There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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

Introduction to Electromagnetic Compatibility

More than a decade of research in the field of thermal, motion, vibration and electromagnetic radiation energy harvesting has yielded increasing power output and smaller embodiments. Power management circuits for rectification and DC-DC conversion are becoming able to efficiently convert the power from these energy harvesters. This paper summarizes recent energy harvesting results and their power management circuits.

Micropower energy harvesting

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.

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Optimal Power Flow in Microgrids With Energy Storage

Differential power processing (DPP) architectures employ distributed, low power processing, submodule-integrated converters to mitigate mismatches in photovoltaic (PV) power systems, while introducing no insertion losses. This paper evaluates the effects of the simple voltage-balancing DPP control approach on the submodule-level maximum power point (MPP) efficiency. It is shown that the submodule MPP efficiency of voltage-balancing DPP converters exceeds 98% in the presence of worst-case MPP voltage variations due to irradiance or temperature mismatches. Furthermore, the effects of reduced converter power rating in the isolated-port DPP architecture are investigated by long-term, high-granularity simulations of five representative PV system scenarios. For partially shaded systems, it is shown that the isolated-port DPP architecture offers about two times larger energy yield improvements compared to full power processing (FPP) module-level converters, and that it outperforms module-level FPP approaches even when the power rating of DPP converters is only 20-30% of the PV system peak power. In the cases of aging-related mismatches, more than 90% of the energy yield improvements are obtained with DPP converters rated at only 10% of the PV peak power.

Performance of Power-Limited Differential Power Processing Architectures in Mismatched PV Systems

A fast and unconditionally stable maximum power point tracking scheme with high tracking efficiency is proposed for photovoltaic generators. The fast dynamics and all range stability are attained by a sliding mode control and the high tracking efficiency by a maximum power point algorithm with fine step. In response to a sudden change in radiation, our experiments show a typical convergence time of 15 ms. This is the fastest convergence time reported to date. In addition we demonstrate stable convergence all across the photovoltaic curve, from short-circuit to open-circuit. The theory is validated experimentally.

Maximum Power Point Tracking Employing Sliding Mode Control

Electric-drive vehicles, including hybrid (HEV), plug-in hybrid (PHEV) and electric vehicles (EV), require a high-voltage (HV) battery pack for propulsion, and a low-voltage (LV) dc bus for auxiliary loads. This paper presents an architecture that uses modular dc-dc bypass converters to perform active battery cell balancing and to supply current to auxiliary loads, eliminating the need for a separate HV-to-LV high step-down dc-dc converter. The modular architecture, which achieves continuous balancing of all cells, can be used with an arbitrary number of cells in series, requires no control communications between converters, and naturally shares the auxiliary load current according to the relative state-of-charge (SOC) and capacities of the battery cells. Design and control details are provided for low-voltage, low-power dual active bridge (DAB) power converters serving as bypass converter modules. Experimental results are presented for a system consisting of two series 3.6 Ah NMC battery cells and two DAB bypass converters, with combined outputs rated to supply a 12 V, 35 W auxiliary load.

Active balancing system for electric vehicles with incorporated low voltage bus

Batteries are promising storage technologies for stationary applications because of their maturity, and the ease with which they are designed and installed compared to other technologies. However, they pose threats to the environment and human health. Several studies have discussed the various battery technologies and applications, but evaluating the environmental impact of batteries in electrical systems remains a gap that requires concerted research efforts. This study first presents an overview of batteries and compares their technical properties such as the cycle life, power and energy densities, efficiencies and the costs. It proposes an optimal battery technology sizing and selection strategy, and then assesses the environmental impact of batteries in a typical renewable energy application by using a stand-alone photovoltaic (PV) system as a case study. The greenhouse gas (GHG) impact of the batteries is evaluated based on the life cycle emission rate parameter. Results reveal that the battery has a significant impact in the energy system, with a GHG impact of about 36–68% in a 1.5 kW PV system for different locations. The paper discusses new batteries, strategies to minimize battery impact and provides insights into the selection of batteries with improved cycling capacity, higher lifespan and lower cost that can achieve lower environmental impacts for future applications.

Yoash Levron

Papers

Optimal Power Flow in Microgrids With Energy Storage

Performance of Power-Limited Differential Power Processing Architectures in Mismatched PV Systems

Maximum Power Point Tracking Employing Sliding Mode Control

Active balancing system for electric vehicles with incorporated low voltage bus

Battery Storage Technologies for Electrical Applications: Impact in Stand-Alone Photovoltaic Systems