scholarly journals Optimal short-term operation and sizing of pumped-storage power plants in systems with high penetration of wind energy

2010 ◽  
Author(s):  
Juan I. Perez-Diaz ◽  
Alejandro Perea ◽  
Jose R. Wilhelmi
Keyword(s):  
Wind Energy ◽  
Power Plants ◽  
Short Term ◽  
Term Operation ◽  
High Penetration ◽  
Pumped Storage

Short-Term Generation Forecasting Against the High Penetration of the Wind Energy

2019 ◽  
Author(s):  
B.K. Hammerschmitt ◽  
F. C. Lucchese ◽  
L. N. Silva ◽  
A. R. Abaide ◽  
J. A. D. A. Rohr
Keyword(s):  
Wind Energy ◽  
Short Term ◽  
High Penetration

scholarly journals Short–Term Planning of Hybrid Power System

2016 ◽  
Vol 67 (4) ◽  
pp. 234-245 ◽  
Author(s):  
Goran Knežević ◽  
Zoran Baus ◽  
Srete Nikolovski
Keyword(s):  
Power System ◽  
Power Plants ◽  
Thermal Power ◽  
Optimization Process ◽  
Thermal Power Plants ◽  
Short Term ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Hydropower Plants ◽  
Pumped Storage

Abstract In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

scholarly journals A Combined Approach for Model-Based PV Power Plant Failure Detection and Diagnostic

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1261
Author(s):  
Christopher Gradwohl ◽  
Vesna Dimitrievska ◽  
Federico Pittino ◽  
Wolfgang Muehleisen ◽  
András Montvay ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Failure Detection ◽  
Energy Yield ◽  
Combined Approach ◽  
Levelized Cost Of Electricity ◽  
Term Operation ◽  
Model Based

Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive market environment where even small performance losses have a high impact on profit margins. Therefore, operation at maximum performance is the key for long-term profitability. This can be achieved by advanced performance monitoring and instant or gradual failure detection methodologies. We present in this paper a combined approach on model-based fault detection by means of physical and statistical models and failure diagnosis based on physics of failure. Both approaches contribute to optimized PV plant operation and maintenance based on typically available supervisory control and data acquisition (SCADA) data. The failure detection and diagnosis capabilities were demonstrated in a case study based on six years of SCADA data from a PV plant in Slovenia. In this case study, underperforming values of the inverters of the PV plant were reliably detected and possible root causes were identified. Our work has led us to conclude that the combined approach can contribute to an efficient and long-term operation of photovoltaic power plants with a maximum energy yield and can be applied to the monitoring of photovoltaic plants.

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