The smart energy management system as a powerful tool is implemented to manage both demands and generation units. The energy management problem in a Microgrid is usually formulated as a nonlinear optimization problem. According to nonlinear and discreet nature of the problem, solving it by a centralized method requires high computational capabilities. In this paper, two DISTRIBUTED energy management system called Alternating Direction Method of multiplier Predictor (ADMM) and Corrector Proximal Multiplier (PCPM) have been investigated in order to jointly schedule the central controller as well as local controllers. The algorithms consider optimal power flow equations within the DISTRIBUTED energy management problem. The proposed DISTRIBUTED algorithms have been investigated on a typical MG and the efficiency of the algorithm has been evidenced through case studies. Simulation results show that the proposed method decreases the operational cost of MG. Also, the results evidenced that the ADMM has been converged faster and provided a lower operation cost if compared to the PCPM.

With the warming of the weather conditions and significant load growth in the distribution sector, peak management in power systems has become an essential issue in hot seasons, and demand response programs are one of the most suitable common methods for managing peak. In this article, the authors propose a new approach to network peak management in critical conditions by the distribution company. This approach is the optimal scheduling of DISTRIBUTED energy sources and various demand response RESOURCES to reduce the network's peak consumption during critical peak hours and with the lowest cost. Demand response RESOURCES in this article include the three critical peak pricing, incentive-based load curtailment, and emergency load response, which the distribution company implements. The problem is optimized using a robust complex number linear programming and considering the power uncertainty of renewable RESOURCES. Providing a peak price 14% larger than the peak price of the normal tariff can bring a suitable load impact from the critical peak program customers in the network. The participation of customers in the load curtailment program in the beginning and end hours of peak management is equal to 30% and 20% of the customer's baseline. Considering the risk related to solar production, power contribution in this program increases by 117 and 74 kilowatts for the same hours. Adopting a risk-averse strategy increases the cost by 745 $ for the distribution company and the reason is the increase in curtailment of 120 kW through the emergency demand response program.

In this paper, a method for improving the performance of the network protection system in the presence of DGs by use of intelligent devices is proposed. The method, which is implemented on a hierarchical multi-agent structure, can improve the coordination problems between overcurrent relays by using a telecommunications platform based on the IEC-61850 standard information model. By this way, the protection scheme is implemented on three levels on the relays. Each level has tasks that are implemented on a layered multi-agent structure, depending on the layout of the network under certain conditions. At the first protection level performed by relay agents, the relay protection characteristic curve is used along with the functions defined on the intelligent devices. At the second level, a database is used to record the events and the pattern of behavior chosen according to them in order to prevent the flow of information on the network and to speed up the performance of the protection system. Functional patterns recorded in the database allow agents to obtain appropriate settings without sending information to the central unit if similar conditions occur. At the third protection level, in the absence of a similar pattern, the new relay settings are calculated according to the network conditions and transmitted to the network monitoring unit. Finally, in order to verify and validate the proposed method, the proposed scheme is simulated on an experimental network in the ETAP software.

In this paper, a microgrid including a solar panel, a battery energy storage system and a diesel generator as the backup source are optimally is designed. The microgrid is considered as a part of a distribution network, that could be considered as local area. As microgrids can operate in grid-connected mode, the proposed algorithm investigates the minimization of the distribution network power loss, the amount of imported power from the utility and the curtailed load in case of emergency. The main purpose of the proposed algorithm is to minimize the overall investment, replacement and operation and maintenance costs for a microgrid. This article suggests a Lightning Attachment Procedure Optimization Algorithm to optimally design the problem of sitting and scheduling of microgrids in distribution systems. Both problems are solved simultaneously. The proposed approach is applied on 33-bus test system, and the results are discussed. Fast convergence, best global answer finding, and robustness are the characteristics of the proposed method, which are concluded from the results and discussion.

In addition to the great benefits of DISTRIBUTED generation (DG) RESOURCES to power systems, there are some disadvantages. In spite of some benefits like decrease of received power from transmission grid, increment of DGs penetration can lead to voltage increase in distribution networks during off peak. Hence the recent efforts have been made to handle problems to increase the penetration of these RESOURCES. The use of energy storage systems (ESSs) is one of the ways to prevent defects may arise from use of DGs in power systems and can help to increase penetration of DGs in power systems. ESSs can save energy during off peak and deliver it to the network in peak hours; hence, these equipment can reduce power losses and prevent voltage deviation during off peak by increasing load due to ESS charging.In this paper, first DG allocation and ESS placement are introduced then simultaneous placement of DG and ESS to reduce power losses in the distribution network are described. The proposed models are solved using genetic algorithm as optimization tool. The obtained results show that simultaneous placement could increase DG penetration compared to the separate allocation of these devices and provide further reduce of the losses in the distribution network.

Traditionally, conventional generation units were used to provide ancillary services e. g. reactive power support, and spinning reserve. Nonetheless, with the emergence of highly penetrated DISTRIBUTED energy RESOURCES (DERs) systems and considering how beneficial they can be; it appears reasonable to use them as reactive power providers. Therefore, this paper introduces a new procedure for DERs to participate in the reactive power market. To do that, an algorithm is proposed to calculate the deliverable reactive power capability of DERs from distribution networks to transmission systems. Furthermore, a reactive power procurement model is introduced to consider DERs participation in the reactive power market. Finally, to show the effectiveness, and validity of this method many case studies are carried out on 33-bus distribution and CIGRE 32-bus transmission test systems

Purpose: The purpose of this applied research is to study the effectiveness of gamification on corporate training.  Methodology: A gamified course was designed and implemented to train the location of Fire Hosing Cabinet for 24 employees of a firefighting maintenance company in Iran Mall shopping Center in Tehran. Using a quantitative quasi-experimental research plan (post-test only control group design) the participants of the study were randomly assigned to treatment (12) and control (12) groups and trained for a week.  Conclusion: The descriptive and interpretive result of the posttest analyses indicated the effectiveness of gamification of the training performed for the employees of the firefighting maintenance company in Iran Mall shopping Center in Tehran. Moreover, the descriptive result of Gamification Acceptance Questionnaire answered by the members of the experimental group after gamified training indicated that all the participants in the experimental group were satisfied with the gamified training course.

The integration of DISTRIBUTED Energy RESOURCES (DER) in power systems can provide the opportunity to supply electricity to customers more efficiently and effectively. The DER includes DISTRIBUTED Generation (DG) and Demand Side Management (DSM). In a smart grid incorporating automated control and DISTRIBUTED energy systems an effective DSM can alleviate the peak load and shift part of the demand to off-peak hours. The aim of this research is to assess the impact of the DG and the DSM on reliability of the smart distribution system by analyzing different case studies. Roy Billinton test system RBTS Bus2 is used to validate case studies which are performed as a part of this paper. For more practical considerations, a modification of the RBTS Bus2 model is developed to assess the system reliability