Digital twin technology offers significant potential for integrated energy systems (IES); however, existing approaches often lack an integrated framework that combines high-fidelity dynamic modeling of coupled multi-energy flows, distributed real-time control with safety guarantees, and proactive safety optimization. This article proposes an integrated optimization framework for energy systems tying together multi-energy flow coupled differential equations and distributed control strategies. By utilizing digital twin modeling, real-time safety regulation, and distributed control, remarkable performance improvements are achieved. Experimental results show that: (1) Compared with traditional centralized PID and distributed consensus approaches, the proposed coupled model improves the digital twin accuracy (ECA) to 95.4% ± 0.9%, representing an increase of 10.2 and 4.7 percentage points, respectively; (2) Compared with traditional approaches, the distributed control architecture decreases the convergence time (CT) to 2.1 ± 0.3 s; (3) The safety constraint violation rates (SVR) are controlled below 1.2% ± 0.7%; (4) Compared with traditional approaches, the multi-energy coordination optimizes the energy utilization efficiency (MEE) to 78.6% ± 1.9%, which is 13.5 percentage points more. Furthermore, theoretical analyses explain the synergistic optimization mechanism between coupled nonlinear terms and distributed consensus algorithms for stability and energy efficiency of the proposed system. This article offers an integrated “modeling-control-optimization” solution for integrated energy systems (IES) under high penetration renewable energy integration.

The paper is devoted to the study of technical and economic aspects of the development of power generation systems based on highly efficient high-power gas turbine technologies. Using cluster analysis tools, technological classes of existing high-power gas turbine equipment are identified and a methodology for selecting a promising level of gas turbine technology is developed, which allows justifying the choice of power plants to meet the energy system's need for electric power. The developed methodology provides a quantitative assessment of the economic efficiency of the identified technological classes of gas turbine plants, taking into account the observed and forecasted levels of fuel prices and the need of thermal power plants for electric power. Its application allows selecting the most promising gas turbine unit for scaling within the energy system, depending on the expected parameters of the external environment, determined by the market conditions of the functioning of the country's electric power sector and the adopted policy in the field of energy security.

This research quantitatively examines laminar hydrogen combustion under diverse pressure and strain conditions, employing comprehensive chemical kinetics in Cantera 3.0 with the H₂–O₂ and GRI-Mech 3.0 mechanisms. To learn more about flame speed, structure, and extinction behavior, we looked at four main flame configurations: freely propagating premixed, counterflow diffusion, premixed counterflow, and stagnation-point flames. The laminar flame speed of pure hydrogen was 310 cm/s, which means it burned very quickly because it spread out quickly. Hydrogen stayed stable up to a strain rate of 6.0 × 10⁵ s^–1 before it went out. The peak flame temperature dropped from 3600 K to 3000 K when the pressure rose from 1 bar to 100 bar. This shows that higher pressure makes things more stable but less heat is released. The innovation of this study resides in the integration of all principal flame configurations into a cohesive modeling framework, demonstrating that strain rate exerts a more significant impact on flame collapse than pressure. These results give us a baseline for designing efficient turbines, rocket combustors, and industrial heating systems that run on hydrogen.

The number of photovoltaic installations at residential level has risen to a marked extent; this has led to the development of microgrids powered mainly by photovoltaic. Motivated by these technologies, particularly with smart grids and IoT-enabled devices, this paper explores the first main stochastic control method—the dynamic programming principle—for enhancing flexibility from the demand side. This is brought about by adjusting the demand for electricity to better match generation from solar energy over the course of each hour, day or longer timeframe. The proposed method is applied to household appliances which exhibit spontaneous cycling, called thermostatically controlled loads, and can manage uncertainty related to weather by employing the technique of shaping filter for modeling ambient temperature as diffusion processes. A stochastic control problem has henceforth been established, and we have come through with a quite novel flexibility Markov model. Accordingly, in theory, the Hamilton–Jacobi–Bellman equation provides the only closed-form exact solutions. Even if the existence of solutions to Bellman’s equation is assured, it is often difficult to compute or characterize optimal controls from Bellman’s equation. Our substantial contribution in this work consists of a systematic method for approximating the exact solutions, inspired from the Taylor-Young formula of second-order in the continuous component of the state. Some of our computational experiences are provided in the context of behind-the-meter solar power with simulated scenarios: step function-like random functions and periodic functions. Monte-Carlo method is employed to study the impact of stochastic versus open-loop control. We believe that the comparative study reveals the breadth of flexibility control, namely, to convert the social benefit of mitigating the consequences of renewables uncertainty to a private benefit for users.

The paper is focused on the relevant risk and uncertainty evaluation of Slovak nuclear power policy. There are considerations about cost estimations for decommissioning and radioactive waste management in Slovakia. Results were incorporated into the actualization of Slovak national policy and program for spent nuclear fuel and radioactive waste management, which was sent for acceptance to the Government of Slovak Republic for the next 6 years period. The most significant risks in Slovakia are connected to build of deep geological repository, and too much consider new projects, which will probably influent human resources in decommissioning. Nevertheless, the nuclear optimism declared in political support of Slovak government should be balanced via real investment to improvement of nuclear infrastructure in Slovakia/Europe/world-wide including substantial investment in nuclear knowledge and human resources. The paper can be inspirative also for other countries with developed nuclear program as Slovak lessons learned.