About
268
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Introduction
Kodjo Agbossou (M'1998, SM’2001) received his B.S. (1987), M.S. (1989) and Ph.D. (1992) degrees in Electronic Measurements from the Université de Nancy I, France.
He is now a Head of Engineering School of Université du Québec à Trois-Rivières (UQTR). and Full Professor in the Electrical and Computer Engineering Department of UQTR.
His present research activities are in the area of renewable energy, smart grid, integration of hydrogen production, and electrical vehicle connexion to the grid.
Publications
Publications (268)
Demand response (DR) plays an essential role in power system management. To facilitate the implementation of these techniques, many aggregators have appeared in response as new mediating entities in the electricity market. These actors exploit the technologies to engage customers in DR programs, offering grid services like load scheduling. However,...
Smart thermostats have become a promising device to control electric baseboard heaters' energy consumption while considering their flexibility in the demand response (DR) context. This article applies a shrinked-space search method to identify the tuning parameters of line voltage communicating thermostats (LVCTs). The proposed approach based on Ba...
Industrial Self-Guided Vehicles (SGVs), a type of Autonomous Mobile Robots (AMRs) used for material handling tasks, have recently attracted increased attention. As logistics scenarios grow more complex, effectively using state-of-the-art navigation algorithms becomes more challenging but essential for enhancing industrial operational efficiency. In...
Research on autonomous vehicles has been at a peak recently. One of the most researched aspects is the performance degradation of sensors in harsh weather conditions such as rain, snow, fog, and hail. This work addresses this performance degradation by fusing multiple sensor modalities inside the neural network used for detection. The proposed fusi...
The residential sectorʼs substantial electricity consumption, driven by heating demands during winter, necessitates optimal energy consumption strategies in the era of decarbonization. To address this challenge, this paper introduces a synthetic dataset specifically tailored to simulate energy consumption in residential apartment buildings. Focusin...
This paper presents a Reinforcement Learning (RL) approach to a price-based Demand Response (DR) program. The proposed framework manages a dynamic pricing scheme considering constraints from the supply and market side. Under these constraints, a DR Aggregator (DRA) is designed that takes advantage of a price generator function to establish a desira...
In flexibility markets, aggregators serve as crucial intermediaries by consolidating and selling consumer flexibility to grid operators or distribution system operators (DSOs). They are essential for grid management, offering load reductions based on power limits, and estimating expected consumer load in demand response scenarios. However, the inhe...
The digital asset industry, including generative artificial intelligence, Bitcoin mining, and high-performance computing, is known for its significant energy consumption and heat generation. This study quantitatively assesses the heat energy potential in digital asset mining, specifically focusing on two commonly used cryptocurrency machines: AntMi...
Electrification of space heating can help reduce greenhouse gas emissions, especially when coupled with advanced control strategies and leveraging building energy flexibility. A methodology to automatically generate accurate control-oriented building models is an important part of quantifying the energy flexibility of a house. This study presents a...
This paper examines the impact of building zoning on demand flexibility potentials. The building thermal dynamic response is modeled by using the state-space representation method. The comfort preference of the occupants is defined by statistical analysis of set-point temperature patterns. The created models are used to study energy flexibility thr...
For many years, energy monitoring at the most disaggregate level has been mainly sought through the idea of Non-Intrusive Load Monitoring (NILM). Developing a practical application of this concept in the residential sector can be impeded by the technical characteristics of case studies. Accordingly, several databases, mainly from Europe and the US,...
For many years, energy monitoring at the most disaggregate level has been mainly sought through the idea of Non-Intrusive Load Monitoring (NILM). Nevertheless, a practical application of this concept in the residential sector should address the underlying concerns raised by the technical specifications of case studies. From one side, such an operat...
The massive penetration of active customers throughout Home Energy Management Systems (HEMS) may cause adverse effects on the power grid, including rebound peaks, instabilities, and power congestion. The concept of coordination has arisen in literature to mitigate these effects and relieve power grid stress. Their advantages have been discussed for...
For a sustainable operation of multiple Self-Guided Vehicles (SGVs) in a dynamic manufacturing environment, it is essential to guarantee collision-free and efficient navigation to the autonomous mobile platforms and safety to the surrounding subjects. To prevent from navigation failures, an SGV must avoid conflicts that constrain itself to abruptly...
Demand response and distributed energy storage play a crucial role in improving the efficiency and reliability of electric grids. This paper describes a strategy for optimally integrating distributed energy storage units within a forward market to address space heating demand under a Stackelberg game in isolated microgrids. The proposed strategy pe...
The effectiveness of regenerative braking strategies plays an important role in extending the driving range of electric vehicles. Since the driver is still an essential factor in levels 3 and 4 of intelligent electric vehicles, improving user acceptance and adoption of the braking control strategy is crucial. This paper puts forward a new regenerat...
New grid management schemes have created exciting opportunities for end customers to maximize their utility by becoming active participants. In particular, Transactive Energy Systems (TES) allow customers to cooperate and negotiate in energy markets, increasing social welfare. These interactions also reduce demand-side uncertainties and simplify gr...
The Non-Intrusive Load Monitoring (NILM) concept is suggested as a practical means for energy monitoring at the most disaggregated level. Notwithstanding, a viable solution to this idea for residential applications should overcome its common and specific issues raised by technical specifications of the case study. Knowing the fact that the former h...
Distributed generation and energy storage technologies have helped SmartGrid projects gain great momentum over the last decade. However, despite a large number of pilot and demonstration projects, low-level information is often unavailable. Therefore, tools for defining and building different operation scenarios are required. These tools can facili...
As an essential feature of autonomous road vehicles, obstacle detection must be executed on a real‐time onboard platform with high accuracy. Cameras are still the most commonly used sensors in autonomous driving. Most detections using cameras are based on convolutional neural networks. In this regard, a recent teacher–student approach, called trans...
Electrification of space heating can help reduce greenhouse gas emissions, especially when coupled with advanced control strategies and leveraging building energy flexibility. A methodology to automatically generate accurate control-oriented building models is an important part of quantifying the energy flexibility of a house. This study presents a...
This paper examines the impact of building zoning on demand flexibility potentials. The building thermal dynamic response is modeled by using the state-space representation method. The comfort preference of the occupants is defined by statistical analysis of set-point temperature patterns. The created models are used to study energy flexibility thr...
Demand Response (DR) programs show great promise for energy saving and load profile flattening. They bring about an opportunity for indirect control of end-users’ demand based on different price policies. However, the difficulty in characterizing the price-responsive behavior of customers is a significant challenge towards an optimal selection of t...
The increase of Plug-in Electric Vehicles (PEVs) penetration in distribution systems necessitates processing strategic assets in order to deal with their energy needs. A careful investigation into matters related to PEV charging management under actual circumstances can be regarded as the critical step towards enabling this process. Accordingly, th...
Flexibility from demand-side resources is increasingly required in modern power systems to maintain the dynamic balance between demand and supply. This flexibility comes from elastic users managing controllable loads. In this context, controlling Electric Space Heaters (ESHs) is of particular interest because it can leverage building inner thermal...
Order picker routing refers to the process of collecting a set of products with the minimum travel time. Recently, a new generation of Automated Guided Vehicles (AGVs) has been developed to assist human order pickers in order to minimize their travel time. These vehicles are using battery as energy source. However, the routing energy efficiency asp...
Spot markets provide an interesting opportunity for profit maximization by energy trading based on immediate decisions on participant bids. However, their short market-clearing time can affect computational efficiency, search space, and reliability of price-energy allocation to bidding participants. Accordingly, developing a prompt and effective de...
End-users’ electricity consumption is highly affected by weather conditions. The uncertain nature of these circumstances can highly challenge energy supply and demand balancing. The identification of explanatory variables that influence energy usage plays a key role in addressing this issue. This paper conducts a benchmark study of several machine...
Load forecasting is an expected ability of electric power networks to enable effective capacity planning. This paper proposes a probabilistic approach to short-term load forecasting (STLF) of residential power consumption. The proposed method is based on Bayesian regression modeling. It utilizes an additive Gaussian Process (GP) to estimate climate...
Transactive Energy (TE) has brought exciting opportunities for all stakeholders in energy markets by enabling management decentralization. This new paradigm empowers demand-side agents to play a more active role through coordinating, cooperating, and negotiating with other agents. Nevertheless, most of these agents are not used to process market si...
Due to the impact of human lifestyle on building energy consumption, the development of occupants’ behavior models is crucial for energy-saving purposes. In this regard, occupancy modeling is an effective approach to intend such a purpose. However, the literature reveals that existing occupancy models have limitations related to the representation...
High penetration of selfish Home Energy Management Systems (HEMSs) causes adverse effects such as rebound peaks, instabilities, and contingencies in different regions of distribution grid. To avoid these effects and relieve power grid stress, the concept of HEMSs coordination has been suggested. Particularly, this concept can be employed to fulfill...
This paper presents a direct power control (DPC) technique based on instantaneous power theory with optimised PI controllers using a grey wolf optimiser (GWO) algorithm. The method allows to control active and reactive power and to improve the generated power quality. Double second-order generalised integrator with frequency-locked loop (DSOGI-FLL)...
Human preferences and lifestyles significantly impact buildings’ energy consumption. Consequently, a better understanding of occupants’ behavior is crucial to decrease energy consumption and maintain occupants’ comfort. Occupant-centric control (OCC) strategies are effective approaches to fulfil such a purpose. As such, occupancy detection and pred...
Home Energy Management systems are in a rapid development curve, supported by the advancements in computational intelligence, smart appliances, and new smart-grid frameworks. These systems are a fundamental part to implement demand-side management strategies and to shift local energy demand to periods of lower consumption effectively. In this paper...
Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a su...
Automated industrial vehicles are taking an imposing place by transforming the industrial operations, and contributing to an efficient in-house transportation of goods. They are expected to bring a variety of benefits towards the Industry 4.0 transition. However, Self-Guided Vehicles (SGVs) are battery-powered, unmanned autonomous vehicles. While t...
Detailed occupancy information in buildings is useful to improve the performance of energy management systems in order to enable energy consumption savings and maintain occupants' comfort. Different technologies employed to provide occupancy information account for high-precision devices such as optical and thermal cameras, and environmental or spe...
The widespread presence of plug-in Electric Vehicles (PEVs) in distribution power grids brings significant concerns regarding their energy demand and peak power requirements. In order to reduce the PEV load impact on power distribution networks, different strategies have been proposed based on the electricity price. This paper proposes a PEV chargi...
An efficient participation of prosumers in power system management depends on the quality of information they can obtain. Prosumers actions can be performed by automated agents that are operating in time-changing environments. Therefore, it is essential for them to deal with data stream problems in order to make reliable decisions based on the most...
Anomaly detection is a significant application of residential appliances load monitoring systems. As an essential prerequisite of load diagnosis services, anomaly detection is critical to energy saving and occupant comfort actualization. Notwithstanding, the investigation into diagnosis of household anomalous appliances has not been decently taken...
In the demand-side management (DSM) context, some appliances are remotely controlled by the utility or by end-users based on the expected aggregated consumption profile or day-ahead electricity rates. The main objective of these actions is to shift the load from critical to off-peak periods. This article proposes a novel approach to estimate in rea...
The world’s energy needs are constantly rising, this growing progression and the problem of greenhouse gas emissions require a massive integration of clean energy sources. Evidently, this integration passes through a power and energy conversion process, which is obtained by a power conditioning system (PCS) and permits to adapt the characteristics...
Enabling diagnosis capabilities of Appliance Load Monitoring (ALM) necessitates providing in-operation information of appliances’ behavior. Due to both appliances’ time-varying model parameters and operations, household aggregated consumption has a dynamic structure. Existing time-invariant load models, built of off-line datasets with static inform...