Battery sizing for a stand alone passive wind system using statistical techniques

In this paper, an original optimization method to jointly determine a reduced study term and an optimum battery sizing is investigated. This storage device is used to connect a passive wind turbine system with a stand alone network. A Weibull probability density function is used to generate different wind speed data. The passive wind system is composed of a wind turbine, a permanent magnet synchronous generator feeding a diode rectifier associated with a very low voltage DC battery bus. This study is essentially based on a similitude model applied on an 8 kW wind turbine system. Our reference model is taken from a 1.7 kW optimized system. The wind system generated power and the load demand are coupled through a battery sized using a statistical approach

Sizing and Energy Management of a Hybrid Locomotive Based on Flywheel and Accumulators

The French National Railways Company (SNCF) is interested in the design of a hybrid locomotive based on various storage devices (accumulator, flywheel, and ultracapacitor) and fed by a diesel generator. This paper particularly deals with the integration of a flywheel device as a storage element with a reduced-power diesel generator and accumulators on the hybrid locomotive. First, a power flow model of energy-storage elements (flywheel and accumulator) is developed to achieve the design of the whole traction system. Then, two energy-management strategies based on a frequency approach are proposed. The first strategy led us to a bad exploitation of the flywheel, whereas the second strategy provides an optimal sizing of the storage device. Finally, a comparative study of the proposed structure with a flywheel and the existing structure of the locomotive (diesel generator, accumulators, and ultracapacitors) is presented

Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks

The optimal integration of distributed energy resources (DERs) is a multiobjective and complex combinatorial optimization problem that conventional optimization methods cannot solve efficiently. This paper reviews the existing DER integration models, optimization and multi-criteria decision-making approaches. Further to that, a recently developed monarch butterfly optimization method is introduced to solve the problem of DER mix in distribution systems. A new multiobjective DER integration problem is formulated to find the optimal sites, sizes and mix (dispatchable and non-dispatchable) for DERs considering multiple key performance objectives. Besides, a hybrid method that combines the monarch butterfly optimization and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to solve the formulated large-scale multi-criteria decision-making problem. Whilst the meta-heuristic optimization method generates non-dominated solutions (creating Pareto-front), the TOPSIS approach selects that with the most promising outcome from a large number of alternatives. The effectiveness of this approach is verified by solving single and multiobjective dispatchable DER integration problems over the benchmark 33-bus distribution system and the performance is compared with the existing optimization methods. The proposed model of DER mix and the optimization technique significantly improve the system performance in terms of average annual energy loss reduction by 78.36%, mean node voltage deviation improvement by 9.59% and average branches loadability limits enhancement by 50%, and minimized the power fluctuation induced by 48.39% renewable penetration. The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems

Signal synthesis by means of evolutionary algorithms

In this article, we investigate a procedure for generating signals with genetic algorithms. Signals are obtained from elementary patterns characterized by different degrees of freedom. These patterns are repeated and combined in order to reach specific signal shapes. The whole signal parametrization has to be determined by solving a difficult inverse problem of high dimensionality and strong multimodality. This can be carried out using evolutionary algorithms with the aim of finding all pattern configurations in the signal. The different signal synthesis schemes are evaluated, tested and applied to the generation of particular railway driving profiles

A new method to energy saving in a micro grid

Optimization of energy production systems is a relevant issue that must be considered in order to follow the fossil fuels consumption reduction policies and CO2 emission regulation. Increasing electricity production from renewable resources (e.g., photovoltaic systems and wind farms) is desirable but its unpredictability is a cause of problems for the main grid stability. A system with multiple energy sources represents an efficient solution, by realizing an interface among renewable energy sources, energy storage systems, and conventional power generators. Direct consequences of multi-energy systems are a wider energy flexibility and benefits for the electric grid, the purpose of this paper is to propose the best technology combination for electricity generation from a mix of renewable energy resources to satisfy the electrical needs. The paper identifies the optimal off-grid option and compares this with conventional grid extension, through the use of HOMER software. The solution obtained shows that a hybrid combination of renewable energy generators at an off-grid location can be a cost-effective alternative to grid extension and it is sustainable, techno-economically viable, and environmentally sound. The results show how this innovative energetic approach can provide a cost reduction in power supply and energy fees of 40% and 25%, respectively, and CO2 emission decrease attained around 18%. Furthermore, the multi-energy system taken as the case study has been optimized through the utilization of three different type of energy storage (Pb-Ac batteries, flywheels, and micro—Compressed Air Energy Storage (C.A.E.S.)

Distributed Power Generation Scheduling, Modelling and Expansion Planning

Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue

Multi objective optimization in charge management of micro grid based multistory carpark

Distributed power supply with the use of renewable energy sources and intelligent energy flow management has undoubtedly become one of the pressing trends in modern power engineering, which also inspired researchers from other fields to contribute to the topic. There are several kinds of micro grid platforms, each facing its own challenges and thus making the problem purely multi objective. In this paper, an evolutionary driven algorithm is applied and evaluated on a real platform represented by a private multistory carpark equipped with photovoltaic solar panels and several battery packs. The algorithm works as a core of an adaptive charge management system based on predicted conditions represented by estimated electric load and production in the future hours. The outcome of the paper is a comparison of the optimized and unoptimized charge management on three different battery setups proving that optimization may often outperform a battery setup with larger capacity in several criteria.Web of Science117art. no. 179

Multiobjective optimization of hybrid wind-photovoltaic plants with battery energy storage system : Current situation and possible regulatory changes

Acknowledgments: The authors would like to thank the Brazilian National Council for Scientific and Technological Development - CNPq Brazil (Processes 406769/2018-4, 308021/2019-3, 302751/2020-3), the National School of Public Administration - ENAP Brazil (Process 04600.003102/2020-21) and the Coordination for the Improvement of Higher Education Personnel - Capes Brazilfor the financial support and research incentive.Peer reviewe