Johann Hurink | University of Twente (original) (raw)

Papers by Johann Hurink

Sustainable Energy, Grids and Networks, 2021

Due to the increasing penetration of electric vehicles (EVs) in the distribution grid, coordinate... more Due to the increasing penetration of electric vehicles (EVs) in the distribution grid, coordinated control of their charging is required to maintain a proper grid operation. Many EV charging strategies assume that the EV can charge at any rate up to a maximum value. Furthermore, many strategies use detailed predictions of uncertain data such as uncontrollable loads as input. However, in practice, charging can often be done only at a few discrete charging rates and obtaining detailed predictions of the uncertain data is difficult. Therefore, this paper presents an online EV scheduling approach based on discrete charging rates that does not require detailed predictions of this uncertain data. Instead, the approach requires only a prediction of a single value that characterizes an optimal offline EV schedule. Simulation results show that this approach is robust against prediction errors in this characterizing value and that this value can be easily predicted. Moreover, the results indicate that incorporating practical limitations such as discrete charging rates and uncertainty in uncontrollable loads can be done in an efficient and effective way.

CIRED - Open Access Proceedings Journal, 2017

The SmartOperator project of RWE Deutschland AG combines multiple techniques to address power qua... more The SmartOperator project of RWE Deutschland AG combines multiple techniques to address power quality issues within the distribution grid: storage, tap changers and demand side management (DSM). This study focuses on the domestic DSM aspects of the project, which controls appliances such as batteries, white goods and electric vehicles within houses. The DSM methodology operates in three steps: prediction, planning and online control. The main lessons learned during the course of the project are presented in this study.

OR Spectrum, 2017

Changes in our electricity supply chain are causing a paradigm shift from centralized control tow... more Changes in our electricity supply chain are causing a paradigm shift from centralized control towards decentralized energy management. Within the framework of decentralized energy management, devices that offer flexibility in their load profile play an important role. These devices schedule their flexible load profile based on steering signals received from centralized controllers. The problem of finding optimal device schedules based on the received steering signals falls into the framework of resource allocation problems. We study an extension of the traditional problems studied within resource allocation and prove that a divide-and-conquer strategy gives an optimal solution for the considered extension. This leads to an efficient recursive algorithm, with quadratic complexity in the practically relevant case of quadratic objective functions. Furthermore, we study discrete variants of two problems common in decentralized energy management. We show that these problems are NP-hard and formulate natural relaxations of both considered discrete problems that we solve efficiently. Finally, we show that the solutions to the natural relaxations closely resemble solutions to the original, hard problems. This research is conducted within the EASI project (12700) supported by STW and Alliander and the EU FP7 project e-balance (609132).

Energies, 2016

Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly... more Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capable of peak-shaving at the transformer level, while keeping the voltages well within legal bounds, keeping the cable load low and obtaining low losses. Further advantages of the methodology are a low communication overhead, low computational requirements and ease of implementation.

A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a po... more A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a polynomial-time approximation scheme for the maximum weight independent set problem in unit disk graphs. In contrast to previously known approximation schemes, our approach does not require a geometric representation (specifying the coordinates of the disk centers). The approximation algorithm presented is robust in the sense that it accepts any graph as input and either returns a (1+)-approximate independent set or a certificate showing that the input graph is no unit disk graph. The algorithm can easily be extended to other families of intersection graphs of geometric objects.

We discuss the self-rostering problem, a concept receiving more and more attention from both theo... more We discuss the self-rostering problem, a concept receiving more and more attention from both theory and practice. We outline our methodology and discuss its application to a number of practical case studies.

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Mathematical Methods of Operations Research, 2002

This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospi... more This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time consuming, tedious and complex task. The stochasticity of the durations of surgical procedures complicates the construction of operating room schedules. In addition, unbalanced scheduling of the operating room department often causes demand fluctuation in other departments such as surgical wards and intensive care units. We propose cyclic operating room schedules, so-called Master Surgical Schedules (MSSs) to deal with this problem. In an MSS, frequently performed elective surgical procedure types are planned in a cyclic manner. To deal with the uncertain duration of procedures we use planned slack. The problem of constructing MSSs is modeled as a Mathematical Program containing probabilistic constraints. Since the resulting Mathematical Program is computationally intractable we propose a column generation approach that maximizes the operation room utilization and levels the requirements for subsequent hospital beds such as wards and intensive care units in two subsequent phases. We tested the solution approach with data from the Erasmus Medical Center. Computational experiments show that the proposed solution approach works well for both the OR utilization and the leveling of requirements of subsequent hospital beds.

A polynomial algorithm is proposed for two scheduling problems for which the complexity status wa... more A polynomial algorithm is proposed for two scheduling problems for which the complexity status was open. A set of jobs with unit processing times, release dates and outtree precedence relations has to be processed on parallel identical machines such that the total completion time C j is minimized. It is shown that the problem can be solved in O(n 2) time if no preemption is allowed. Furthermore, it is proved that allowing preemption does not reduce the optimal objective value, which verifies a conjecture of Baptiste and Timkovsky.

Sustainable Energy, Grids and Networks, 2021

Due to the increasing penetration of electric vehicles (EVs) in the distribution grid, coordinate... more Due to the increasing penetration of electric vehicles (EVs) in the distribution grid, coordinated control of their charging is required to maintain a proper grid operation. Many EV charging strategies assume that the EV can charge at any rate up to a maximum value. Furthermore, many strategies use detailed predictions of uncertain data such as uncontrollable loads as input. However, in practice, charging can often be done only at a few discrete charging rates and obtaining detailed predictions of the uncertain data is difficult. Therefore, this paper presents an online EV scheduling approach based on discrete charging rates that does not require detailed predictions of this uncertain data. Instead, the approach requires only a prediction of a single value that characterizes an optimal offline EV schedule. Simulation results show that this approach is robust against prediction errors in this characterizing value and that this value can be easily predicted. Moreover, the results indicate that incorporating practical limitations such as discrete charging rates and uncertainty in uncontrollable loads can be done in an efficient and effective way.

CIRED - Open Access Proceedings Journal, 2017

The SmartOperator project of RWE Deutschland AG combines multiple techniques to address power qua... more The SmartOperator project of RWE Deutschland AG combines multiple techniques to address power quality issues within the distribution grid: storage, tap changers and demand side management (DSM). This study focuses on the domestic DSM aspects of the project, which controls appliances such as batteries, white goods and electric vehicles within houses. The DSM methodology operates in three steps: prediction, planning and online control. The main lessons learned during the course of the project are presented in this study.

OR Spectrum, 2017

Changes in our electricity supply chain are causing a paradigm shift from centralized control tow... more Changes in our electricity supply chain are causing a paradigm shift from centralized control towards decentralized energy management. Within the framework of decentralized energy management, devices that offer flexibility in their load profile play an important role. These devices schedule their flexible load profile based on steering signals received from centralized controllers. The problem of finding optimal device schedules based on the received steering signals falls into the framework of resource allocation problems. We study an extension of the traditional problems studied within resource allocation and prove that a divide-and-conquer strategy gives an optimal solution for the considered extension. This leads to an efficient recursive algorithm, with quadratic complexity in the practically relevant case of quadratic objective functions. Furthermore, we study discrete variants of two problems common in decentralized energy management. We show that these problems are NP-hard and formulate natural relaxations of both considered discrete problems that we solve efficiently. Finally, we show that the solutions to the natural relaxations closely resemble solutions to the original, hard problems. This research is conducted within the EASI project (12700) supported by STW and Alliander and the EU FP7 project e-balance (609132).

Energies, 2016

Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly... more Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capable of peak-shaving at the transformer level, while keeping the voltages well within legal bounds, keeping the cable load low and obtaining low losses. Further advantages of the methodology are a low communication overhead, low computational requirements and ease of implementation.

A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a po... more A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a polynomial-time approximation scheme for the maximum weight independent set problem in unit disk graphs. In contrast to previously known approximation schemes, our approach does not require a geometric representation (specifying the coordinates of the disk centers). The approximation algorithm presented is robust in the sense that it accepts any graph as input and either returns a (1+)-approximate independent set or a certificate showing that the input graph is no unit disk graph. The algorithm can easily be extended to other families of intersection graphs of geometric objects.

We discuss the self-rostering problem, a concept receiving more and more attention from both theo... more We discuss the self-rostering problem, a concept receiving more and more attention from both theory and practice. We outline our methodology and discuss its application to a number of practical case studies.

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Mathematical Methods of Operations Research, 2002

This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospi... more This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time consuming, tedious and complex task. The stochasticity of the durations of surgical procedures complicates the construction of operating room schedules. In addition, unbalanced scheduling of the operating room department often causes demand fluctuation in other departments such as surgical wards and intensive care units. We propose cyclic operating room schedules, so-called Master Surgical Schedules (MSSs) to deal with this problem. In an MSS, frequently performed elective surgical procedure types are planned in a cyclic manner. To deal with the uncertain duration of procedures we use planned slack. The problem of constructing MSSs is modeled as a Mathematical Program containing probabilistic constraints. Since the resulting Mathematical Program is computationally intractable we propose a column generation approach that maximizes the operation room utilization and levels the requirements for subsequent hospital beds such as wards and intensive care units in two subsequent phases. We tested the solution approach with data from the Erasmus Medical Center. Computational experiments show that the proposed solution approach works well for both the OR utilization and the leveling of requirements of subsequent hospital beds.

A polynomial algorithm is proposed for two scheduling problems for which the complexity status wa... more A polynomial algorithm is proposed for two scheduling problems for which the complexity status was open. A set of jobs with unit processing times, release dates and outtree precedence relations has to be processed on parallel identical machines such that the total completion time C j is minimized. It is shown that the problem can be solved in O(n 2) time if no preemption is allowed. Furthermore, it is proved that allowing preemption does not reduce the optimal objective value, which verifies a conjecture of Baptiste and Timkovsky.