Decision Making for Energy Management in Smart Grid

The chapter discusses the problem of energy management in Smart MicroGrid. The strategies of Smart MicroGrid energy management and objectives of Smart MicroGrid operation have been analyzed. The chapter emphasizes the potential of information technologies implementation to achieve energy management goals and provide a description of energy management information system which is used for MicroGrid planning and operation. The information flows which are used for making decision on Smart MicroGrid energy management have been analyzed.

Development of Planning and Operation Guidelines for Strategic Grid Planning of Urban Low-Voltage Grids with a New Supply Task

In contrast to rural distribution grids, which are mostly “feed-in oriented” in terms of electrical power, urban distribution grids are “load oriented”, as the number of customer connections and density of loads in urban areas is significantly higher than in rural areas. Taking into account the progressive electrification of the transport and heating sector, it is necessary to assess the required grid optimization or expansion measures from a conventional, as well as an innovative point of view. This is necessary in order to be able to contain the enormous investment volumes needed for transforming the energy system and aligning the infrastructures to their future requirements in time. Therefore, this article first explains the methodological approach of allocating scenarios of the development of electric mobility and heat pumps to analyzed grids. The article continues with describing which power values need to be applied and which conventional and innovative planning measures are available for avoiding voltage band violations and equipment overloads within the framework of strategic grid planning. Subsequently, the results of grid planning studies are outlined and evaluated with an assessment model that evaluates capital as well as operational costs. On this basis, planning and operation guidelines for urban low-voltage grids are derived. The main result is that low-voltage grids can accommodate charging infrastructure for electric mobility, as well as heat pumps to a certain degree. In addition, it is concluded that conventional planning measures are not completely avoidable, but can be partially avoided or deferred through dynamic load management.

Construction Planning and Operation of Battery Swapping Stations for Electric Vehicles: A Literature Review

The popularity of electric vehicles has been limited by factors such as range, long charging times and fast power failure in winter. In order to overcome these challenges, battery swapping stations (BSS) have been constructed and greatly promoted in recent years. In this paper, the related literature on electric vehicle service is reviewed and the co-occurrence of keywords is analyzed using CiteSpace. The literature is classified according to clustering results and recurring themes, such as the location of BSS, inventory decisions, charging strategies and BSS assignment. In each topic, typical optimization models and algorithms proposed in previous studies are summarized. Then, this paper gives a case about the business model and revenue capacity calculation of BSS. Finally, it points out the future research direction of battery swapping stations for electric vehicles.

Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation

This editorial document provides the main motivations and a brief description of each paper published in the “Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation” Special Issue. This Special Issue aims to present several innovative solutions on planning and operation of distribution power networks under smart grid paradigm where prosumers, electric vehicles, and other typical loads are usually connected. Some of those solutions and computational applications were covered in this Special Issue, namely probabilistic power flow, voltage and power factor control, agent-based simulation, digital twin, resilient energy scheduling, and uncertainty modeling are among the contributions. The published works are very timely and are of great interest, which will certainly drive the impact of future researchers in the near term concerning the field of this Special Issue.

Research on a Bi-Level Collaborative Optimization Method for Planning and Operation of Multi-Energy Complementary Systems

Multi-energy complementary systems (MCSs) are complex multilevel systems. In the process of system planning, many aspects—such as power planning, investment cost, and environmental impact—should be considered. However, different decision makers tend to have different levels of control objectives, and the multilevel problems of the system need to be solved effectively with comprehensive judgment. Therefore, based on the terminal MCS energy structure model, the optimization method of MCS planning and operation coordination, considering the influence of planning and operation in the system’s life cycle, is studied in this paper. Consequently, the research on the collaborative optimization strategy of MCS construction and operation was carried out based on the bi-level multi-objective optimization theory in this paper. Considering the mutual restraint and correlation between system construction and operation in practical engineering, a bi-level optimization model for collaborative optimization of MCS construction and operation was constructed. To solve the model effectively, the existing non-dominated sorting genetic algorithm III (NSGA-III) was improved by the authors on the basis of previous research, which could enhance the global search ability and convergence speed of the algorithm. To effectively improve and strengthen the reliability of energy supply, and increase the comprehensive energy utilization of the system, the effects of carbon transaction cost and renewable energy penetration were considered in the optimization process. Based on an engineering example, the bi-level model was solved and analyzed. It should be noted that the optimization results of the model were verified to be applicable and effective by comparison with the single-level multi-objective programming optimization. The findings of this paper could provide theoretical reference and practical guidance for the planning and operation of MCSs, making them significant for social application.