This paper proposes a system analysis focused on finding the optimal operating conditions (nominal capacity, cycle depth, current rate, state of charge level) of a lithium battery energy storage system. The purpose of this work is to minimize the cost of the storage system in a renewable DC microgrid. Thus, main stress factors influencing both battery lifetime (calendar and cycling) and performances are described and modelled. Power and energy requirements are also discussed through a probabilistic analysis on some years of real data from the ADREAM photovoltaic building of the LAAS-CNRS in Toulouse, FRANCE.

The increasing penetration of distributed energy resources in next-generation distribution networks has resulted in an explosion of the Internet of Things to upgrade their control and monitoring systems. This poses new challenges for the efficient energy management and reliable decision-making of these systems. This is due to the potentially large amount of data that cannot be handled by the traditional architecture of control and data acquisition systems, which have limited storage and computation capabilities. In order to adapt to the new energy management requirements of next-generation distribution networks, a state-of-the-art energy management method called cloud-fog hierarchical architecture is proposed in this work. Based on this architecture, we established a utility and revenue model for various stakeholders, including normal customers, prosumers, and distribution system operators. Furthermore, by embedding an artificial intelligence module in the proposed architecture, energy management could be implemented automatically. Neural networks were used at fog computing layers to achieve regression prediction of energy usage behavior and power source output. Moreover, based on the maximizing utility objective function, the amount of energy consumption of customers and prosumers in the distribution network was optimized with a genetic algorithm at cloud layer. The proposed methods were tested with a set of normal customers and prosumers in a general distribution network, and the results, including the captured usage patterns of the customers and revenues of various stakeholders, verify the effectiveness of the proposed method. This work provides an effective reference for the development of real-time energy management systems for the next-generation distribution network.

International audienceThe increasing deployment of intermittent renewable energy sources (RESs) around the world has revealed concerns about the power grid stability. To solve this problem, a massive use of storage systems is needed. The main goal of this work is to develop a hybrid energy storage system (HESS) combining several storage devices with complementary performances. In this paper, lead-acid batteries and supercapacitors (SCs) are associated in order to deliver a pulsed current. An innovative cascade control with anti-windup tracking manages the power sharing between a buck and a boost converters connected to the same DC bus. Analog control circuits and power converters have been designed to evaluate the performances of the HESS in real conditions

Microgrid (MG) is an efficient platform to integrate distributed energy resources in distribution networks.The operation of MG is also expected to take advantage of emerging smart grid technologies to improve operation and robustness. Among these emerging technologies, blockchain technology provide a big potential to rule the energy transaction in an innovative way. In this paper, a physical architecture of the ecosystem with MGs is firstly presented. Moreover, as the main parts of the blockchain technology, the operation of distributed ledger and smart contracts are introduced in the transaction process. Considering dynamic pricing scheme in the process of energy transaction in the ecosystem, we model the energy transaction between MGs and distribution system operator (DSO) to decide the trading amount and price of the energy. The welfare maximization mathematical model is established accordingly, and the formulated dual problem will be used to find the shadow price of selling renewable energy to grid and real-time retailer price from DSO. Finally, with the deployment of distribution ledger, the energy transaction process can be fully recorded, and transaction execution can be achieved with the help of smart contracts. In light of the mentioned perspective, beside demonstrated benefit brought to both MGs and DSO, the energy transaction and management based on the blockchain will result in higher reliability and improved auditability in the ecosystem.

In the global context of the electric power grid modernization, storage of electricity is a crucial issue. Nowadays, energy storage systems (ESS) are used more and more in positive energy buildings in conjunction with new Low Voltage Direct Current (LVDC) grids. However, the impact of renewable energy sources (RES) on ESS is not well known. The main objective of this article is to determine a systematic methodology to study energy data from a positive energy building in order to determine the impact on ESS dedicated to be included in smartgrids. The aim is to obtain comparative results in normalized working conditions and determine charge/discharge cycles. Clustering methods were compared to choose the more adapted one to treat the stored data of energy production and consumption during more than three years in our experimental platform in LAAS-CNRS, Toulouse. Each type of cycle will help further study in order to estimate its impact on efficiency and lifetime of ESS and then choose the more adapted element for each application.

Light emitting diodes (LEDs) are commonly expected to be the future of lighting because of a high luminous efficacy, a long lifetime and a high color rendering index (CRI). Nevertheless, the performance and the reliability of an LED are strongly dependent on the LED junction temperature. This paper presents a multi-objective methodology to find the optimal forward current subject to the annualized cost of the luminaire (initial capital cost, replacement cost, operation and maintenance cost…) and the annualized energy consumption. A simple LED model based on empirical data has been developed and takes into account optical, electrical, thermal and ageing behaviour. Three different white LEDs have been evaluated through several combinations of forward currents and heatsinks to satisfy a given mission profile. A set of optimal solutions has been determined by Pareto optimization.

Energy storage systems (ESSs) can enhance the performance of energy networks in multiple ways; they can compensate the stochastic nature of renewable energies and support their large-scale integration into the grid environment. Energy storage options can also be used for economic operation of energy systems to cut down system's operating cost. By utilizing ESSs, it is very possible to store energy in off-peak hours with lower cost and energize the grid during peak load intervals avoiding high price spikes. Application of ESSs will also enable better utilization of distributed energy sources and provide higher controllability at supply/demand side which is helpful for load leveling or peak shaving purposes. Last but not least, ESSs can provide frequency regulation services in off-grid locations where there is a strong need to meet the power balance in different operating conditions. Each of the abovementioned applications of energy storage units requires certain performance measures and constraints, which has to be well considered in design phase and embedded in control and management strategies. This chapter mainly focuses on these aspects and provides a general framework for optimal design and operation management of battery-based ESSs in energy networks.

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