Abstract

In the last decade in Europe, the power generated by Renewable Energy Sources (RES) has significantly increased. For the electric power system, the integration of a high amount of power generated by RES represents a big challenge. Energy Storage Systems (ESS) may help to solve problems related to the grid integration of RES. In this study, an analysis of the benefits that a planned and dedicated Adiabatic Compressed Air Energy Storage (A-CAES) system may provide to a distribution network with a high penetration of RES will be carried out. The A-CAES system, taken into account in this investigation, is based on the proposed German study so-called “ADELE project”. The technical benefits as well as the corresponding costs that A-CAES brings to the system which were analyzed using the load and RES generation time series for 2010 and 2020, and were based on technical data from a selected part of a German distribution power network, were evaluated and results of those broad investigations are presented in this study. The result of the investigations shows that the direct technical benefits are quite limited for the A-CAES technology as it exists today.

Abstract

The future smart grids (SGs) consist of considerable amount of renewable energy sources (RESs), electrical vehicles (EVs), and energy storage systems (ESSs). The uncertainties associated with EVs and uncontrollable nature of RESs have magnified voltage stability challenges and the importance of an effective energy management system (EMS) in SGs as a practical solution. This study presents a multi-agent transactive energy management system (TEMS) to control demand and supply in the presence of high levels of RESs and EVs, and maximises profit of each participant in addition to satisfying voltage regulation constraints. For this purpose, a real-time pricing is considered based on Cournot oligopoly competition model for demand and merit order effect for production to compensate RESs' fluctuations in real time by an indirect control method. Simulations are conducted in the modified IEEE 37-bus test system with 1141 customers, 670 EVs, two solar plants, four wind turbines, and one ESS. The results show that the proposed multi-agent TEMS can indirectly control EVs, elastic loads, and ESSs to balance the RESs oscillation, minimise customers cost, and regulate voltage in a real-time manner. "p"QC 20171204

Abstract

In this paper, a new learning tool is proposed to train professional figures, such as entrepreneurs, engineers, and technicians, who need to improve their skills in the field of Internet of Energy. The proposed tool aims to cover the lack of experimental knowledge on new energy systems and to layer proper skills, which are useful to deal with challenges required by smart energy management in the new complex distributed configuration of the electric power systems, characterized by demand response services. This tool is based on a small-scale laboratory demonstrator, representative of a smart rural house, equipped with a measurement and control system. This demonstrator can be remotely accessed, through web server applications based on a low cost single-board computer. Trainers can have direct experience on the main concepts related to smart grids, renewable energy sources, electrochemical storage systems, and electric vehicles, through the use of the proposed tool managed by the web software interface. Document type: Article

Abstract

The increase in penetration of variable renewable energy sources (RES) introduced additional difficulties regarding the management of the Portuguese Power System. This is mainly due to the high temporal variability and low controllability, characteristics of these kinds of sources. There is a real need to reduce the impact of non-dispatchable RES sources; maximizing their penetration and minimizing curtailment. This is especially true for the wind power and run-of-the-river hudro (ROR); as it appears beneficial to combine their variable production with added capacity of energy storage and demand side management; thereby increasing the flexibility of the power system as a whole. This paper aims to assess the excess wind generation (and other non-dispatchable sources); this for periods of production's excess in a 2020 timeframe, and assuming different weather scenarios. The adjustment of wind power generation (WPG) profile to the load prfile is also addressed; the result is computed in the form of the value of the energy temporally deferred, using Pumped Hydro Storage (PHS) power plants as well as electric Vehicles (EVs)

Abstract

International audience; Lithium batteries are key solutions for sustainable energies storage and particularly interesting for green transportation. Vehicle manufacturers are making a clear transition to a more efficient and ecofriendly transport. In fact, Battery Management Systems (BMS) are crucial for a safe and optimized use of these energy storage systems. This article presents an accurate dynamic electro-thermal model for lithium batteries, designed for high power applications. The model has been implemented using MATLAB (Simulink) and parameters were obtained from experiments. Most parameters depend on current, temperature, and Battery State of Charge (SOC). The accuracy of this model is tested under different operating conditions (static and dynamic current profiles) and simulations are in agreement with experimental results, even after twenty hours of test.

Abstract

The provision of ancillary services is an additional revenue stream for the owners of inverter-equipped storage systems, such as batteries and electric vehicles. As real demonstrations have shown, primary frequency control (PFC) is a suitable and economically viable service for small-scale energy storage (ES) systems. This paper proposes a decentralized stochastic control policy, which significantly reduces ES units’ losses when providing PFC. The proposed controller can be tuned to obtain the desired service reserve provision errors, while achieving a balance between tracking accuracy and efficiency. An extension of the algorithm significantly reduces the switching rate of the devices by up to 95%. Analytical expressions for the reserve errors and the switching rates, dependent on the aggregation size and the controllers’ settings, are derived and verified by simulations. Simulation results show that the proposed controller can significantly reduce ES units’ losses when they are providing PFC by 8–15.5%, while achieving the expected tracking performance.