Abstract
Distribution system planning and operation has seen many structural changes due to the increased participation of consumers in the energy market and the adaptation of new technologies such as distributed energy resources (DERs), electric vehicles (EV) and local energy storage systems (ESSs). Despite the convenience of such technologies and the gradual drop in their prices, new technical challenges (e.g., excessive power losses) have emerged at the system level. Over the past few decades, power loss minimization in distribution systems has gained popularity and the need for loss sensitivity analysis (LSA) frameworks has become a necessity for its successful implementation. Existing work on LSA mostly focuses on system planning aspects through DER optimal placement and sizing. However, enabling LSA-based system operational applications is a vital step toward the successful transition to modern distribution systems (MDSs). Therefore, this paper presents a comprehensive overview on the state of the art in LSA for MDSs. First, the theoretical formulations of existing LSA methods are summarized. Then, the applications of LSA in distribution systems are highlighted. Finally, based on the analysis of literature, open research gaps and future research pathways are discussed.
Highlights
Modern distribution systems (MDSs) are facing major challenges due to the rapid growth in energy demand and the engagement of consumers in energy markets
This paper presents a comprehensive analysis of existing literature that uses loss sensitivity analysis (LSA) for MDS planning and optimal operation
The increased penetration levels of consumer resources in MDSs necessitates the development of accurate tools that examine their impact on system losses
Summary
Modern distribution systems (MDSs) are facing major challenges due to the rapid growth in energy demand and the engagement of consumers in energy markets. Consumers can participate in the energy market through local energy management, home automation, energy storage and usage, EV charging, DER integration, and many other ancillary services [1]. Through this participation, consumers can schedule their loads based on dynamic electricity prices [2]. There might be locations in the system where losses can be high during peak demand hours In this regard, LSA-based real-time optimal EV charging can be used to improve system efficiency and provide economic savings to utilities and consumers. The adaptation of LSA framework is essential for successful transition to MDSs
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