An improved decentralised coordinated control scheme for microgrids with AC-coupled units

Microgrids composed of solemnly AC-coupled distributed energy resources can be found in many real-life applications while their control has not been researched nearly enough to address some fundamental challenges, the most important of which is overall system reliability and fault tolerance. This paper proposes a droop-based coordinated control scheme for microgrids with AC-coupled units, a method that enables distributed energy resources units to hot swap between current source and voltage source grid-supporting control modes for satisfying load demand and ensuring energy storage systems will constantly be able to form the grid during islanded operation. The proposed control scheme has been realised in MATLAB/Simulink simulation model of a small-scale microgrid of AC-coupled units that corresponds to a real testbed in Northern Greece. Preliminary simulation results, in islanded mode, demonstrate the effectiveness of the proposed control scheme regarding power-sharing accuracy among the resources and state-of-charge balancing among storage units

Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration

In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes

Power Quality Improvement in Distribution Grids via Real-Time Smart Exploitation of Electric Vehicles

Integration of electric vehicles into electric power system brings both challenges and solutions in the operation of power grids. On the one hand, simultaneously charging a large number of electric vehicles causes branch congestion or large voltage drop. Operating the electric vehicles in the discharging mode, on the other hand, introduces the provision of several ancillary services like peak power shaving and spinning reserves. From the electric vehicles operation point of view, thus, the distribution system operators require a real-time monitoring infrastructure to capture the states of electric vehicle chargers and accordingly operate their grids in the safe mode with respect to the power quality standards (e.g., EN 50160). In this context, the real-time smart charging and storage platform of the EU Horizon 2020 “MEISTER” project, based on the information and communication technology, manages the availability of electric vehicles as a potential source of energy in the need of one or more flexibility services demanded by low voltage distribution system operators. In addition to the implemented information and communication technology platform, this paper presents how the smart use of the electric vehicle resources supports the power quality of the distribution system in terms of system voltage support, bidirectional power flow management, harmonic alleviation and power factor control

Benchmark Comparison of Analytical, Data-Based and Hybrid Models for Multi-Step Short-Term Photovoltaic Power Generation Forecasting

Accurately forecasting power generation in photovoltaic (PV) installations is a challenging task, due to the volatile and highly intermittent nature of solar-based renewable energy sources. In recent years, several PV power generation forecasting models have been proposed in the relevant literature. However, there is no consensus regarding which models perform better in which cases. Moreover, literature lacks of works presenting detailed experimental evaluations of different types of models on the same data and forecasting conditions. This paper attempts to fill in this gap by presenting a comprehensive benchmarking framework for several analytical, data-based and hybrid models for multi-step short-term PV power generation forecasting. All models were evaluated on the same real PV power generation data, gathered from the realisation of a small scale pilot site in Thessaloniki, Greece. The models predicted PV power generation on multiple horizons, namely for 15 min, 30 min, 60 min, 120 min and 180 min ahead of time. Based on the analysis of the experimental results we identify the cases, in which specific models (or types of models) perform better compared to others, and explain the rationale behind those model performances

Novel hybrid design For microgrid control

This paper proposes a new hybrid control system for an AC microgrid. The system uses both centralised and decentralised strategies to optimize the microgrid energy control while addressing the challenges introduced by current technologies and applied systems in real microgrid infrastructures. The well-known 3-level control (tertiary, secondary, primary) is employed with an enhanced hierarchical design using intelligent agent-based components in order to improve efficiency, diversity, modularity, and scalability. The main contribution of this paper is dual. During normal operation, the microgrid central controller (MGCC) is designed to undertake the management of the microgrid, while providing the local agents with the appropriate constraints for optimal power flow. During MGCC fault, a peer-to-peer communication is enabled between neighbouring agents in order to make their optimal decision locally. The initial design of the control structure and the detailed analysis of the different operating scenarios along with their requirements have shown the applicability of the new system in real microgrid environments

Hybrid multi-agent-based adaptive control scheme for AC microgrids with increased fault-tolerance needs

This paper presents a fault-tolerant secondary and adaptive primary microgrid control scheme using a hybrid multi-agent system (MAS), capable of operating either in a semi-centralised or distributed manner. The proposed scheme includes a droop-based primary level that considers the microgrid energy reserves in production and storage. The secondary level is responsible for: a) the microgrid units\u27 coordination, b) voltage and frequency restoration and c) calculation of the droop/ reversed-droop coefficients. The suggested architecture is arranged upon a group of dedicated asset agents that collect local measurements, take decisions independently and, collaborate in order to achieve more complex control objectives. Additionally, a supervising agent is added to fulfill secondary level objectives. The hybrid MAS can operate either with or without the supervising agent operational, manifesting fast redistribution of the supervising agent tasks. The proposed hybrid scheme is tested in simulation upon two separate physical microgrids using three scenarios. Additionally, a comparison with conventional control methodologies is performed in order to illustrate further the operation of a hybrid approach. Overall, results show that the proposed control framework exhibits unique characteristics regarding reconfigurability and fault-tolerance, while power quality and improved load sharing are ensured even in case of critical component failure