Robert Eriksson - Academia.edu (original) (raw)

Papers by Robert Eriksson

arXiv (Cornell University), Jun 4, 2018

arXiv (Cornell University), Aug 15, 2019

This paper develops a new method for voltage instability prediction using a recurrent neural netw... more This paper develops a new method for voltage instability prediction using a recurrent neural network with long short-term memory. The method is aimed to be used as a supplementary warning system for system operators, capable of assessing whether the current state will cause voltage instability issues several minutes into the future. The proposed method use a long sequence-based network, where both real-time and historic data are used to enhance the classification accuracy. The network is trained and tested on the Nordic32 test system, where combinations of different operating conditions and contingency scenarios are generated using time-domain simulations. The method shows that almost all N-1 contingency test cases were predicted correctly, and N-1-1 contingency test cases were predicted with over 93 % accuracy only seconds after a disturbance. Further, the impact of sequence length is examined, showing that the proposed long sequenced-based method provides significantly better classification accuracy than both a feedforward neural network and a network using a shorter sequence.

In this paper we unify electricity market operations with power system security considerations. U... more In this paper we unify electricity market operations with power system security considerations. Using data-driven techniques, we address both small signal stability and steady-state security, derive tractable decision rules in the form of line flow limits, and incorporate the resulting constraints in market clearing algorithms. Our goal is to minimize redispatching actions, and instead allow the market to determine the most cost-efficient dispatch while considering all security constraints. To maintain tractability of our approach we perform our security assessment offline, examining large datasets, both from measurements and simulations, in order to determine stable and unstable operating regions. With the help of decision trees, we transform this information to linear decision rules for line flow constraints. We propose conditional line transfer limits, which can accurately capture security considerations, while being less conservative than current approaches. Our approach can be scalable for large systems, accounts explicitly for power system security, and enables the electricity market to identify a cost-efficient dispatch avoiding redispatching actions. We demonstrate the performance of our method in a case study.

IET smart grid, May 29, 2020

This study develops a machine learning-based method for a fast estimation of the dynamic voltage ... more This study develops a machine learning-based method for a fast estimation of the dynamic voltage security margin (DVSM). The DVSM can incorporate the dynamic system response following a disturbance and it generally provides a better measure of security than the more commonly used static voltage security margin (VSM). Using the concept of transient P-V curves, this study first establishes and visualises the circumstances when the DVSM is to prefer the static VSM. To overcome the computational difficulties in estimating the DVSM, this study proposes a method based on training two separate neural networks on a data set composed of combinations of different operating conditions and contingency scenarios generated using time-domain simulations. The trained neural networks are used to improve the search algorithm and significantly increase the computational efficiency in estimating the DVSM. The machine learning-based approach is thus applied to support the estimation of the DVSM, while the actual margin is validated using time-domain simulations. The proposed method was tested on the Nordic32 test system and the number of time-domain simulations was possible to reduce with ∼70%, allowing system operators to perform the estimations in near real-time.

arXiv (Cornell University), Jul 9, 2022

Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-... more Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-dimensional control problems. In this study, a real-time control system based on DRL is developed for long-term voltage stability events. The possibility of using system services from demand response (DR) and energy storage systems (ESS) as control measures to stabilize the system is investigated. The performance of the DRL control is evaluated on a modified Nordic32 test system. The results show that the DRL control quickly learns an effective control policy that can handle the uncertainty involved when using DR and ESS. The DRL control is compared to a rule-based load shedding scheme and the DRL control is shown to stabilize the system both significantly faster and with lesser load curtailment. Finally, when testing and evaluating the performance on load and disturbance scenarios that were not included in the training data, the robustness and generalization capability of the control were shown to be effective.

arXiv (Cornell University), Dec 1, 2020

The post-contingency loadability limit (PCLL) and the secure operating limit (SOL) are the two ma... more The post-contingency loadability limit (PCLL) and the secure operating limit (SOL) are the two main approaches used in computing the security margins of an electric power system. While the SOL is significantly more computationally demanding than the PCLL, it can account for the dynamic response after a disturbance and generally provides a better measure of the security margin. In this study, the difference between these two methods is compared and analyzed for a range of different contingency and load model scenarios. A methodology to allow a fair comparison between the two security margins is developed and tested on a modified version of the Nordic32 test system. The study shows that the SOL can differ significantly from the PCLL, especially when the system has a high penetration of loads with constant power characteristics, or a large share of induction motor loads with fast load restoration. The difference between the methods is also tested for different contingencies, where longer fault clearing times are shown to significantly increase the difference between the two margins.

IEEE Transactions on Power Systems, 2021

This paper develops a new method for voltage instability prediction using a recurrent neural netw... more This paper develops a new method for voltage instability prediction using a recurrent neural network with long short-term memory. The method is aimed to be used as a supplementary warning system for system operators, capable of assessing whether the current state will cause voltage instability issues several minutes into the future. The proposed method use a long sequence-based network, where both real-time and historic data are used to enhance the classification accuracy. The network is trained and tested on the Nordic32 test system, where combinations of different operating conditions and contingency scenarios are generated using time-domain simulations. The method shows that almost all N-1 contingency test cases were predicted correctly, and N-1-1 contingency test cases were predicted with over 93 % accuracy only seconds after a disturbance. Further, the impact of sequence length is examined, showing that the proposed long sequenced-based method provides significantly better classification accuracy than both a feedforward neural network and a network using a shorter sequence.

American Journal of Applied Sciences, 2008

This study presents transient stability assessment of electrical power system using Probabilistic... more This study presents transient stability assessment of electrical power system using Probabilistic Neural Network (PNN) and principle component analysis. Transient stability of a power system is first determined based on the generator relative rotor angles obtained from time domain simulation outputs. Simulations were carried out on the IEEE 9-bus test system considering three phase faults on the system. The data collected from the time domain simulations are then used as inputs to the PNN in which PNN is used as a classifier to determine whether the power system is stable or unstable. Principle component analysis is applied to extract useful input features to the PNN so that training time of the PNN can be reduced. To verify the effectiveness of the proposed PNN method, it is compared with the multi layer perceptron neural network. Results show that the PNN gives faster and more accurate transient stability assessment compared to the multi layer perceptron neural network in terms of classification results.

arXiv (Cornell University), Jul 25, 2022

Frequency Containment Reserves might be insufficient to provide an appropriate response in the pr... more Frequency Containment Reserves might be insufficient to provide an appropriate response in the presence of large disturbances and low inertia scenarios. As a solution, this work assesses the supplementary droop frequency-based Emergency Power Control (EPC) from HVDC interconnections, applied in the detailed Nordic Power System model. EPC distribution and factors that determine the EPC performance of an HVDC link are the focus of interest. The main criteria are the maximum Instantaneous Frequency Deviation and used EPC power. The presented methodology is motivated based on the theoretical observation concerning linearized system representation. However, the assessed and proposed properties of interest, such as provided EPC active and reactive power, their ratio, and energy of total loads and losses in the system due to the EPC, concern highly nonlinear system behavior. Finally, based on the obtained study, remarks on the pragmatical importance of the EPC distribution to the frequency nadir limitation are provided.

This paper investigates Frequency Restoration Reserve (FRR) allocation and dimensioning approache... more This paper investigates Frequency Restoration Reserve (FRR) allocation and dimensioning approaches in a multi-area context, focusing on the Nordic Load-Frequency Control (LFC) block. We aim to (i) provide a framework for multi-area FRR dimensioning applicable to dynamic as well as static approaches, and (ii) enhance the understanding of how the available information impacts the need for FRR capacity. We model the optimal FRR dimensioning and allocation in the entire Nordic LFC block, considering sharing of FRR between areas. We describe how FRR can be dimensioned dynamically, analyse the benefits of moving from a static to a dynamic approach, and investigate the impact of when FRR is dimensioned in terms of the available information. The proposed FRR dimensioning procedure includes a new application of a methodology to simulate imbalance scenarios and a novel reformulation of a chance-constrained optimization problem. Case study results show that dynamic dimensioning of FRR leads to...

2020 17th International Conference on the European Energy Market (EEM), 2020

System operators have the option to trade balancing reserves among countries and operators. In or... more System operators have the option to trade balancing reserves among countries and operators. In order to trade balancing reserves with other system operators the markets should be harmonized. While the spot and intraday markets are already harmonized within the Nordics, the balancing markets still display differences. The differences can be subtle, yet they may play a significant role for the planning, operation, modelling and control of the power system. In this paper, we conduct a thorough literature review on Nordic balancing markets and summarize the market rules and requirements. This review can help operators and modellers to better represent the Nordic power system. Index Terms-electricity markets, balancing markets, frequency reserves, power system operation.

In this paper, strategies for a holistic integration of multiple HVDC links into existing power s... more In this paper, strategies for a holistic integration of multiple HVDC links into existing power systems are presented. High Voltage Direct Current (HVDC) links can support the operation of AC grids on different timescales. Contrary to AC transmission lines, the power flow on HVDC links can be freely controlled. Due to their ability of rapidly controlling the power transmitted, they can help to stabilize the dynamic system response of interconnected power systems, e.g. providing fast frequency response. Moreover, they can be an important tool in controlling and in optimizing the operation of interconnected power system. In this paper, different strategies are presented, then their benefits and potential challenges are discussed. Keywords— High Voltage Direct Current (HVDC), Emergency Power Control, Frequency Containment Reserves, Lowand Zero-inertia, Electricity market, Loss Factors, Frequency Reserve Sharing

2019 IEEE Power & Energy Society General Meeting (PESGM)

This paper examines how various integration aspects of full converter wind turbines, such as grid... more This paper examines how various integration aspects of full converter wind turbines, such as grid code design, control aspects, and placement of turbines, impact the long-term voltage stability of a power system. The simulations are conducted on a modified version of the Nordic32 test system. Different cases have been analyzed and show, for example, that if over-dimensioning of converters is implemented, it is mainly the converters' current capacity that should be increased since the voltage limitation of converters seldom is reached during voltage instability events. Furthermore, a restrictive reactive control scheme is tested, with the aim of minimizing the wear and maintenance of converter components. Although found to generally reduce the voltage stability, the proposed control scheme could be adopted during specific conditions where the local need of voltage support is low. The placement of larger wind farms was found to have the largest impact, both on long-term voltage stability of the system itself, and on the effect that the analyzed design and control aspects had on the system stability. Consequently, the placement of WFs is found be an important factor to consider when designing ancillary services and grid codes for wind power.

2019 IEEE Milan PowerTech

In this paper, a predictive method to detect voltage instability using an artificial neural netwo... more In this paper, a predictive method to detect voltage instability using an artificial neural network is presented. The proposed method allows transmission system operators to predict long-term voltage instability far before the system voltage stability has been degraded, allowing swift and cost-effective control actions. The predictor is tested and trained on the Nordic32 test system for a wide range of different contingencies. The predictor proves to be accurate in providing early warnings of impending voltage instability, allowing 96.3 % of all test cases being correctly classified only seconds after a contingency. The method is proposed to be used as an effective tool for supplementary voltage instability detection for transmission system operators.

2018 North American Power Symposium (NAPS), 2018

This paper reviews and evaluates the main types of voltage stability indicators (VSIs) based on l... more This paper reviews and evaluates the main types of voltage stability indicators (VSIs) based on local measurements and further provides a background to their development. Due to weaknesses during dynamic conditions, the bus VSIs based on Thévenin's equivalent impedance methods are in general found to be unsuitable for most corrective applications, but may instead be used to estimate local loadability margin to voltage instability. Line VSIs, although requiring some data communication, are in general found to be more robust and may in most cases be used both for predictive and corrective applications. Sensitivitybased VSIs are typically more accurate for detecting voltage instability, but are instead sensitive to measurement noise and are highly nonlinear when the system is close to a voltage collapse, consequently being unsuitable for estimating stability margins. The VSIs based on the local identification of voltage emergency situations (LIVES) concept can take into account the delayed effects from load tap changers, making them suitable for corrective applications and to use in local protection schemes.

2018 North American Power Symposium (NAPS), 2018

Frequency control is one of the main actions in power system operation, since large frequency dev... more Frequency control is one of the main actions in power system operation, since large frequency deviation from the nominal value can lead to automatic frequency protection triggering to avoid equipment damaging. The three main factors which affect the dynamical response of the frequency include the amount of power imbalance due to a disturbance, available reserves and total inertia of the system. Due to increased integration of renewable energy sources, the total inertia of the system decreases and makes the speed of the response more sensitive to power balance disturbances. This paper assesses the dynamical performance of generators involved in the Frequency Containment Reserves and correlates them with additional Emergency Power Control from High Voltage Direct Current (HVDC) interconnections. The currently used constant power ramp control and a new proposed frequency droop control of HVDC interconnections are investigated for different amounts of inertia in a test system representing the Nordic Power System. The performance of each HVDC control is evaluated with respect to the maximum Instantaneous Frequency Deviation and the amount of power required for provided frequency control actions.

ArXiv, 2020

In the Nordic region, many interconnectors are formed by HVDC links, as Scandinavia, Continental ... more In the Nordic region, many interconnectors are formed by HVDC links, as Scandinavia, Continental Europe and the Baltic region are non-synchronous AC systems. This paper presents two cost benefit analyses on the utilization of HVDC interconnectors in the Nordic countries: in the first we investigate the utilization of HVDC interconnectors for reserve procurement and, in the second, we assess the implementation of implicit grid losses on HVDC interconnectors in the day-ahead market. The first analysis is motivated by some real events in 2018 where the inertia of the Nordic system dropped below a critical level and the most critical generating unit, a nuclear power plant in Sweden, was redispatched to guarantee the security of the system. In our analysis, we investigate the cost savings of using HVDC lines for frequency support using the Emergency Power Control (EPC) functionality instead of redispatching. Our results confirm that the frequency of redispatching actions will increase in...

The Frequency Containment Reserve (FCR) is one of the balancing actions to keep the frequency wit... more The Frequency Containment Reserve (FCR) is one of the balancing actions to keep the frequency within acceptable limits. The objective of the FCR (also known as primary frequency control) is to stabilize the system frequency within a short time interval after a disturbance. Related to that, maximum steady-state frequency deviation and maximum Instantaneous Frequency Deviation (IFD) are defined. With higher integration of renewable energy sources, power systems will reduce its impact on pollution, but face much more often with low inertia scenarios. With low inertia values, the system decreases its inherent property to react to large power disturbances. In these cases, IFD is profoundly affected, and there is a need for fast and cost-effective solutions. High-Voltage Direct-Current (HVDC) links, with appropriate control strategies, could offer a solution to this problem. According to current system requirements, HVDC links must be capable of providing frequency support. Several studie...

2018 Power Systems Computation Conference (PSCC), 2018

In this paper, we propose a data-driven preventive security-constrained AC optimal power flow (SC... more In this paper, we propose a data-driven preventive security-constrained AC optimal power flow (SC-OPF), which ensures small-signal stability and N-1 security. Our approach can be used by both system and market operators for optimizing redispatch or AC based market-clearing auctions. We derive decision trees from large datasets of operating points, which capture all security requirements and allow to define tractable decision rules that are implemented in the SC-OPF using mixedinteger nonlinear programming (MINLP). We propose a secondorder cone relaxation for the non-convex MINLP, which allows us to translate the non-convex and possibly disjoint feasible space of secure system operation to a convex mixed-integer OPF formulation. Our case study shows that the proposed approach increases the feasible space represented in the SC-OPF compared to conventional methods, can identify the global optimum as opposed to tested MINLP solvers and significantly reduces computation time due to a decreased problem size.

arXiv (Cornell University), Jun 4, 2018

arXiv (Cornell University), Aug 15, 2019

This paper develops a new method for voltage instability prediction using a recurrent neural netw... more This paper develops a new method for voltage instability prediction using a recurrent neural network with long short-term memory. The method is aimed to be used as a supplementary warning system for system operators, capable of assessing whether the current state will cause voltage instability issues several minutes into the future. The proposed method use a long sequence-based network, where both real-time and historic data are used to enhance the classification accuracy. The network is trained and tested on the Nordic32 test system, where combinations of different operating conditions and contingency scenarios are generated using time-domain simulations. The method shows that almost all N-1 contingency test cases were predicted correctly, and N-1-1 contingency test cases were predicted with over 93 % accuracy only seconds after a disturbance. Further, the impact of sequence length is examined, showing that the proposed long sequenced-based method provides significantly better classification accuracy than both a feedforward neural network and a network using a shorter sequence.

In this paper we unify electricity market operations with power system security considerations. U... more In this paper we unify electricity market operations with power system security considerations. Using data-driven techniques, we address both small signal stability and steady-state security, derive tractable decision rules in the form of line flow limits, and incorporate the resulting constraints in market clearing algorithms. Our goal is to minimize redispatching actions, and instead allow the market to determine the most cost-efficient dispatch while considering all security constraints. To maintain tractability of our approach we perform our security assessment offline, examining large datasets, both from measurements and simulations, in order to determine stable and unstable operating regions. With the help of decision trees, we transform this information to linear decision rules for line flow constraints. We propose conditional line transfer limits, which can accurately capture security considerations, while being less conservative than current approaches. Our approach can be scalable for large systems, accounts explicitly for power system security, and enables the electricity market to identify a cost-efficient dispatch avoiding redispatching actions. We demonstrate the performance of our method in a case study.

IET smart grid, May 29, 2020

This study develops a machine learning-based method for a fast estimation of the dynamic voltage ... more This study develops a machine learning-based method for a fast estimation of the dynamic voltage security margin (DVSM). The DVSM can incorporate the dynamic system response following a disturbance and it generally provides a better measure of security than the more commonly used static voltage security margin (VSM). Using the concept of transient P-V curves, this study first establishes and visualises the circumstances when the DVSM is to prefer the static VSM. To overcome the computational difficulties in estimating the DVSM, this study proposes a method based on training two separate neural networks on a data set composed of combinations of different operating conditions and contingency scenarios generated using time-domain simulations. The trained neural networks are used to improve the search algorithm and significantly increase the computational efficiency in estimating the DVSM. The machine learning-based approach is thus applied to support the estimation of the DVSM, while the actual margin is validated using time-domain simulations. The proposed method was tested on the Nordic32 test system and the number of time-domain simulations was possible to reduce with ∼70%, allowing system operators to perform the estimations in near real-time.

arXiv (Cornell University), Jul 9, 2022

Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-... more Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-dimensional control problems. In this study, a real-time control system based on DRL is developed for long-term voltage stability events. The possibility of using system services from demand response (DR) and energy storage systems (ESS) as control measures to stabilize the system is investigated. The performance of the DRL control is evaluated on a modified Nordic32 test system. The results show that the DRL control quickly learns an effective control policy that can handle the uncertainty involved when using DR and ESS. The DRL control is compared to a rule-based load shedding scheme and the DRL control is shown to stabilize the system both significantly faster and with lesser load curtailment. Finally, when testing and evaluating the performance on load and disturbance scenarios that were not included in the training data, the robustness and generalization capability of the control were shown to be effective.

arXiv (Cornell University), Dec 1, 2020

The post-contingency loadability limit (PCLL) and the secure operating limit (SOL) are the two ma... more The post-contingency loadability limit (PCLL) and the secure operating limit (SOL) are the two main approaches used in computing the security margins of an electric power system. While the SOL is significantly more computationally demanding than the PCLL, it can account for the dynamic response after a disturbance and generally provides a better measure of the security margin. In this study, the difference between these two methods is compared and analyzed for a range of different contingency and load model scenarios. A methodology to allow a fair comparison between the two security margins is developed and tested on a modified version of the Nordic32 test system. The study shows that the SOL can differ significantly from the PCLL, especially when the system has a high penetration of loads with constant power characteristics, or a large share of induction motor loads with fast load restoration. The difference between the methods is also tested for different contingencies, where longer fault clearing times are shown to significantly increase the difference between the two margins.

IEEE Transactions on Power Systems, 2021

This paper develops a new method for voltage instability prediction using a recurrent neural netw... more This paper develops a new method for voltage instability prediction using a recurrent neural network with long short-term memory. The method is aimed to be used as a supplementary warning system for system operators, capable of assessing whether the current state will cause voltage instability issues several minutes into the future. The proposed method use a long sequence-based network, where both real-time and historic data are used to enhance the classification accuracy. The network is trained and tested on the Nordic32 test system, where combinations of different operating conditions and contingency scenarios are generated using time-domain simulations. The method shows that almost all N-1 contingency test cases were predicted correctly, and N-1-1 contingency test cases were predicted with over 93 % accuracy only seconds after a disturbance. Further, the impact of sequence length is examined, showing that the proposed long sequenced-based method provides significantly better classification accuracy than both a feedforward neural network and a network using a shorter sequence.

American Journal of Applied Sciences, 2008

This study presents transient stability assessment of electrical power system using Probabilistic... more This study presents transient stability assessment of electrical power system using Probabilistic Neural Network (PNN) and principle component analysis. Transient stability of a power system is first determined based on the generator relative rotor angles obtained from time domain simulation outputs. Simulations were carried out on the IEEE 9-bus test system considering three phase faults on the system. The data collected from the time domain simulations are then used as inputs to the PNN in which PNN is used as a classifier to determine whether the power system is stable or unstable. Principle component analysis is applied to extract useful input features to the PNN so that training time of the PNN can be reduced. To verify the effectiveness of the proposed PNN method, it is compared with the multi layer perceptron neural network. Results show that the PNN gives faster and more accurate transient stability assessment compared to the multi layer perceptron neural network in terms of classification results.

arXiv (Cornell University), Jul 25, 2022

Frequency Containment Reserves might be insufficient to provide an appropriate response in the pr... more Frequency Containment Reserves might be insufficient to provide an appropriate response in the presence of large disturbances and low inertia scenarios. As a solution, this work assesses the supplementary droop frequency-based Emergency Power Control (EPC) from HVDC interconnections, applied in the detailed Nordic Power System model. EPC distribution and factors that determine the EPC performance of an HVDC link are the focus of interest. The main criteria are the maximum Instantaneous Frequency Deviation and used EPC power. The presented methodology is motivated based on the theoretical observation concerning linearized system representation. However, the assessed and proposed properties of interest, such as provided EPC active and reactive power, their ratio, and energy of total loads and losses in the system due to the EPC, concern highly nonlinear system behavior. Finally, based on the obtained study, remarks on the pragmatical importance of the EPC distribution to the frequency nadir limitation are provided.

This paper investigates Frequency Restoration Reserve (FRR) allocation and dimensioning approache... more This paper investigates Frequency Restoration Reserve (FRR) allocation and dimensioning approaches in a multi-area context, focusing on the Nordic Load-Frequency Control (LFC) block. We aim to (i) provide a framework for multi-area FRR dimensioning applicable to dynamic as well as static approaches, and (ii) enhance the understanding of how the available information impacts the need for FRR capacity. We model the optimal FRR dimensioning and allocation in the entire Nordic LFC block, considering sharing of FRR between areas. We describe how FRR can be dimensioned dynamically, analyse the benefits of moving from a static to a dynamic approach, and investigate the impact of when FRR is dimensioned in terms of the available information. The proposed FRR dimensioning procedure includes a new application of a methodology to simulate imbalance scenarios and a novel reformulation of a chance-constrained optimization problem. Case study results show that dynamic dimensioning of FRR leads to...

2020 17th International Conference on the European Energy Market (EEM), 2020

System operators have the option to trade balancing reserves among countries and operators. In or... more System operators have the option to trade balancing reserves among countries and operators. In order to trade balancing reserves with other system operators the markets should be harmonized. While the spot and intraday markets are already harmonized within the Nordics, the balancing markets still display differences. The differences can be subtle, yet they may play a significant role for the planning, operation, modelling and control of the power system. In this paper, we conduct a thorough literature review on Nordic balancing markets and summarize the market rules and requirements. This review can help operators and modellers to better represent the Nordic power system. Index Terms-electricity markets, balancing markets, frequency reserves, power system operation.

In this paper, strategies for a holistic integration of multiple HVDC links into existing power s... more In this paper, strategies for a holistic integration of multiple HVDC links into existing power systems are presented. High Voltage Direct Current (HVDC) links can support the operation of AC grids on different timescales. Contrary to AC transmission lines, the power flow on HVDC links can be freely controlled. Due to their ability of rapidly controlling the power transmitted, they can help to stabilize the dynamic system response of interconnected power systems, e.g. providing fast frequency response. Moreover, they can be an important tool in controlling and in optimizing the operation of interconnected power system. In this paper, different strategies are presented, then their benefits and potential challenges are discussed. Keywords— High Voltage Direct Current (HVDC), Emergency Power Control, Frequency Containment Reserves, Lowand Zero-inertia, Electricity market, Loss Factors, Frequency Reserve Sharing

2019 IEEE Power & Energy Society General Meeting (PESGM)

This paper examines how various integration aspects of full converter wind turbines, such as grid... more This paper examines how various integration aspects of full converter wind turbines, such as grid code design, control aspects, and placement of turbines, impact the long-term voltage stability of a power system. The simulations are conducted on a modified version of the Nordic32 test system. Different cases have been analyzed and show, for example, that if over-dimensioning of converters is implemented, it is mainly the converters' current capacity that should be increased since the voltage limitation of converters seldom is reached during voltage instability events. Furthermore, a restrictive reactive control scheme is tested, with the aim of minimizing the wear and maintenance of converter components. Although found to generally reduce the voltage stability, the proposed control scheme could be adopted during specific conditions where the local need of voltage support is low. The placement of larger wind farms was found to have the largest impact, both on long-term voltage stability of the system itself, and on the effect that the analyzed design and control aspects had on the system stability. Consequently, the placement of WFs is found be an important factor to consider when designing ancillary services and grid codes for wind power.

2019 IEEE Milan PowerTech

In this paper, a predictive method to detect voltage instability using an artificial neural netwo... more In this paper, a predictive method to detect voltage instability using an artificial neural network is presented. The proposed method allows transmission system operators to predict long-term voltage instability far before the system voltage stability has been degraded, allowing swift and cost-effective control actions. The predictor is tested and trained on the Nordic32 test system for a wide range of different contingencies. The predictor proves to be accurate in providing early warnings of impending voltage instability, allowing 96.3 % of all test cases being correctly classified only seconds after a contingency. The method is proposed to be used as an effective tool for supplementary voltage instability detection for transmission system operators.

2018 North American Power Symposium (NAPS), 2018

This paper reviews and evaluates the main types of voltage stability indicators (VSIs) based on l... more This paper reviews and evaluates the main types of voltage stability indicators (VSIs) based on local measurements and further provides a background to their development. Due to weaknesses during dynamic conditions, the bus VSIs based on Thévenin's equivalent impedance methods are in general found to be unsuitable for most corrective applications, but may instead be used to estimate local loadability margin to voltage instability. Line VSIs, although requiring some data communication, are in general found to be more robust and may in most cases be used both for predictive and corrective applications. Sensitivitybased VSIs are typically more accurate for detecting voltage instability, but are instead sensitive to measurement noise and are highly nonlinear when the system is close to a voltage collapse, consequently being unsuitable for estimating stability margins. The VSIs based on the local identification of voltage emergency situations (LIVES) concept can take into account the delayed effects from load tap changers, making them suitable for corrective applications and to use in local protection schemes.

2018 North American Power Symposium (NAPS), 2018

Frequency control is one of the main actions in power system operation, since large frequency dev... more Frequency control is one of the main actions in power system operation, since large frequency deviation from the nominal value can lead to automatic frequency protection triggering to avoid equipment damaging. The three main factors which affect the dynamical response of the frequency include the amount of power imbalance due to a disturbance, available reserves and total inertia of the system. Due to increased integration of renewable energy sources, the total inertia of the system decreases and makes the speed of the response more sensitive to power balance disturbances. This paper assesses the dynamical performance of generators involved in the Frequency Containment Reserves and correlates them with additional Emergency Power Control from High Voltage Direct Current (HVDC) interconnections. The currently used constant power ramp control and a new proposed frequency droop control of HVDC interconnections are investigated for different amounts of inertia in a test system representing the Nordic Power System. The performance of each HVDC control is evaluated with respect to the maximum Instantaneous Frequency Deviation and the amount of power required for provided frequency control actions.

ArXiv, 2020

In the Nordic region, many interconnectors are formed by HVDC links, as Scandinavia, Continental ... more In the Nordic region, many interconnectors are formed by HVDC links, as Scandinavia, Continental Europe and the Baltic region are non-synchronous AC systems. This paper presents two cost benefit analyses on the utilization of HVDC interconnectors in the Nordic countries: in the first we investigate the utilization of HVDC interconnectors for reserve procurement and, in the second, we assess the implementation of implicit grid losses on HVDC interconnectors in the day-ahead market. The first analysis is motivated by some real events in 2018 where the inertia of the Nordic system dropped below a critical level and the most critical generating unit, a nuclear power plant in Sweden, was redispatched to guarantee the security of the system. In our analysis, we investigate the cost savings of using HVDC lines for frequency support using the Emergency Power Control (EPC) functionality instead of redispatching. Our results confirm that the frequency of redispatching actions will increase in...

The Frequency Containment Reserve (FCR) is one of the balancing actions to keep the frequency wit... more The Frequency Containment Reserve (FCR) is one of the balancing actions to keep the frequency within acceptable limits. The objective of the FCR (also known as primary frequency control) is to stabilize the system frequency within a short time interval after a disturbance. Related to that, maximum steady-state frequency deviation and maximum Instantaneous Frequency Deviation (IFD) are defined. With higher integration of renewable energy sources, power systems will reduce its impact on pollution, but face much more often with low inertia scenarios. With low inertia values, the system decreases its inherent property to react to large power disturbances. In these cases, IFD is profoundly affected, and there is a need for fast and cost-effective solutions. High-Voltage Direct-Current (HVDC) links, with appropriate control strategies, could offer a solution to this problem. According to current system requirements, HVDC links must be capable of providing frequency support. Several studie...

2018 Power Systems Computation Conference (PSCC), 2018

In this paper, we propose a data-driven preventive security-constrained AC optimal power flow (SC... more In this paper, we propose a data-driven preventive security-constrained AC optimal power flow (SC-OPF), which ensures small-signal stability and N-1 security. Our approach can be used by both system and market operators for optimizing redispatch or AC based market-clearing auctions. We derive decision trees from large datasets of operating points, which capture all security requirements and allow to define tractable decision rules that are implemented in the SC-OPF using mixedinteger nonlinear programming (MINLP). We propose a secondorder cone relaxation for the non-convex MINLP, which allows us to translate the non-convex and possibly disjoint feasible space of secure system operation to a convex mixed-integer OPF formulation. Our case study shows that the proposed approach increases the feasible space represented in the SC-OPF compared to conventional methods, can identify the global optimum as opposed to tested MINLP solvers and significantly reduces computation time due to a decreased problem size.