The power-electronic-based grid emulator has been widely used for grid-code compliance testing of wind turbines (WTs). To accommodate the increasing voltage and power levels of WTs, the modular multilevel converter (MMC) emerges as a promising approach for the future grid emulator. This paper provides an overview of testing requirements and control strategies for the MMC-based grid emulator. Specifications, challenges and solutions to implement expected control functionalities of the MMCbased grid emulator are discussed according to testing requirements of WTs. Emerging testing functionalities and future trends of grid emulators conclude this paper.
In power systems, the installed generation capacity must exceed the annual peak demand, even though some capacity is kept idle most of the time. However, if it is uneconomical or not feasible to augment a sufficient capacity, the demand might exceed the available capacity. This mandates the system operator to shed the load in order to maintain security of the system. With the advent of advanced smart metering infrastructure, communication between system operator and end-use customers makes it possible to adjust/curtail/shift the demand with respect to the state of the system. The response of the demand commonly termed as demand response (DR) can be attained either by incentive-based or pricebased. With the help of DR, the renewable energy generation capacity can be increased by tuning the demand to match the variable and unpredictable power from renewable generation. It can also bring other benefits such as peak shaving, hosting capacity enhancement, and generation cost reduction. Furthermore, electric vehicles, heat pumps, and electric water heater can also be used as distributed storage resources to contribute to ancillary services, such as frequency/ voltage regulation, peak-shaving power or help to integrate fluctuating renewable resources. All these DR modes of operation need conventional regulatory frameworks and market design for capitalizing the available resources. Therefore, the objective of the study is to discuss the DR classification and their control strategies, DR role in microgrids and integration of renewable energy resources. Also, highlighted the opportunities and challenges along with the insights for the research scope associated with DR.
Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy.
Purpose – The purpose of the paper is to find the best distributed generators (DGs) location for improving reliability and reducing power loss using distribution system reconfiguration. This is implemented in the presence of the tie-switches. It proposes a search-based algorithm for the reconfiguration problem. Individual DG placement is obtained for all system configurations, and analytical hierarchy process tool is used for finding the overall best location. This is carried out for various system loadings. Design/methodology/approach – This paper proposes a knowledge-based search algorithm which needs the base conditions of the distribution system. A detailed analysis is carried out for finding the best DG locations from the obtained DG placements for various system configurations. Simulations are rigorously carried out with the help of programming. Results from these simulations are further given to analytical hierarchy tool for obtaining the DGs location. Findings – The findings of the paper are the DG placement for various system loadings and various system configurations and to obtain the best DG location for any system configuration. A search-based algorithm is designed for accomplishing it. Originality/value – The proposed method identifies the placement of distributed generation at distribution systems for reliability improvement and power loss reduction which is one of the present day needs for fulfilling the raising power consumers.
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