A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks

In order to coordinate the economic desire of microgrid (MG) owners and the stability operation requirement of the distribution system operator (DSO), a multi-market participation framework is proposed to stimulate the energy transaction potential of MGs through distributed and centralized ways. Firstly, an MG equipped with storage can contribute to the stability improvement at special nodes of the distribution grid where the uncertain factors (such as intermittent renewable sources and electric vehicles) exist. The DSO is thus interested in encouraging specified MGs to provide voltage stability services by creating a distribution grid service market (DGSM), where the dynamic production-price auction is used to capture the competition of the distributed MGs. Moreover, an aggregator, serving as a broker and controller for MGs, is considered to participate in the day-ahead wholesale market. A Stackelberg game is modeled accordingly to solve the price and quantity package allocation between aggregator and MGs. Finally, the modified IEEE-33 bus distribution test system is used to demonstrate the applicability and effectiveness of the proposed multi-market mechanism. The results under this framework improve both MGs and utility

Economic power schedule and transactive energy through an intelligent centralized energy management system for a DC residential distribution system

Direct current (DC) residential distribution systems (RDS) consisting of DC living homes will be a significant integral part of future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between the main grid and the demand side. The utilization of distributed generation (DG) requires an economic operation, stability, and an environmentally friendly approach in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through a centralized energy management system (CEMS), but also a control approach to implement and ensure DG output voltages to various DC buses in a DC RDS. Based on data collection, prediction and a certain objectives, the expert system in a CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency

Dynamic Pricing for Microgrids Energy Transaction in Blockchain-based Ecosystem

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-situ research progress in the elastoplastic deformation mechanism of one-dimensional monolithic nanomaterials

Recently, with the development of research techniques, researchers have discovered numerous new phenomena in nanowires with potential applications. Clearly depicting the structure-activity relationship between nanowire structure and mechanical properties has important guiding significance for the design, service and performance optimization of nanodevices. Firstly, several typical in-situ testing methods of mechanical properties of nanowires were summarized. Secondly, the mechanical properties such as elasticity and strength of various nanowires in tensile tests were introduced. The size-dependent plastic deformation of nanowires was described. In addition, the unique mechanical behavior of nanomaterials in the in-situ tests was discussed. In the future, it is necessary to systematically study the effect of electron beam irradiation on the deformation behavior of nanowires during in situ electron microscopy characterization and to investigate the mechanical properties exhibited by nanowires under complex external field environments. Thus, a complete set of theoretical guidance systems can be established, which is an important development direction in the field of in situ characterization of nanomaterial properties

A Novel Multi-Objective Optimal Approach for Wind Power Interval Prediction

Numerous studies on wind power forecasting show that random errors found in the prediction results cause uncertainty in wind power prediction and cannot be solved effectively using conventional point prediction methods. In contrast, interval prediction is gaining increasing attention as an effective approach as it can describe the uncertainty of wind power. A wind power interval forecasting approach is proposed in this article. First, the original wind power series is decomposed into a series of subseries using variational mode decomposition (VMD); second, the prediction model is established through kernel extreme learning machine (KELM). Three indices are taken into account in a novel objective function, and the improved artificial bee colony algorithm (IABC) is used to search for the best wind power intervals. Finally, when compared with other competitive methods, the simulation results show that the proposed approach has much better performance

A High-Gain DC Side Converter with a Ripple-Free Input Current for Offshore Wind Energy Systems

Considering that the distance between offshore wind farms and onshore converters is getting farther and farther, dc transmission becomes increasingly more applicable than conventional ac transmission. To reduce the transmission loss, a feasible solution is using a high-gain dc/dc converter to boost the rectified output voltage to thousands of volts. Thus, a novel single-switch high-gain dc/dc converter with a ripple-free input current is presented in this paper. The structure consists of two cells—a coupled-inductor cell and a switched-capacitor cell. The coupled-inductor cell in the proposed converter provides a ripple-free input current. The switched-capacitor cell provides a high voltage gain. The converter has a simple control strategy due to the use of a single switch. Moreover, the output capacitor is charged and discharged continuously by a 180° phase shift to eliminate the output voltage ripple. A steady-state analysis of the converter is proposed to determine the parameters of the devices. In addition, a 240 W, 40/308 V laboratory prototype at 35 kHz switching frequency has been developed, in which the input current ripple is only 1.1% and a peak efficiency of 94.5% is reached. The experimental results verify the validity and feasibility of the proposed topology

Defining Three Distribution System Scenarios for Microgrid Applications

Power systems, especially distribution systems, are undergoing the most drastic overhauls with the growing integration of renewable energy and digitalization. One of the most efficient technological solutions to address the challenges the distribution system faces today, is the formation of microgrids. With heterogeneous driving forces from policy, regulation, system operation, infrastructure developer, aggregator, and end-user, how microgrid will evolve and develop in the future distribution system remains an open question and deserve closer scrutiny. In this paper, a brief state of the art of current microgrid design is introduced considering knowledge and experience from both practitioner and academia. Based on a simple foresight method, three foreseeable scenarios for the future distribution system are depicted. Aspects related to its use cases, energy management system features, and market models will be discussed for each possible scenario. This will shed light onthe future research and development of microgrid applications