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Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

State of the Art in Research on Microgrids: A Review

This paper proposes a novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system. The distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize the operation costs. It is assumed that both the dispatchable and nondispatchable distributed generators (DGs) exist in the networked MGs. In order to achieve the equilibrium among all entities and take into account the uncertainties of DG outputs, we formulate the problem as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level. Each level consists of two stages. The first stage is to determine base generation setpoints based on the load and nondispatchable DG output forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. A scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Case studies of a distribution system with multiple MGs of different types demonstrate the effectiveness of the proposed methodology. The centralized control, deterministic formulation, and stochastic formulation are also compared.

Coordinated Energy Management of Networked Microgrids in Distribution Systems

This paper presents an overview of the state of the art control strategies specifically designed to coordinate distributed energy storage (ES) systems in microgrids. Power networks are undergoing a transition from the traditional model of centralised generation towards a smart decentralised network of renewable sources and ES systems, organised into autonomous microgrids. ES systems can provide a range of services, particularly when distributed throughout the power network. The introduction of distributed ES represents a fundamental change for power networks, increasing the network control problem dimensionality and adding long time-scale dynamics associated with the storage systems’ state of charge levels. Managing microgrids with many small distributed ES systems requires new scalable control strategies that are robust to power network and communication network disturbances. This paper reviews the range of services distributed ES systems can provide, and the control challenges they introduce. The focus of this paper is a presentation of the latest decentralised, centralised and distributed multi-agent control strategies designed to coordinate distributed microgrid ES systems. Finally, multi-agent control with agents satisfying Wooldridge’s definition of intelligence is proposed as a promising direction for future research.

https://orbit.dtu.dk/files/190879836/C_Users_Thomas_Documents_UNSW_PhD_Research_Paper_Review_Control_for_Microgrids_with_Distributed_Energy_Storage_Systems_Draft_Final_160612_Review_MA_MG_ES.dvi.pdf

Control Strategies for Microgrids With Distributed Energy Storage Systems: An Overview

Energy storage may improve power management in microgrids that include renewable energy sources. The storage devices match energy generation to consumption, facilitating a smooth and robust energy balance within the microgrid. This paper addresses the optimal control of the microgrid's energy storage devices. Stored energy is controlled to balance power generation of renewable sources to optimize overall power consumption at the microgrid point of common coupling. Recent works emphasize constraints imposed by the storage device itself, such as limited capacity and internal losses. However, these works assume flat, highly simplified network models, which overlook the physical connectivity. This work proposes an optimal power flow solution that considers the entire system: the storage device limits, voltages limits, currents limits, and power limits. The power network may be arbitrarily complex, and the proposed solver obtains a globally optimal solution.

/pdf/optimal-power-flow-in-microgrids-with-energy-storage-2lb9d6owge.pdf

Optimal Power Flow in Microgrids With Energy Storage

In this study a new scheme of a step-up converter with very high voltage gain is proposed. The scheme is based on a natural combination of the switched-coupled-inductor boost converter and the diode-capacitor multiplier. The study proposes a special scheme of their mutual use for attaining very high voltage gain. An important advantage of the proposed circuit is the avoidance of the current spikes through the transistor and diodes because of the leakage inductance of the coupled inductors. The scheme provides soft commutation of the switch and the diodes. The study analyses the modes of operation and obtains the basic fundamental relations in steady state; an expression for voltage stress across the switch is derived. A new method for dynamic analysis is proposed. The corresponding analytical expressions and curves of the transient behaviour are also obtained. Modelling of the proposed structure and the experimental results are in full agreement regarding the expected efficiency and correctness of the theoretical analysis. A 100 W laboratory prototype was built and verified.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-pel.2014.0785

High step-up DC–DC converter based on the switched-coupled-inductor boost converter and diode-capacitor multiplier: steady state and dynamics

Non-intrusive load monitoring is an algorithm or process that disaggregates the total power in a facility to identify consumption of individual appliances In this paper, a new algorithm is proposed to classify events of appliance states based on modification of the cross-entropy (CE) method The main contribution is a formulation and solution of the problem with the CE method as a constrained optimization problem This new technique is called the modified CE method The proposed algorithm is simple, as it operates in real time, using low rate sampling of the active power In addition, there is no need to train the system or to use complex hardware The algorithm is tested using the REDD and AMPds datasets and the results are compared to several state-of-the-art techniques

Modified Cross-Entropy Method for Classification of Events in NILM Systems

A general transposed series-parallel topology of a switched-capacitor converter is presented and analyzed in this paper. This topology evolved from the conventional series-parallel through rectangular matrices based topologies to partial arbitrary matrices which are constructed of different size strings of capacitors to arbitrary matrices, based on a bank of equally valued capacitors. Theoretically, these topologies have a large number of dc/dc voltage ratios, which lead to the capability to achieve very accurate fixed dc/dc voltage ratios. These topologies also have the capability for “fine tuning” when voltage regulation is necessary. For the general transposed series-parallel topology, it is shown that the number of possible dc/dc voltage transfer ratios escalates exponentially with an addition of each capacitor as the sum of partition functions. Therefore, relatively fewer components are required for an assumed accurate voltage ratio. Dispersion of parameters in the capacitance value is considered. Small ripple analysis, losses calculations and efficiency considerations are also discussed. Simulations are performed for 2.2 and 2.25 voltage ratios. The simulations are in good agreement with the theoretical calculations.

Yuval Beck

Papers

Optimal Power Flow in Microgrids With Energy Storage

High step-up DC–DC converter based on the switched-coupled-inductor boost converter and diode-capacitor multiplier: steady state and dynamics

Modified Cross-Entropy Method for Classification of Events in NILM Systems

Capacitive Transposed Series-Parallel Topology With Fine Tuning Capabilities

MO-NILM: A multi-objective evolutionary algorithm for NILM classification