scholarly journals Optimal power flow model for building integrated photovoltaic systems operating in the Andean range

2019 ◽  
Vol 16 (1) ◽  
pp. 52
Author(s):  
Andres Julian Aristizabal ◽  
Daniel Ospina ◽  
Mónica Castaneda ◽  
Sebastian Zapata ◽  
Edison Banguero
Keyword(s):  
Power Output ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Meteorological Data ◽  
Correlation Factor ◽  
Photovoltaic System ◽  
Photovoltaic Array ◽  
Optimal Power ◽  
Building Integrated Photovoltaic ◽  
Array Performance

<p>This paper presents a novel model to evaluate the power output of a building integrated photovoltaic system (BIPVS) operating in the Andean Range.  The Optimal Power Flow (OPF) model optimizes the power output of the BIPVS within an electrical system without violating operational limits.  The model is validated with the experimental performance of a 6 kW BIPVS installed in Bogota, Colombia. The meteorological data affect the power flow. The model is evaluated under sunny and rainy days to characterize the photovoltaic array performance. The results showed that the AC PV-energy generation was 5,904 kWh/year for 2017 and that there is a correlation factor of 99.87% between the experimental power flow and the proposed model.</p>

scholarly journals Optimal Power Flow Calculation Considering Large-Scale Photovoltaic Generation Correlation

2020 ◽  
Vol 8 ◽  
Author(s):  
He Li ◽  
Huijun Li ◽  
Weihua Lu ◽  
Zhenhao Wang ◽  
Jing Bian
Keyword(s):  
Power Flow ◽  
Power Plants ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Short Term Memory ◽  
Photovoltaic System ◽  
Power Flow Calculation ◽  
Flow Calculation ◽  
Optimal Power ◽  
The Impact

In order to analyze the impact of large-scale photovoltaic system on the power system, a photovoltaic output prediction method considering the correlation is proposed and the optimal power flow is calculated. Firstly, establish a photovoltaic output model to obtain the attenuation coefficient and fluctuation amount, and analyze the correlation among the multiple photovoltaic power plants through the k-means method. Secondly, the long short-term memory (LSTM) neural network is used as the photovoltaic output prediction model, and the clustered photovoltaic output data is brought into the LSTM model to generate large-scale photovoltaic prediction results with the consideration of the spatial correlation. And an optimal power flow model that takes grid loss and voltage offset as targets is established. Finally, MATLAB is used to verify that the proposed large-scale photovoltaic forecasting method has higher accuracy. The multi-objective optimal power flow calculation is performed based on the NSGA-II algorithm and the modified IEEE systems, and the optimal power flow with photovoltaic output at different times is compared and analyzed.

Optimal Power Flow Considering Generator Number Constraint on Regulation of Active Power Output

2014 ◽  
Vol 672-674 ◽  
pp. 1042-1047
Author(s):  
Yu De Yang ◽  
Pei Xian Qu
Keyword(s):  
Power Output ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Optimal Solution ◽  
Active Power ◽  
Interior Point Algorithm ◽  
Discrete Variables ◽  
Optimal Power ◽  
The Relationship

Operation number constraint of control means isn’t considered to traditional optimal power flow model, and at optimal solution all the control variables often be changed, which causes a tedious dispatching plan and is difficult to operate. In this paper, Optimal Power Flow (OPF) with constraints limiting the number of control actions was discussed, and 0-1 discrete variables of model was transformed to complementary constraint, then modern interior point algorithm was used for solving. Through simulation the relationship between generator number constraint on regulation of the active power output and optimization objective was explored, which could obtain best balance point on two, and close to conventional OPF optimization objective with reducing the number of regulation.

scholarly journals Optimal Management of a Microgrid with Radiation and Wind-Speed Forecasting: A Case Study Applied to a Bioclimatic Building

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2398
Author(s):  
Luis O. Polanco Vásquez ◽  
Víctor M. Ramírez ◽  
Diego Langarica Córdova ◽  
Juana López Redondo ◽  
José Domingo Álvarez ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Energy Management ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Photovoltaic System ◽  
Management Tool ◽  
Optimal Power ◽  
Double Exponential Smoothing ◽  
The University

An Energy Management System (EMS) that uses a Model Predictive Control (MPC) to manage the flow of the microgrids is described in this work. The EMS integrates both wind speed and solar radiation predictors by using a time series to perform the primary grid forecasts. At each sampling data measurement, the power of the photovoltaic system and wind turbine are predicted. Then, the MPC algorithm uses those predictions to obtain the optimal power flows of the microgrid elements and the main network. In this work, three time-series predictors are analyzed. As the results will show, the MPC strategy becomes a powerful energy management tool when it is integrated with the Double Exponential Smoothing (DES) predictor. This new scheme of integrating the DES method with an MPC presents a good management response in real-time and overcomes the results provided by the Optimal Power Flow method, which was previously proposed in the literature. For the case studies, the test microgrid located in the CIESOL bioclimatic building of the University of Almeria (Spain) is used.

scholarly journals Robust Stochastic Dynamic Optimal Power Flow Model of Electricity-Gas Integrated Energy System considering Wind Power Uncertainty

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhengfeng Qin ◽  
Xiaoqing Bai ◽  
Xiangyang Su
Keyword(s):  
Stochastic Optimization ◽  
Wind Power ◽  
Power Output ◽  
Gas Turbines ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Mixed Integer ◽  
Stochastic Dynamic ◽  
Optimal Power

The application of gas turbines and power to gas equipment deepens the coupling relationship between power systems and natural gas systems and provides a new way to absorb the uncertain wind power as well. The traditional stochastic optimization and robust optimization algorithms have some limitations and deficiencies in dealing with the uncertainty of wind power output. Therefore, we propose a robust stochastic optimization (RSO) model to solve the dynamic optimal power flow model for electricity-gas integrated energy systems (IES) considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance. Then, the Wasserstein ambiguity set is affined to the eventwise ambiguity set, and the proposed RSO model is transformed into a mixed-integer programming model, which can be solved rapidly and accurately using commercial solvers. Numerical results for EG-4 and EG-118 systems verify the rationality and effectiveness of the proposed model.

Optimal Power Flow Using Newton’s Method

2012 ◽  
Vol 3 (2) ◽  
pp. 167-169
Author(s):  
F.M.PATEL F.M.PATEL ◽  
◽  
N. B. PANCHAL N. B. PANCHAL
Keyword(s):  
Newton’S Method ◽  
Newton's Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Power

Designing the Electricity Market with Energy Storage Devices

2020 ◽  
Vol 12 (12) ◽  
pp. 31-43
Author(s):  
Tatiana A. VASKOVSKAYA ◽  
◽  
Boris A. KLUS ◽  
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Energy System ◽  
Energy Storage Systems ◽  
Storage Model ◽  
Optimal Power ◽  
Wide Range

The development of energy storage systems allows us to consider their usage for load profile leveling during operational planning on electricity markets. The paper proposes and analyses an application of an energy storage model to the electricity market in Russia with the focus on the day ahead market. We consider bidding, energy storage constraints for an optimal power flow problem, and locational marginal pricing. We show that the largest effect for the market and for the energy storage system would be gained by integration of the energy storage model into the market’s optimization models. The proposed theory has been tested on the optimal power flow model of the day ahead market in Russia of 10000-node Unified Energy System. It is shown that energy storage systems are in demand with a wide range of efficiencies and cycle costs.

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