Journal of Energy Management and Technology
Volume:8 Issue: 4, Autumn 2024

The combination of various energy carriers is an essential factor in power systems to increase endurance and resistance against high-impact events to supply network loads. In this article, a model is presented that deals with the optimal economic operation of the energy hub by increasing the system load resiliency and energy security at the lowest cost. To achieve these goals, energy storage devices and types of energy carriers are used. Furthermore, the loads are categorized as critical and noncritical loads and the highest priority in this article is to supply critical loads. In addition, four scenarios are considered, and each scenario is scrutinized in four steps. Critical load resilience index and energy security indices have been studied in this article, HHI and diversity indices are energy security indices. The operating horizon is 24 hours. In this article, there is a challenge between increasing load resilience and energy security and minimizing costs in the energy hub. In this study, mixed integer nonlinear programming [MINLP] is applied to formulate this optimization problem, which is implemented and solved by GAMS software. The results show that costs rise as critical load resilience increases.

Hydrogen carrier plays an important role in today’s modern power grids. Hydrogen-based fuel cell vehicles also draw a path to a more sustainable society. This paper addresses the potential of hydrogen systems in a renewable-dominant multi-microgrid system to increase resiliency. The fuel cell-based trucks carry battery storage and act as emergency resources. A hybrid stochastic-robust optimization is proposed to optimize the scheduling plan for resources. The uncertainty of renewable output is handled by adjustable robust optimization whereas traffic of roads has been modeled using stochastic programming by using a dummy nodes and arcs model. A fuel management scheme is proposed to adjust the hydrogen fuel of the trucks. The results revealed that the corrective strategy, i.e., a combination of hydrogen facility and mobile storage improves the overall resiliency indexes. In this regard, the area covered under the resiliency trapezoid increased up to 90% under the robust case. The critical load curtailment decreased from 38.65 MW to 30.08 MW under the risk-neutral case and from 50.78 MW to 42.17 MW under the risk-averse case. The system is stronger with the proposed corrective strategies and the ramp of resiliency fall has been decreased from 0.285 to 0.199 and from 0.382 to 0.293 under risk-neutral and risk-averse cases, respectively. Finally, the replacement of a hydrogen storage system with a stationary battery storage system revealed that the stationary battery storage similarly reduces the load curtailment however the presence of hydrogen storage helps the MBS refueling which directly influences the load recovery performance.

As urbanization intensifies, cities are progressively transitioning into "smart cities," harnessing advanced technologies and data analytics to optimize infrastructure, enhance citizen services, and promote sustainable resource management. However, this evolution is accompanied by challenges, including cybersecurity, data privacy, and coordination between multiple stakeholders. This review paper examines current approaches to energy management in smart cities, exploring the pivotal roles of Internet of Things (IoT) technologies, data analytics, and security frameworks within smart energy systems. The study also provides a comparative analysis of 5G, Wi-Fi, Bluetooth, and Zigbee technologies, focusing on their potential applications in smart city environments. In addition, the discussion on the integration of distributed energy sources, the integration of electric vehicles and their two-way communication, the types of energy storage systems and their tabular comparison with an emphasis on the sustainable use of energy and the reduction of environmental impacts are other goals of the authors in this research. This paper explores the application of smart technologies in resource management, focusing on waste handling, street lighting, building heating, ventilation, and air conditioning (HVAC) systems, and water consumption. Traditional methods for these aspects often lack efficiency and sustainability. The paper proposes solutions utilizing Artificial Intelligence (AI), IoT, and sensor networks to create intelligent systems. Conclusively, this work offers a comprehensive perspective on overcoming the operational and security challenges essential to realizing sustainable, efficient, and safe smart cities.

The energy hub (EH) concept is a key component in modern energy systems that integrates multiple energy resources and carriers to meet different energy demands. This paper investigates an EH composed of conventional generation units, renewable energy resources (RERs), energy storage systems (ESSs), and heating and cooling assets. It tries to optimize EH owner profits while minimizing various costs through mathematical programming. Additionally, it addresses uncertainty management in EH arising from RERs outputs, utilizing a chance constraint - information gap decision theory - robust optimization (CC-IGDT-RO) approach derived from optimization with uncertain data and feasibility robustness theorems. Furthermore, it introduces flexibility services as an alternative means to effectively address this uncertain energy management component. A comparative analysis with existing literature demonstrates the robustness and applicability of the proposed framework, which is 42% lower in the costs within conventional EHs, and providing 10% more flexibility in comparison with cases in review.

Every year a large amount of subsidized diesel fuel is delivered to farmers for irrigation purposes. In addition to low efficiency and high maintenance costs, diesel pumps increase environmental pollution and produce greenhouse gases. For this reason, in recent decades, the replacement of diesel pumps with electric pumps has been a priority for governments in most developing countries. Despite the many benefits of electrifying agricultural wells, providing the required demand for electric pumps has always been one of the main challenges facing grid operators. The development of renewable resources and distributed generation resources can be an effective strategy to provide economically justifiable solutions to supply the demand for agricultural wells and result in savings in fossil fuel consumption. Policymakers must have a clear understanding of different approaches regarding the electrification of irrigation systems and conceivable scenarios. In this paper, economic studies based on the enactments of the plan to supply electricity to Iran's agricultural wells are presented on a pilot scale. In this paper, a clustering of agricultural wells based on the fuzzy clustering method is presented. The purpose of using the fuzzy clustering method is to present the best classification of wells in terms of dispersion rate and select the best demand-supply scenario (of the four proposed scenarios) based on the analysis of the economic indices. In the final section of the paper, the analysis of the results of the proposed method is discussed.

One of the most essential development factors in any country is the quality of electricity supply and distribution. Energy consumers seek electricity supply at a very high safety level. Considering the sensitivity of electronic devices and the dependence of most activities on electricity, providing sustainable energy in urban systems is critical. Unscheduled shutdowns are the leading cause of disruption in the continuity of electricity supply and reduce the quality of power delivered to customers. Operational risks are potential events that result in unplanned outages in the network. In the current research, the fuzzy cognitive map (FCM) method has been used to investigate the relationships between risks and to reach a comprehensive solution for the simultaneous control and management of several risks. Accordingly, extracting the effect of operational risks on each other and how to draw them in the form of a FCM is analyzed and represented. The results emphasize that adverse weather conditions are the most influential with the highest degree of output and equipment failure is the most influential with the highest degree of input in operational risks. The highest value of the sum of input and output degrees (centrality) is the breakdown in the transformer, which has the highest value. The analysis of managerial and practical perspectives shows that the operators, by focusing on forecasting weather conditions and retrofitting network structures and technical management of transformers, reach a convergent and sustainable solution to manage operational risks and ultimately reduce unplanned shutdowns.

Regarding the high wind potential in the Iranian shores, the best ‎place for installing wind turbines ‎is a location away from the beach.In this research, a sample of an offshore wind turbine with a jacketed ‎type foundation equipped with a damper was considered. It is ‎necessary to use a damper system to reduce wind and wave ‎vibrations and ‎lower damage. In this regard, the Tuned Liquid Column ‎Gas Damper (TLCGD) system which is ‎one of the most effective ‎dampers were used. The best places to install this item in the three shores of Iran were ‎examined by considering the data of 26 oceanographic stations. The equations of hydrodynamic and ‎aerodynamic forces acting on ‎this five degrees of freedom sample were ‎obtained, and expanded in MATLAB with the effects of 10,000 wave and wind data of ‎selected points. Equatin was ‎solved by the ode45 ‎function. The main objective of this study is to find suitable locations ‎‎with minimum fluid movement in TLCGD (cm) and the highest power ‎generation capacity ‎‎(W).‎ Then, the range of each area was located using the average results of ‎each point and ArcGIS software. Using the theory of Multi Objective Optimization, the optimum points was extracted.‎ The results ‎showed that for the Caspian Sea, Point (‎37.0 N‎, 53.2 E‎) ‎and the surrounding areas in the east and Point (‎38.0 N‎, ‎49.4 E‎) and ‎‎26 in the northwest were suitable for installing turbines.