Stochastic multi-carrier energy management in the smart islands using reinforcement learning and unscented transform

Zou, Hongbo; Tao, Juan; Elsayed, Salah K.; Elattar, Ehab E.; Almalaq, Abdulaziz; Mohamed, Mohamed A.

doi:10.1016/j.ijepes.2021.106988

Cited by 66 publications

(28 citation statements)

References 36 publications

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“…The RL method is used for widespread applications. For example, a distributed multiagent-based RL method has been proposed in [36] for optimal reactive power flow. In order to bring the simulation closer to the reality, the load and production uncertainty are considered and the UT method is used to simulate the uncertainty.…”

Section: B Detecting Fdia and Proposed Solutionmentioning

confidence: 99%

A Secured Advanced Management Architecture in Peer-to-Peer Energy Trading for Multi-Microgrid in the Stochastic Environment

et al. 2021

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Careful consideration of grid developments illustrates the fundamental changes in its structure which its developments have taken place gradually for a long time. One of the most important developments is the expansion of the communication infrastructure that brings many advantages in the cyber layer of the system. The actual execution of the peer-to-peer (P2P) energy trading is one core advantage which also may lead to the systematic risks such as cyber-attacks. Consequently, it is necessary to form a useful way to cover such challenges. This paper focuses on the online detection of false data injection attack (FDIA), which tries to disrupt the trend of optimal peerto-peer energy trading in the stochastic condition. Moreover, this article proposes an effective modified Intelligent Priority Selection based Reinforcement Learning (IPS-RL) method to detect and stop the malicious attacks in the shortest time for effective energy trading based on the peer to peer structure. The presented method is compared with other methods such as support vector machine (SVM), reinforcement learning (RL), particle swarm optimization (PSO)-RL, and genetic algorithm (GA)-RL to validate the functionality of the method. The proposed method is implemented and examined on three interconnected microgrids in the form of peer-to-peer structure wherein each microgrid has various agents such as photovoltaic (PV), wind turbine, fuel cell, tidal system, storage unit, etc. Eventually, the unscented transformation (UT) is applied for uncertainty analysis and making the nearreality simulations., m Value of the average and variance. cThe injected malicious data.Attack time.

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Section: B Detecting Fdia and Proposed Solutionmentioning

confidence: 99%

A Secured Advanced Management Architecture in Peer-to-Peer Energy Trading for Multi-Microgrid in the Stochastic Environment

et al. 2021

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“…Components of W are arranged by considering the fitting function. The W j matrix is indicated as an array of the W matrix components (37) defined in this thread. This process is also precise for set K j (38).…”

Section: Intelligent Priority Selection Algorithmmentioning

confidence: 99%

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

et al. 2021

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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.

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“…(7) and Eq. ( 8) respectively [36][37][38]. Alpha () is crucial to estimate wind velocities at higher altitudes by processing the wind velocities measured at lower or previous altitudes.…”

Section: Shear Profilementioning

confidence: 99%

Power Supply to Local Communities Through Wind Energy Integration: An Opportunity Through China-Pakistan Economic Corridor (CPEC)

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Global warming and depletion of fossil fuels have urged the world to control their impacts and find clean and green energy sources. Due to this paradigm shift, renewable energy resources (RESs) have received tremendous attention around the globe and amongst other RESs, wind energy has been proving itself a promising renewable resource. However, still, the proper selection of wind turbines (WTs) and their installation is considered a major challenge. Presently, due to the economic boom of Pakistan as a regional power under the China Pakistan Economic Corridor (CPEC) and increasing energy demand, it needs to meet the energy shortage. This paper aims to conduct a pre-feasibility investigation of wind farm exploitation at Gwadar and Quetta, major cities of Baluchistan province in Pakistan by harnessing the wind energy potential and electricity generation cost through different WT models. The wind speed (WS) data is recorded by a professional wind mast at different measurement heights during F.Y 2016 and analyzed using Five approaches, Modified Maximum Likelihood Method (MMLM), Graphical Method (GM), Empirical Method of Lysen (EML), Empirical Method of Jestus (EMJ) and Energy Pattern Factor Method (EPF) at the proposed site and EPF shows the best performance than other approaches. Different WTs models are also evaluated and out of them, the GW121 WT gives the lowest cost in dollars and lowest payback period at each site so it can be recommended as one of the most feasible WT for electricity generation for powering local communities at the proposed sites.

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Stochastic multi-carrier energy management in the smart islands using reinforcement learning and unscented transform

Cited by 66 publications

References 36 publications

A Secured Advanced Management Architecture in Peer-to-Peer Energy Trading for Multi-Microgrid in the Stochastic Environment

A Secured Advanced Management Architecture in Peer-to-Peer Energy Trading for Multi-Microgrid in the Stochastic Environment

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

Power Supply to Local Communities Through Wind Energy Integration: An Opportunity Through China-Pakistan Economic Corridor (CPEC)

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