- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
State estimation (SE) is well-established at the transmission system level of the electricity grid, where it has been in use for the last few decades and is a most vital component of energy management systems employed in the monitoring and control centers of electric transmission systems. However, its use for the monitoring and control of power distribution systems (DSs) has not yet been widely implemented because DSs have been majorly passive with uni-directional power flows. This scenario is now changing with the advent of smart grid, which is changing the nature of electric distribution networks by embracing more dispersed generation, demand responsive loads, and measurements devices with different data rates. Thus, the development of distribution system state estimation (DSSE) tool is inevitable for the implementation of protection, optimization, and control techniques, and various other features envisioned by the smart grid concept. Due to the inherent characteristics of DS different from those of transmission systems, transmission system state estimation (TSSE) is not applicable directly to DSs. This paper is an attempt to present the state-of-the-art on DSSE as an enabler function for smart grid features. It broadly reviews the development of DSSE, challenges faced by its development, and various DSSE algorithms. Additionally, it identifies some future research lines for DSSE.
6.5. Advanced energy management systems for DS
ADMS is another good research area where DSSE has to play a fundamental role. The relationship of DMS with its TS counterpart, i.e. EMS, is depicted in Fig. 11. Earlier, DSs were passive with unidirectional power flows, which made their management and control easy. However, the future smart grid is transforming the existing power distribution grid in terms of 1) communication infrastructure, 2) integration of sources of different nature, 3) involvement of different types of loads and equipments, 4) data accumulation, 5) data security and sharing, and 6) deregulation of electricity grid which brings in many business players . Thus, the future grid would be an extra ordinary complex grid, whose operations would require certain common platform to increase its operational flexibility by facilitating flexible data exchange and system interoperability [122,123]. This would in turn require a fully functional DMS, which integrate sources and loads of different nature, and provide a platform for different utilities to cooperate in data sharing. In this regard, many researchers have tried to develop management and control functions to enhance system monitoring at the distribution level [124,125]. Algorithms for three important functions of DMS, namely load estimation, ac power flow, and optimal system re-configuration, are presented in . Another similar study is performed in , in which the authors demonstrate the development of standard measurement-acquisition system and a real-time situational-awareness function for the Korean Smart grid initiative project. In , the authors developed an application software for DMS, which was used to investigate the effect of missing or delayed measurements on DSSE. In , a two-level DSSE algorithm is proposed for DMS of low-voltage (LV) DN. This algorithm was tested on a LV-network, which has a mixture of conventional-generation sources and DGs, smart-loads, and storagefacility. The authors in , develop a DMS framework integrating network modeling, SE and control for the implementation of Volt/Var support service. However, these algorithms are proposed mainly for radial DNs and doesn’t take into account meshed network topology. In this regard, a possible future work may consider the modification of  for meshed network topology with enhanced DG integration. Efficient and quickly convergent power flow algorithms, for instance [131–133], that considers both radial and meshed network models and integration of multi-DER, may be adopted.