Geert Deconinck

KU Leuven | ku leuven · Department of Electrical Engineering (ESAT)

Power flow analysis plays a critical role in the control and operation of power systems. The high computational burden of traditional solution methods led to a shift towards data-driven approaches, exploiting the availability of digital metering data. However, data-driven approaches, such as deep learning, have not yet won the trust of operators as...

Background The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learning for control applications in LVAD remains minimally explored. This work introduces a preload‐based...

The framework of Koopman operator theory is discussed along with its connections to Dynamic Mode Decomposition (DMD) and (Kernel) Extended Dynamic Mode Decomposition (EDMD). This paper provides a succinct overview with consistent notation. The authors hope to provide an exposition that more naturally emphasizes the connections between theory and al...

Power flow analysis plays a critical role in the control and operation of power systems. The high computational burden of traditional solution methods led to a shift towards data-driven approaches, exploiting the availability of digital metering data. However, data-driven approaches, such as deep learning, have not yet won the trust of operators as...

In the realm of power systems, the increasing involvement of residential users in load forecasting applications has heightened concerns about data privacy. Specifically, the load data can inadvertently reveal the daily routines of residential users, thereby posing a risk to their property security. While federated learning (FL) has been employed to...

The examination of the maximum number of electric vehicles (EVs) that can be integrated into the distribution network (DN) without causing any operational incidents has become increasingly crucial as EV penetration rises. This issue can be addressed by utilizing dynamic operating envelopes (DOEs), which are generated based on the grid status. While...

The stability of modern power grids relies heavily on effective frequency control, mainly achieved through automatic generation control (AGC) systems. However, AGC systems have become increasingly vulnerable to cyber-physical attacks due to their dependence on communication infrastructure and cyber-physical devices. In this article, we present a no...

The delivery of flexibility from distributed assets guarantees the stable operation of the power system as increasing volumes of renewable energy are deployed. Nevertheless, verifying the adequate provision is challenging when considering behind‐the‐meter resources. A cost‐effective alternative to dedicated metring is using measurements from smart...

The role of phasor measurement unit (PMU) data as real-time indicators of system dynamics is critically important for accurate state estimation in power systems. PMUs, being cyber-physical devices, are susceptible to cyber-attacks, such as false data injection (FDI). As FDI can lead to incorrect state estimation and subsequent destructive impacts,...

Secure communication networks are crucial for the proper functioning of power grid infrastructure. Anomaly detection is essential for maintaining network security, but most existing methods rely on power system measurement anomalies that appear only after an attack has been effectively executed. Identifying attacks in their early stages, primarily...

This paper introduces the District Optimization Testing (DOPTEST) concept, which naturally extends from the Building Optimization Testing (BOPTEST) framework, for simulation-based testing of advanced control strategies in districts. While the focus of the BOPTEST framework is on individual building control, DOPTEST is meant to assess system integra...

Recent geopolitical developments have placed global decarbonization at the top of the global agenda. However, moving toward a low-carbon energy system is challenging. The exponential growth of renewable technologies introduces unprecedented uncertainty in the operators’ decision-making process, while the increasing electrification leads to drastic...

p>Unbalanced optimal power flow refers to mathematical optimization problems subject to the physics of grids with phase unbalance. They can serve as a core technology, or benchmark, for centralized or distributed optimal control solutions. In recent years, convex relaxations of this problem have attracted significant interest in the community. For...

In recent years, several applications have been proposed in the context of distribution networks. Many of these can be formulated as an optimal power flow problem, a mathematical optimization program which includes a model of the steady-state physics of the electricity network. If the network loading is balanced and the lines are transposed, the ne...

An effective tool used in practice to maintain network balance is residential demand side management (DMS). However, privacy concerns related to the processing of user personal consumption data often result in a slow wide-scale adoption and acceptance. Various general purpose cryptographic techniques are available, such as homomorphic encryption an...

Residential demand response programs aim to activate demand flexibility at the household level. In recent years, reinforcement learning (RL) has gained significant attention for these type of applications. A major challenge of RL algorithms is data efficiency. New RL algorithms, such as proximal policy optimisation (PPO), have tried to increase dat...

Despite the ample research on computing power grid flexibility envelopes, how to analytically monetize their points on a one-to-one (1-1) basis remains elusive, due to nonlinear grid constraints. Our methodology renders the 1-1 flexibility-to-cost mapping reachable, but in the context of grid-friendly smart sustainable buildings (GF-SSBs). We explo...

In recent years, several applications have been proposed in the context of distribution networks. Many of these can be formulated as an optimal power flow problem, a mathematical optimization program which includes a model of the steady-state physics of the electricity network. If the network loading is balanced and the lines are transposed, the ne...

Model predictive control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy systems remains at a minimum while fulfilling all system constraints. However, this method presumes an adequate model of the underlying system dynamics, which is prone to modelling errors and is not necessarily ad...

Most existing voltage optimization approaches of low voltage distribution networks (LVDNs) assume users follow the regulations unconditionally, which is not always true. To tackle this, we propose a real-time peer to peer flexibility trading scheme for LVDNs. Besides distributed optimization, our scheme offers a way to let users trade their flexibi...

A number of decarbonization scenarios for the energy sector are built on simultaneous electrification of energy demand, and decarbonization of electricity generation through renewable energy sources. However, increased electricity demand due to heat and transport electrification and the variability associated with renewables have the potential to d...

Following recent EU directives, the penetration of smart sustainable buildings (SSBs) in low voltage (LV) networks is expected to drastically increase. This open ups opportunities for developing novel frameworks to coordinate the provision of ancillary services (AS) stemming from SSBs. In pursuit of investigating the extent of the previously untapp...

Obtaining accurate models for heating and building systems is crucial for prediction and control in the context of energy effciency and demand response. Models should be both computationally and data-effcient, as well as easy to implement. This paper therefore introduces a methodology for data-driven modeling and control of residential heating syst...

This article introduces new roles in future peer-to-peer electricity trading markets. Following a qualitative approach, firstly, the value network of the current electricity market is presented. To do so, service streams, critical roles, activities, and their setting in the electricity market are identified. Secondly, in order to identify the main...

Mathematical models representing the behavior of electrical loads are an important part of any optimal power flow problem. The current state-of-the-art in unbalanced optimal power flow mostly considers wye-connected, constant power loads. However, for applications such as conservation voltage reduction, it is crucial to model how the consumption of...

In order to achieve a decarbonised energy system, change has to happen from electricity generation to the transmission grid over the distribution level all the way down to the industrial loads and the local households. To get involvement of communities in this energy transition, local participation is needed, so that the citizens can be aware of th...

Recently, multi-energy systems (MESs), whereby different energy carriers are coupled together, have become popular. For a more efficient use of MESs, the optimal operation of these systems needs to be considered. This paper focuses on the day-ahead optimal schedule of an MES, including a combined heat and electricity (CHP) unit, a gas boiler, a PV...

Power systems face more uncertainty by increasing photovoltaic system installations on the roof of buildings. To optimally manage energy and available flexibility in a building, stochastic optimization is used to take an optimal decision under uncertainty and minimize the operational cost. In stochastic optimization, a scenario set is used as an in...

Increased penetration of low‐carbon technologies, such as residential photovoltaic systems, electric vehicles, and batteries, can potentially cause voltage quality issues in distribution networks. Active distribution networks adopt control schemes where these assets are actively managed to prevent potential issues, increasing the network utilizatio...

Model-predictive-control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy systems remains at a minimum while fulfilling all system constraints. However, this method presumes an adequate model of the underlying system dynamics, which is prone to modelling errors and is not necessarily ad...

The main purpose of this Special Issue of IEEE Transactions on Systems, Man, And Cybernetics: Systems is to discuss recent advances for intelligence in power and energy systems. The IEEE Systems, Man, and Cybernetics (SMC) Society has a lot of activities that provide potential solutions for more intelligence in power and energy systems. This articl...

The concept of nearly zero energy (nZE) or sustainable buildings is prominently featured in the EU's energy strategy. However, transitioning to the envisioned era of ``smartness" and ``sustainability" involves overcoming several technoeconomic barriers: the difference in nature between different building archetypes, the simultaneous management of d...

Recent years have seen a significant increase in the adoption of electric vehicles, and investments in electric vehicle charging infrastructure and rooftop photo-voltaic installations. The ability to delay electric vehicle charging provides inherent flexibility that can be used to compensate for the intermittency of photo-voltaic generation and opt...

This paper develops a novel nonconvex formulation of the unbalanced power flow equations. This formulation extends the lifted nonconvex ‘DistFlow’ a.k.a. balanced branch flow model formulation to the unbalanced case. The feasible set is characterized by linear and nonconvex quadratic equations in matrix variables. It is shown that this formulation...

In low voltage (LV) networks, the majority of distributed energy resources (DER) are customer-owned. As such, it is harder for the distribution system operator (DSO) to control its system and maintaining acceptable operating conditions. Even if residential flexibility is available, it should be employed without significant disturbances to customer-...

This paper presents an extensive multi-period optimal power flow framework, with new modelling elements, for smart LV distribution systems that rely on residential flexibility for combating operational issues. A detailed performance assessment of different setups is performed, including: ZIP flexible loads (FLs), varying degrees of controllability...

Electricity generation is decentralising quickly. Simultaneously, final energy use for residential customers electrifies in order to reduce carbon dioxide emissions. Together with ubiquitous digitalisation, this decentralisation and flexibility at the demand side paves the way towards local energy communities and – in its most distributed version –...

Due to the rising renewable penetration rate, modern low voltage distribution network (LVDN) calls for active control with tractable computation and limited communication. To tackle this, the paper proposes a novel stochastic distributed optimization approach. The computation of optimum is completely decentralized, with a global broadcast signal is...

This study proposes a model for multi-phase, multi-winding, lossy transformers. A methodology is developed to decompose such transformers into a sub-network of multi-conductor Π-sections, shunts and idealised (lossless) two-winding transformers. The approach, therefore, can be used to include three-phase transformer models in any unbalanced power f...

A model-free distributed control scheme that implements active voltage control in low voltage distribution network (LVDN) is proposed. By solving an individual Hamilton-Jacobi-Bellman-Flemming function with public information, users can compute a good approximation to their optimal control trajectory and take uncertainties into account in a distrib...

Most distribution systems, which were designed years ago under different standards, are largely incapable of integrating (in an uncoordinated manner) high levels of residential distributed energy resources (DER), becoming burdened by operational voltage and thermal issues. Especially for low voltage (LV) distribution systems, proper controllability...

A R T I C L E I N F O Keywords: mixed-integer nonlinear programming multi-period optimal power flow residential flexibility shiftable loads smart buildings A B S T R A C T The presence of smart buildings (SBs) is expected to grow manifold in the next decade, leading to both challenges and opportunities in managing increasingly "active" distribution...

With the increasing development of grid-connected microgrids predominantly powered by renewable energy sources, their negative impact on the distribution grid cannot be ignored. Whilst this burden is borne by the distribution system operator (DSO), microgrid-users can contribute in grid congestion management to maintain a stable grid connection by...

This paper presents an extensive multi-period optimal power flow framework, with new modelling elements, for smart LV distribution systems that rely on residential flexibility for combating operational issues. A detailed performance assessment of different setups is performed, including: ZIP flexible loads (FLs), varying degrees of controllability...

Thermostatically Controlled Loads (TCLs) provide a source of demand flexibility, and are often considered a good source for Demand Response (DR) applications. Due to their heterogeneity, and as such a lack of dynamics models, Reinforcement Learning (RL) is often used to exploit this flexibility. Unfortunately, RL requires exploratory interaction wi...

Control of distribution networks are facing significant challenges with the increasing penetration of distributed energy resources. The focus of this thesis is to develop active voltage control systems provided by photovoltaic (PV) and PV-battery inverters to mitigate or eliminate voltage problems of distribution networks. Various approaches that c...

With the rise of distributed energy resources, photovoltaic-battery systems are needed to maintain voltages within limits, and balance between demand and supply. These systems can be exploited more by controlling them to provide multiple, stacked services. In this paper, we propose a novel control methodology for photovoltaic-battery systems to pro...

Various approaches that combine local, centralized and distributed voltage control techniques have been proposed in literature. These techniques suffer from different problems. Local voltage control systems suffer from degraded voltage regulation; centralized voltage control systems have poor reliability and scalability; distributed voltage control...