Grid integration of wave energy & generic modelling of ocean devices for power system studies

The work presented in this thesis covers four major topics of research related to the grid integration of wave energy. More specifically, the grid impact of a wave farm on the power quality of its local network is investigated. Two estimation methods were developed regarding the flicker level Pst generated by a wave farm in relation to its rated power as well as in relation to the impedance angle ψk of the node in the grid to which it is connected. The electrical design of a typical wave farm design is also studied in terms of minimum rating for three types of costly pieces of equipment, namely the VAr compensator, the submarine cables and the overhead line. The power losses dissipated within the farm's electrical network are also evaluated. The feasibility of transforming a test site into a commercial site of greater rated power is investigated from the perspective of power quality and of cables and overhead line thermal loading. Finally, the generic modelling of ocean devices, referring here to both wave and tidal current devices, is investigated

GRID INTEGRATION OF WAVE AND TIDAL ENERGY

International audienceWave and tidal energy provide a renewable source of electricity. However, their inherent fluctuations may have a negative impact on the power quality of a local electrical network. Grid operators assess this impact through the use of dynamic models of the generation units, which are inserted into the overall power system model. Providing these models is a compulsory step for any power generator to procure a grid connection above a specified power capacity. Significant issues were encountered in the wind energy industry regarding the dynamic modelling of devices, among which were model numerical instability, poor dynamic model quality and model incompatibility. Considering the large diversity of device types in the emerging ocean energy industry, these problems are considered as a major barrier to the larger scale grid-integration of marine energy converters. Dynamic models must clearly demonstrate the compliance of the actual power generation device and array of devices to the grid code requirements for grid-connection to be allowed. A further barrier to grid connection of ocean energy devices is that existing grid codes – mainly written in the context of wind energy-may be irrelevant or inadequate for ocean energy devices. This paper presents an overview of these issues, and details a radically different approach to the dynamic modelling of ocean energy devices that will assist in overcoming the issues previously encountered in the development of wind turbine models. It also highlights the gaps and inadequacy regarding grid code requirements for ocean energy devices, and provides some recommendations for a new ocean energy grid code

GRID IMPACT OF A WAVE FARM ON ITS LOCAL NETWORK: ANALYSIS OF VOLTAGE AND FLICKER LEVELS

International audienceMost oscillating wave energy converters without significant amounts of energy storage capacity generate significant electrical power fluctuations in the range of seconds. Because of these fluctuations, a wave farm may have a negative impact on the power quality of the local grid to which it is connected. Hence, the impact of these devices on both distribution and transmission networks needs to be well understood, before large scale wave farms can be allowed to connect to the grid. This paper details a case study on the impact of a wave farm on the distribution grid around the national wave test site of Ireland. The electrical power output of the oscillating water column (OWC) wave energy converters was derived from experimental time series produced in the context of the FP7 project " CORES ". The results presented in this paper consider voltage fluctuation levels and flicker levels for a typical time series. Simulations were performed using DIgSILENT simulation tool " PowerFactory "

Decentralized Smart Charging of Large-Scale EVs using Adaptive Multi-Agent Multi-Armed Bandits

The drastic growth of electric vehicles and photovoltaics can introduce new challenges, such as electrical current congestion and voltage limit violations due to peak load demands. These issues can be mitigated by controlling the operation of electric vehicles i.e., smart charging. Centralized smart charging solutions have already been proposed in the literature. But such solutions may lack scalability and suffer from inherent drawbacks of centralization, such as a single point of failure, and data privacy concerns. Decentralization can help tackle these challenges. In this paper, a fully decentralized smart charging system is proposed using the philosophy of adaptive multi-agent systems. The proposed system utilizes multi-armed bandit learning to handle uncertainties in the system. The presented system is decentralized, scalable, real-time, model-free, and takes fairness among different players into account. A detailed case study is also presented for performance evaluation.Comment: CIRED 2023 International Conference & Exhibition on Electricity Distribution, Jun 2023, Rome, Ital

Towards the optimal use of an existing MRE electrical network from an electrothermal perspective

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Estimation method for evaluating the wave-induced flicker level emitted by a tidal energy farm

International audienceThe inherently fluctuating nature of sea waves can be reflected to a significant extent in the power output of tidal turbines. However, these fluctuations can give rise to power quality issues such as flicker. Hence, it is important to assess the impact which tidal farms may have on their local network before such power plants are allowed to connect to the grid. This paper analyses under which sea-state and grid conditions a 30 MW rated tidal farm breaches the grid code requirements in terms of short-term flicker level. Then, it describes a simplified method for estimating the flicker level by means of an equivalent sinusoidally-modulated voltage profile

Wave-induced flicker level emitted by a tidal farm

International audienceThe inherently fluctuating nature of sea waves can be reflected to a significant extent in the power output of tidal turbines. However, these fluctuations can give rise to power quality issues such as flicker. Hence, it is important to assess the impact which tidal farms may have on their local network before such power plants are allowed to connect to the grid. This paper describes the influence of the wave climate on the short-term flicker level induced by a tidal farm on the point of common coupling. It analyses also under which conditions the tidal farm breaches the grid code requirements in terms of short-term flicker level

Renewable Energy in Data Centers: the Dilemma of Electrical Grid Dependency and Autonomy Costs

International audienceIntegrating larger shares of renewables in data centers' electrical mix is mandatory to reduce their carbon footprint. However, as they are intermittent and fluctuating, renewable energies alone cannot provide a 24/7 supply and should be combined with a secondary source. Finding the optimal infrastructure configuration for both renewable production and financial costs remains difficult. In this paper, we examine three scenarios with on-site renewable energy sources combined respectively with the electrical grid, batteries alone and batteries with hydrogen storage systems. The objectives are first, to size optimally the electric infrastructure using combinations of standard microgrids approaches, secondly to quantify the level of grid utilization when data centers consume/ export electricity from/to the grid, to determine the level of effort required from the grid operator, and finally to analyze the cost of 100% autonomy provided by the battery-based configurations and to discuss their economical viability. Our results show that in the grid-dependent mode, 63.1% of the generated electricity has to be injected into the grid and retrieved later. In the autonomous configurations, the cheapest one including hydrogen storage leads to a unit cost significantly more expensive than the electricity supplied from a national power system in many countries

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

International audienceEdge Computing has emerged from the Cloud to tackle the increasingly stringent latency, reliability and scalability imperatives of modern applications, mainly in the Internet of Things arena. To this end, the data centers are pushed to the edge of the network to diversify and bring the services closer to the users. This spatial distribution offer a wide range of opportunities for allowing self-consumption from local renewable energy sources with regard to the local weather conditions. However, scheduling the users' tasks so as to meet the service restrictions while consuming the most renewable energy and reducing the carbon footprint remains a challenge. In this paper, we design a nationwide Edge infrastructure, and study its behavior under three typical electrical configurations including solar power plant, batteries and the grid. Then, we study a set of techniques that collaboratively allocates resources on the edge data centers to harvest renewable energy and reduce the environmental impact. These strategies also includes energy efficiency optimization by means of reasonable quality of service degradation and consolidation techniques at each data center in order to reduce the need for brown energy. The simulation results show that combining these techniques allows to increase the self-consumption of the platform by 7.83% and to reduce the carbon footprint by 35.7% compared to the baseline algorithm. The optimizations also outperform classical energy-aware resource management algorithms from the literature. Yet, these techniques do not equally contribute to these performances, consolidation being the most efficient

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

Outstanding Paper AwardInternational audienceEdge Computing has emerged from the Cloud to tackle the increasingly stringent latency, reliability and scalability imperatives of modern applications, mainly in the Internet of Things arena. To this end, the data centers are pushed to the edge of the network to diversify and bring the services closer to the users. This spatial distribution offer a wide range of opportunities for allowing self-consumption from local renewable energy sources with regard to the local weather conditions. However, scheduling the users' tasks so as to meet the service restrictions while consuming the most renewable energy and reducing the carbon footprint remains a challenge. In this paper, we design a nationwide Edge infrastructure, and study its behavior under three typical electrical configurations including solar power plant, batteries and the grid. Then, we study a set of techniques that collaboratively allocates resources on the edge data centers to harvest renewable energy and reduce the environmental impact. These strategies also includes energy efficiency optimization by means of reasonable quality of service degradation and consolidation techniques at each data center in order to reduce the need for brown energy. The simulation results show that combining these techniques allows to increase the self-consumption of the platform by 7.83% and to reduce the carbon footprint by 35.7% compared to the baseline algorithm. The optimizations also outperform classical energy-aware resource management algorithms from the literature. Yet, these techniques do not equally contribute to these performances, consolidation being the most efficient