Effective Energy Management via False Data Detection Scheme for the Interconnected Smart Energy Hub–Microgrid System under Stochastic Framework

Abstract

During the last few years, attention has overwhelmingly focused on the integrated management of urban services and the demand of customers for locally-based supply. The rapid growth in developing smart measuring devices has made the underlying systems more observable and controllable. This exclusive feature has led the system designers to pursue the implementation of complex protocols to provide faster services based on data exchanges. On the other hand, the demands of consumers for locally-based supply could cause a disjunction and islanding behavior that demands to be dealt with by precise action. At first, keeping a centralization scheme was the main priority. However, the advent of distributed systems opened up new solutions. The operation of distributed systems requires the implementation of strong communication links to boost the existing infrastructure via smart control and supervision, which requires a foundation and effective investigations. Hence, necessary actions need to be taken to frustrate any disruptive penetrations into the system while simultaneously benefiting from the advantages of the proposed smart platform. This research addresses the detection of false data injection attacks (FDIA) in energy hub systems. Initially, a multi-hub system both in the presence of a microgrid (the interconnected smart energy hub-based microgrid system) and without it has been modeled for energy management in a way that allows them to cooperate toward providing energy with each other. Afterward, an FDIA is separately exerted to all three parts of the energy carrier including the thermal, water, and electric systems. In the absence of FDIA detection, the impact of FDIA is thoroughly illustrated on energy management, which considerably contributes to non-optimal operation. In the same vein, the intelligent priority selection based reinforcement learning (IPS-RL) method is proposed for FDIA detection. In order to model the uncertainty effects, the unscented transformation (UT) is applied in a stochastic framework. The results on the IEEE standard test system validate the system’s performance.

Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

“…LPSP desired REF REF desired 0 ≤ P PV ≤ P PV,max 0 ≤ P WT ≤ P WT,max P Bat.,min ≤ P Bat. ≤ P Bat.,max P Diesel,min ≤ P Diesel ≤ P Diesel,max (7) where LPSP desired is the predetermined limit of LPSP, which gives an indication about the reliability, and REF desired is the predetermined limit of the renewable energy fraction (REF).…”

“…These challenges represent complex and nonlinear optimization problems. Optimization means reaching the optimal solution and the best design of the HRES with minimum cost [7,8].…”

Energy Conservation Measures and Value Engineering for Small Microgrid: New Hospital as a Case Study

“…Energy conservation measures can improve not only the energy efficiency of a microgrid but also the resilience and reliability of a microgrid. A microgrid can be comprised of a decentralized photovoltaics, wind turbines, diesel generators, batteries, fuel cells (FCs), and loads that can operate autonomously (island mode) [1][2][3][4] or interconnected with the utility grid (connected mode) [5,6]. Energy conservation refers to minimizing energy consumption using more efficient equipment and appliances as well as sensible utilization.…”

An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions

“…Not having a safe cyber platform can undoubtedly raise the risk of unauthorized access due to the usage of smart devices. One of the most perilous and important attacks in the context of the power systems described in [10] is the false data injection, or FDI, attack. Reference [11] indicates how FDI attacks could overshadow energy scheduling in the electrical grid.…”

“…The authors proved the extent to which vulnerability indices can be improved by shifting from a DC microgrid. Papers [8,10] present AC/DC microgrids in a consideration of the effects of uncertainty on energy management. [23]…”