| 1. |
- Herre, Lars, 1990-, et al.
(författare)
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Simplified Model of Integrated Paper Mill for Optimal Bidding in Energy and Reserve Markets
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Due to the increased use of variable renewable energy sources, more capacity for reserves is required. Non-generating resources such as large industrial consumers can arbitrage energy prices and provide reserve capacity by exploiting the inherent flexibility in selected industrial processes. A large enough industrial consumer can capitalize on this flexibility through optimized bidding in electricity markets.In this work, the day-ahead cost minimization of a risk-averse pulp and paper mill is formulated as a two-stage stochastic problem, considering thermodynamic and electrical constraints. The bids in the energy and reserve markets are jointly optimized subject to price uncertainty as well as uncertainty of frequency realization. The results of a case study in Sweden display a significant economic benefit in exploiting the flexibility of integrated pulp and paper mills with electric boilers. The expected cost of the pulp and paper mill resulting from different strategies are compared and the risk-aversion of the pulp and paper mill is investigated. Reserve offers are mainly facilitated by fast-acting electric boilers and supported by flexibility in the steam network. We show that reserve offers can significantly improve the profitability of the pulp and paper mill.
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| 2. |
- Herre, Lars, 1990-, et al.
(författare)
-
Simplified model of integrated paper mill for optimal bidding in energy and reserve markets
- 2020
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 279
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Tidskriftsartikel (refereegranskat)abstract
- Due to the increased use of variable renewable energy sources, more capacity for reserves is required. Non-generating resources such as large industrial consumers can arbitrage energy prices and provide reserve capacity by exploiting the inherent flexibility in selected industrial processes. A large enough industrial consumer can capitalize on this flexibility through optimized bidding in electricity markets. In this work, the day-ahead cost minimization of a risk-averse pulp and paper mill is formulated as a two-stage stochastic problem, considering thermodynamic and electrical constraints. The bids in the energy and reserve markets are jointly optimized subject to price uncertainty as well as uncertainty of frequency realization. The results of a case study in Sweden display a significant economic benefit in exploiting the flexibility of integrated pulp and paper mills with electric boilers. The expected cost of the pulp and paper mill resulting from different strategies are compared and the risk-aversion of the pulp and paper mill is investigated. Reserve offers are mainly facilitated by fast-acting electric boilers and supported by flexibility in the steam network. We show that reserve offers can significantly improve the profitability of the pulp and paper mill.
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| 3. |
- Babazadeh, Davood, 1982-, et al.
(författare)
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Distributed Two-stage Network Topology Processor for HVDC Grid Operation
- 2017
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Ingår i: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING. - : IEEE. - 9781538622124
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Konferensbidrag (refereegranskat)abstract
- This paper presents the results of an analysis of distributed two-stage coordination of network topology processor for HVDC grids. In the first stage of the two-stage processor, the substation topology is analyzed locally using an automated graph based algorithm. Thereafter, a distributed algorithm is proposed to used the neighboring information to realize the grid connectivity. For distributed islanding detection, the connectivity problem is formulated as a set of linear equations and solved iteratively using successive-over-relaxation method. The performance of the proposed methods versus conventional one-stage method has been tested in an islandinv, scenario for a 5-terminal HVDC grid.
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| 4. |
- Blaauwbroek, Niels, et al.
(författare)
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Interfacing solutions for power hardware-inthe- loop simulations of distribution feeders for testing monitoring and control applications
- 2017
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Ingår i: IET Generation, Transmission & Distribution. - : IET Digital Library. - 1751-8687 .- 1751-8695.
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Tidskriftsartikel (refereegranskat)abstract
- The need for advanced monitoring and control applications (MCAs) in future distribution networks calls for highly accurate and fully integrated simulation solutions for the purpose of performance assessment of these MCAs. Offline simulation using models of the power system, measurement equipment, local controllers and the information and communication infrastructure do not always resemble reality accurate enough. Therefore, power hardware-in-the-loop (PHIL) simulations are considered a cost-effective approach to overcome these challenges. This study presents the design of a PHIL-interface that allows to integrate a physical low-voltage feeder within a larger real-time simulated distribution network. Using the combination of the physical network and the larger simulated network, MCAs can be tested for scalability as well as accuracy. A data acquisition and processing system is presented that acquires all the true system states of both the physical feeder and the real-time simulated network, such that the MCAs can be verified in real-time. The functioning of the PHIL-interface is validated using practical results and illustrated using a test case for the performance assessment of a branch current state estimation algorithm.
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| 5. |
- Brodén, Daniel A., 1989-
(författare)
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Modeling and Simulations of Demand Response in Sweden
- 2017
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Electric power systems are undergoing a paradigm shift where an increasing number of variable renewable energy resources such as wind and solar power are being introduced to all levels of existing power grids. At the same time consumers are gaining a more active role where self energy production and home automation solutions are no longer uncommon. This challenges traditional power systems which were designed to serve as a centralized top-down solution for providing electricity to consumers. Demand response has risen as a promising solution to cope with some of the challenges that this shift is creating. In this thesis, control and scheduling studies using demand response, and consumer load models adapted to environments similar to Sweden are proposed and evaluated. The studies use model predictive control approaches for the purpose of providing ancillary and financial services to electricity market actors using thermal flexibility from detached houses. The approaches are evaluated on use-cases using data from Sweden for the purpose of reducing power imbalances of a balance responsible player and congestion management for a system operator. Simulations show promising results for reducing power imbalances by up to 30% and managing daily congestion of 5-19 MW using demand response. Moreover, a consumer load model of an office building is proposed using a gray-box modeling approach combining physical understanding of buildings with empirical data. Furthermore, the proposed consumer load model along with a similar model for detached houses are packaged and made freely available as MATLAB applications for other researchers and stakeholders working with demand response. The applications allow the user to generate synthetic electricity load profiles for heterogeneous populations of detached houses and office buildings down to 1-min resolution. The aim of this thesis has been to summarize and discuss the main highlights of the included articles. The interested reader is encouraged to investigate further details in the second part of the thesis as they provide a more comprehensive account of the studies and models proposed.
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| 6. |
- Brodén, Daniel, 1989-, et al.
(författare)
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Anticipating Overrides of Schedulable Space Heating Systems in Detached Houses for Demand Response
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we propose and evaluate two cases of a model predictive scheduling approach to anticipate overrides of schedulable electric space heating systems in detached houses. We assume a demand-response set-up where the space heating systems of a population of heterogeneous detached houses are scheduled over a finite horizon with the objective of having their aggregated space heating load follow a desired load profile. We envision that the desired load profile provides hourly to sub-hourly ancillary services to electricity market actors and define schedule overrides as the interruption of demand response following a violation of the indoor temperature comfort in a house. We use a model to represent the indoor temperature change in detached houses on minute resolution which considers, among other variables, weather- and individual behavioral-related heat gains and losses in the building. The model predictive scheduling approach is evaluated on a use-case consisting of a balance responsible player looking to minimize its daily expected power imbalances on the intraday market. The scheduling is performed on 100 detached houses participating in demand-response for two predictive cases and a non-predictive case for comparison. The predictive cases differ in the level of information known about thebuilding attributes of the population. Simulations are performed for 90 consecutive days corresponding to a Swedish winter period where results indicate power imbalance reductions of up to 30% and notable differences between predictive cases.
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| 7. |
- Brodén, Daniel, 1989-, et al.
(författare)
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MATLAB Applications to Generate Synthetic Electricity Load Profiles of Office Buildings and Detached Houses
- 2017
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Ingår i: 2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1-6.
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Konferensbidrag (refereegranskat)abstract
- In this paper we present two MATLAB applications that generates synthetic electricity load profiles for office buildings and detached houses down to 1-minute resolution. The applications have been developed using App Designer — a MATLAB environment for application development. The applications are based on consumer load models for office buildings and detached houses published in previous research work. The aim of this paper is to present an overview of the application functionalities, code design, assumptions and limitations, and examples of their potential use in power system education and research. To the author’s knowledge these are the first applications which allow generating synthetic load profiles for office buildings and houses in practical and intuitive manner where building attributes can be easily configured.
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| 8. |
- Cheng, Li, et al.
(författare)
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Design of Neural Network for Adaptive Current Control with Different Short-Circuit Ratios
- 2022
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Ingår i: Proceedings IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Current control of grid-connected converters may result in harmonic instability when grid impedance changes. To prevent this issue, current controller parameters can be tuned adaptively according to different short-circuit ratios (SCRs). It is thus important to estimate the grid impedance in real-time. Unlike traditional FFT-based impedance measurement methods, a more efficient estimation approach based on neural networks is proposed in this paper. This method does not require a fixed and relatively long sampling window, making it possible for real-time impedance measurement. Further, a step-by-step design method of the feedforward neural network (FNN) used for grid impedance estimation is developed. Time-domain simulation results validate the effectiveness of the approach. Based on the designed FNN, adaptive current control is implemented and verified through simulation.
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| 9. |
- Cheng, Li, et al.
(författare)
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Neural-Network-Based Impedance Estimation for Transmission Cables Considering Aging Effect
- 2023
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Ingår i: 2023 8th IEEE Workshop on the Electronic Grid, eGRID 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- In power-electronic-based power systems like wind farms, conducting stability analysis necessitates a comprehensive understanding of the system impedance across a wide frequency range, from sub-harmonic frequencies up to the Nyquist frequency of control systems of power converters. The cable aging effect can significantly impact the cable impedance, while accurately estimating the degree of aging proves challenging. To avoid the requirement for precise aging prognostic, this paper proposes an approach based on Artificial Neural Networks (ANN) that enables the estimation of AC cable impedance in a wind farm solely through fundamental frequency measurements. The data used for training the ANN is obtained from the cable model in PSCAD, incorporating physical and geometrical parameters, which accurately approximates real cables within power systems. The training results of the ANN validate the accuracy of the proposed identification approach. As a result, the proposed approach effectively eliminates the potential misjudgment of system stability caused by the aging effect of power cables.
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| 10. |
- Cheng, Li, et al.
(författare)
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Online Identification of Wind Farm Wide Frequency Admittance with Power Cables Using the Artificial Neural Network
- 2023
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Ingår i: 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1530-1535
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Konferensbidrag (refereegranskat)abstract
- In power-electronic-based power systems like wind farms, stability analysis requires knowledge of system impedance across a wide frequency range, from sub-harmonic frequencies to the Nyquist frequency. Although it is feasible to take the fundamental frequency measurement during power system operation, obtaining a wide-frequency impedance curve in real time is very challenging. This paper proposed an ANN-based approach to estimate wide-frequency system admittance of wind farms with power cables, through fundamental frequency measurements. Real-life uncertainties are considered, including shunt capacitor injection, filter inductance variance, cable aging, errors in voltage and current measurements, and the variance of other system parameters. The generalization ability of the ANN is validated on a new dataset with different uncertainty distributions, and the error sensitivity to the potential system parameter variance is evaluated. These results can be referenced in the data acquisition step in future neural-network-based applications.
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