESS) are being viewed as a game-changer for renewable integration due to their ability to absorb the variability and uncertainty arising from the wind generation. While abundant literature is available on system adequacy and operational reliability evaluation, operational adequacy studies considering wind and energy storage have received very little attention, despite their elevated significance. This work presents a novel framework that integrates wind power and energy storage models to a bulk power system model to sequentially evaluate the operational adequacy in the operational mission time. The analytical models are developed using a dynamic system state probability evaluation approach by incorporating a system state probability estimation technique, wind power probability distribution, state enumeration, state transition matrix, and time series analysis in order to quantify the operational adequacy of a bulk power system integrated with wind power and ESS. The loss of load probability (LOLP) is used as the operational adequacy index to quantify the spatio-temporal variation in risk resulting from the generation and load variations, their distribution on the network structure, and the operational strategies of the integrated ESS. The proposed framework is aimed to serve as a guideline for operational planning, thereby simplifying the decision-making process for system operators while considering resources like wind and energy storage facilities. The methodology is applied to a test system to quantify the reliability and economic benefits accrued from different operational strategies of energy storage in response to wind generation and other operational objectives in different system scenarios.


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