scholarly journals Management of Wind Power Variations in Electricity System Investment Models

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Lisa Göransson ◽  
Caroline Granfeldt ◽  
Ann-Brith Strömberg
Keyword(s):  
Parallel Processing ◽  
Wind Power ◽  
Capacity Expansion ◽  
Total System ◽  
Time Dimension ◽  
Electricity System ◽  
Novel Approach ◽  
The Hours ◽  
Fully Connected ◽  
Investment Models

AbstractAccounting for variability in generation and load and strategies to tackle variability cost-efficiently are key components of investment models for modern electricity systems. This work presents and evaluates the Hours-to-Decades (H2D) model, which builds upon a novel approach to account for strategies to manage variations in the electricity system covering several days, the variation management which is of particular relevance to wind power integration. The model discretizes the time dimension of the capacity expansion problem into 2-week segments, thereby exploiting the parallel processing capabilities of modern computers. Information between these segments is then exchanged in a consensus loop. The method is evaluated with regard to its ability to account for the impacts of strategies to manage variations in generation and load, regional resources and trade, and inter-annual linkages. Compared to a method with fully connected time, the proposed method provides solutions with an increase in total system cost of no more than 1.12%, while reducing memory requirements to 1/26’th of those of the original problem. For capacity expansion problems concerning two regions or more, it is found that the H2D model requires 1–2% of the calculation time relative to a model with fully connected time when solved on a computer with parallel processing capability.

Probabilistic estimation of spinning reserves in smart grids with Bayesian-driven reserve allocation adjustment algorithm

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yerzhigit Bapin ◽  
Vasilios Zarikas
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Unit Commitment ◽  
Wind Power Generation ◽  
Total System ◽  
Spinning Reserve ◽  
Content Type ◽  
Novel Approach ◽  
Spinning Reserves ◽  
Actual Unit

Purpose This study aims to introduce a methodology for optimal allocation of spinning reserves taking into account load, wind and solar generation by application of the univariate and bivariate parametric models, conventional intra and inter-zonal spinning reserve capacity as well as demand response through utilization of capacity outage probability tables and the equivalent assisting unit approach. Design/methodology/approach The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern probability density function (PDF). The study also uses the Bayesian network (BN) algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours. Findings The results show that the utilization of bivariate wind prediction model along with reserve allocation adjustment algorithm improve reliability of the power grid by 2.66% and reduce the total system operating costs by 1.12%. Originality/value The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern PDF. The study also uses the BN algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

scholarly journals Enhancing Wind Turbine Power Forecast via Convolutional Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 261
Author(s):  
Tianyang Liu ◽  
Zunkai Huang ◽  
Li Tian ◽  
Yongxin Zhu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Rapid Development ◽  
Superior Performance ◽  
Learning Platform ◽  
Novel Approach ◽  
Wind Power Forecast ◽  
Transformation Methods

The rapid development in wind power comes with new technical challenges. Reliable and accurate wind power forecast is of considerable significance to the electricity system’s daily dispatching and production. Traditional forecast methods usually utilize wind speed and turbine parameters as the model inputs. However, they are not sufficient to account for complex weather variability and the various wind turbine features in the real world. Inspired by the excellent performance of convolutional neural networks (CNN) in computer vision, we propose a novel approach to predicting short-term wind power by converting time series into images and exploit a CNN to analyze them. In our approach, we first propose two transformation methods to map wind speed and precipitation data time series into image matrices. After integrating multi-dimensional information and extracting features, we design a novel CNN framework to forecast 24-h wind turbine power. Our method is implemented on the Keras deep learning platform and tested on 10 sets of 3-year wind turbine data from Hangzhou, China. The superior performance of the proposed method is demonstrated through comparisons using state-of-the-art techniques in wind turbine power forecasting.

Application of Power Communication System in Wind Power Plant

2013 ◽  
Vol 724-725 ◽  
pp. 655-658
Author(s):  
Rui Jing Shi ◽  
Xiao Chao Fan ◽  
Feng Ting Li ◽  
Bo Wei
Keyword(s):  
Wireless Communication ◽  
Wind Power ◽  
Communication System ◽  
Transmission Rate ◽  
Wind Farms ◽  
Optical Fiber Communication ◽  
Total System ◽  
Fiber Communication ◽  
Network Transmission ◽  
Cable Communication

The application of power communication system in the field of wind power mainly includes the overall system communication and local field communication. During the operation of wind farms, the total system requires that the electric power communication system should provide reliable rapid information channel, accuracy of transmission on a variety of digital business. This article will focus on the application of power communication system between the wind turbine and the booster station, which includes optical fiber communication, communication and leased public circuit, as well as the cable communication, wireless communication, microwave wireless communication. Finally, in the premise of various communications comparison, according to the actual situation of the wind power field, the network transmission rate and reliability should be considered to the requirements of power market.

scholarly journals Impacts of Electric Road Systems on the German and Swedish Electricity Systems—An Energy System Model Comparison

2021 ◽  
Vol 9 ◽  
Author(s):  
Johanna Olovsson ◽  
Maria Taljegard ◽  
Michael Von Bonin ◽  
Norman Gerhardt ◽  
Filip Johnsson
Keyword(s):  
Wind Power ◽  
Peak Power ◽  
Large Scale ◽  
Solar Power ◽  
Energy System ◽  
Transport Sector ◽  
Electricity System ◽  
Road Systems ◽  
The Impact ◽  
Electricity Systems

This study analyses the impacts of electrification of the transport sector, involving both static charging and electric road systems (ERS), on the Swedish and German electricity systems. The impact on the electricity system of large-scale ERS is investigated by comparing the results from two model packages: 1) a modeling package that consists of an electricity system investment model (ELIN) and electricity system dispatch model (EPOD); and 2) an energy system investment and dispatch model (SCOPE). The same set of scenarios are run for both model packages and the results for ERS are compared. The modeling results show that the additional electricity load arising from large-scale implementation of ERS is mainly, depending on model and scenario, met by investments in wind power in Sweden (40–100%) and in both wind (20–75%) and solar power (40–100%) in Germany. This study also concludes that ERS increase the peak power demand (i.e., the net load) in the electricity system. Therefore, when using ERS, there is a need for additional investments in peak power units and storage technologies to meet this new load. A smart integration of other electricity loads than ERS, such as optimization of static charging at the home location of passenger cars, can facilitate efficient use of renewable electricity also with an electricity system including ERS. A comparison between the results from the different models shows that assumptions and methodological choices dictate which types of investments are made (e.g., wind, solar and thermal power plants) to cover the additional demand for electricity arising from the use of ERS. Nonetheless, both modeling packages yield increases in investments in solar power (Germany) and in wind power (Sweden) in all the scenarios, to cover the new electricity demand for ERS.

An Analytical Approach for DG Placement in Reconfigured Distribution Networks

2016 ◽  
Vol 5 (3) ◽  
pp. 137
Author(s):  
Sarfaraz Nawaz ◽  
Ajay Bansal ◽  
M. P. Sharma
Keyword(s):  
Distribution System ◽  
Mathematical Formulation ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Type I ◽  
Total System ◽  
Power Losses ◽  
Real Power ◽  
Novel Approach ◽  
Operating Constraints

<p>A novel approach is proposed in this paper for optimal placement of DG units in reconfigured distribution system with the aim of reduction of real power losses while satisfying operating constraints. The proposed analytical method for optimal DG placement is developed based on a new mathematical formulation. Type-I and type-II DG units are used here. The results of the proposed technique are validated on IEEE 69 bus distribution system. The level of DG penetration is also considered in a range of 0–50% of total system load. A novel index is also proposed which incorporates level of DG penetration and percentage reduction in real power losses. The results are promising when compared with recently proposed algorithms.</p>

scholarly journals The Benefit of Collaboration in the North European Electricity System Transition—System and Sector Perspectives

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4648 ◽  
Author(s):  
Lisa Göransson ◽  
Mariliis Lehtveer ◽  
Emil Nyholm ◽  
Maria Taljegard ◽  
Viktor Walter
Keyword(s):  
Steel Industry ◽  
Heat Supply ◽  
Fossil Fuels ◽  
Transport Sector ◽  
Total System ◽  
Electricity Prices ◽  
The North ◽  
Electricity System ◽  
System Transition ◽  
The Impact

This work investigates the connection between electrification of the industry, transport, and heat sector and the integration of wind and solar power in the electricity system. The impact of combining electrification of the steel industry, passenger vehicles, and residential heat supply with flexibility provision is evaluated from a systems and sector perspective. Deploying a parallel computing approach to the capacity expansion problem, the impact of flexibility provision throughout the north European electricity system transition is investigated. It is found that a strategic collaboration between the electricity system, an electrified steel industry, an electrified transport sector in the form of passenger electric vehicles (EVs) and residential heat supply can reduce total system cost by 8% in the north European electricity system compared to if no collaboration is achieved. The flexibility provision by new electricity consumers enables a faster transition from fossil fuels in the European electricity system and reduces thermal generation. From a sector perspective, strategic consumption of electricity for hydrogen production and EV charging and discharging to the grid reduces the number of hours with very high electricity prices resulting in a reduction in annual electricity prices by up to 20%.

scholarly journals Impact of Combined Demand-Response and Wind Power Plant Participation in Frequency Control for Multi-Area Power Systems

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1687 ◽  
Author(s):  
Irene Muñoz-Benavente ◽  
Anca D. Hansen ◽  
Emilio Gómez-Lázaro ◽  
Tania García-Sánchez ◽  
Ana Fernández-Guillamón ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Wind Power ◽  
Demand Response ◽  
Power Plants ◽  
Frequency Control ◽  
Frequency Regulation ◽  
Wind Power Plant ◽  
Total System ◽  
Interconnected Power Systems

An alternative approach for combined frequency control in multi-area power systems with significant wind power plant integration is described and discussed in detail. Demand response is considered as a decentralized and distributed resource by incorporating innovative frequency-sensitive load controllers into certain thermostatically controlled loads. Wind power plants comprising variable speed wind turbines include an auxiliary frequency control loop contributing to increase total system inertia in a combined manner, which further improves the system frequency performance. Results for interconnected power systems show how the proposed control strategy substantially improves frequency stability and decreases peak frequency excursion (nadir) values. The total need for frequency regulation reserves is reduced as well. Moreover, the requirements to exchange power in multi-area scenarios are significantly decreased. Extensive simulations under power imbalance conditions for interconnected power systems are also presented in the paper.

Network Anomaly Analysis using the Microsoft HoloLens

2018 ◽  
Vol 62 (1) ◽  
pp. 2094-2098
Author(s):  
Steve Beitzel ◽  
Josiah Dykstra ◽  
Paul Toliver ◽  
Jason Youzwak
Keyword(s):  
User Study ◽  
Mixed Reality ◽  
Eye Gaze ◽  
Lessons Learned ◽  
Time Dimension ◽  
Desktop Computer ◽  
Novel Approach ◽  
Anomaly Analysis ◽  
Microsoft Hololens ◽  
Future Work

We investigate the feasibility of using Microsoft HoloLens, a mixed reality device, to visually analyze network capture data and locate anomalies. We developed MINER, a prototype application to visualize details from network packet captures as 3D stereogram charts. MINER employs a novel approach to time-series visualization that extends the time dimension across two axes, thereby taking advantage of the immersive 3D space available via the HoloLens. Users navigate the application through eye gaze and hand gestures to view summary and detailed bar graphs. Callouts display additional detail based on the user’s immediate gaze. In a user study, volunteers used MINER to locate network attacks in a dataset from the 2013 VAST Challenge. We compared the time and effort with a similar test using traditional tools on a desktop computer. Our findings suggest that network anomaly analysis with the HoloLens achieved comparable effectiveness, efficiency and satisfaction. We describe user metrics and feedback collected from these experiments; lessons learned and suggested future work.

scholarly journals Electric Vehicles as Flexibility Management Strategy for the Electricity System—A Comparison between Different Regions of Europe

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2597 ◽  
Author(s):  
Maria Taljegard ◽  
Lisa Göransson ◽  
Mikael Odenberger ◽  
Filip Johnsson
Keyword(s):  
Wind Power ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Road Transport ◽  
Investment Model ◽  
Transport Sector ◽  
Renewable Electricity ◽  
Technical Limitation ◽  
Electricity System ◽  
The Uk

This study considers whether electric vehicles (EVs) can be exploited as a flexibility management strategy to stimulate investments in and operation of renewable electricity under stringent CO2 constraints in four regions with different conditions for renewable electricity (Sweden, Germany, the UK, and Spain). The study applies a cost-minimisation investment model and an electricity dispatch model of the European electricity system, assuming three types of charging strategies for EVs. The results show that vehicle-to-grid (V2G), i.e., the possibility to discharging the EV batteries back to grid, facilitates an increase in investments and generation from solar photovoltaics (PVs) compare to the scenario without EVs, in all regions except Sweden. Without the possibility to store electricity in EV batteries across different days, which is a technical limitation of this type of model, EVs increase the share of wind power by only a few percentage points in Sweden, even if Sweden is a region with good conditions for wind power. Full electrification of the road transport sector, including also dynamic power transfer for trucks and buses, would decrease the need for investments in peak power in all four regions by at least 50%, as compared to a scenario without EVs or with uncontrolled charging of EVs, provided that an optimal charging strategy and V2G are implemented for the passenger vehicles.

A Novel Approach of Battery Energy Storage for Improving Value of Wind Power in Deregulated Markets

2013 ◽  
Vol 14 (3) ◽  
pp. 255-264 ◽  
Author(s):  
Y Minh Nguyen ◽  
Yong Tae Yoon
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Wind Power ◽  
Frequency Control ◽  
Minimum Cost ◽  
Wind Generation ◽  
Frequency Regulation ◽  
Battery Energy Storage ◽  
Novel Approach ◽  
Battery Energy

Abstract Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

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