This article outlines a procedure for loss allocation in both radial and meshed distribution networks with distributed generation that could be regulated in various ways. The method is analytically developed based on the theory of electrical circuits combined with game theory based on Aumann-Shapley, which guarantees both the electrical principles and the fair axioms of game theory. The proposed method obtains unitary participation coefficients for each network user based on the currents demanded/injected by each user and the network topology. The proposed allocation method based on Aumann-Shapley has been compared with other traditional allocation methods, is adaptable to distribution networks, and shows great potential and ease of implementation. Moreover, it can be applied to any kind of distribution network (radial or meshed) with distributed energy resources.

This paper introduces an innovative approach to address the distribution network reconfiguration (DNR) challenge, aiming to reduce power loss through an advanced hyperbolic tangent particle swarm optimization (HT-PSO) method. This approach is distinguished by the adoption of a novel hyperbolic tangent function, which effectively limits the rate of change values, offering a significant improvement over traditional sigmoid function-based methods. A key feature of this new approach is the integration of a tunable parameter, $\delta$, into the HT-PSO, enhancing the curve’s adaptability. The careful optimization of $\delta$ ensures superior control over the rate of change across the entire operational range. This enhanced control mechanism substantially improves the efficiency of the search and convergence processes in DNR. Comparative simulations conducted on 33- and 94-bus systems show an improvement in convergence, demonstrating a more exhaustive exploration of the search space than existing methods documented in the literature based on PSO and variations where functions are proposed for the rate of change of values.

Abstract— This paper presents a method for optimal allocation of energy storage devices in electric power distribution systems with the inclusion of renewable sources, also determining the optimal number to be allocated and the battery optimal cycle of loading and unloading. The method observes the constraints of the electrical network, such as the voltage profile within preset limits, as well as the intermittency of renewable sources based on wind and solar energy. The proposed method was applied to a hypothetical 5-bus network and the IEEE 24-bus distribution network. The results show that the proposed method can extend battery life and reduce the cost of purchasing electric energy.

This paper presents a method for multi-period optimization of natural gas and electric power systems incorporating gas-fired power plants to analyze the impact of the interdependence between those commodities, in terms of cost and energy supply. The proposed method considers electricity network constraints, such as voltage profile, electrical losses, and limits of the transmission lines, as well as the technical restrictions on the gas network, such as the diameter, length, pressure, and limits for those variables. The proposed method was applied to a 12-bus electric network and a 7-node gas network, and several interdependencies between the electricity and the natural gas system network can be observed. The results show how the restrictions cause the behavior of the gas-fired power plants—in a low demand stage, it is restricted even when the gas-fired power generation prices are below the hydraulic generation prices, while in scenarios of higher demand, saturated cargo flows are observed, causing bus bar prices to be affected with higher operating costs. In this sense, the results of the variation in bus bar prices show little price stability in some bus bars in different stages, due to the behavior of the generation supply that is forced to operate by system restrictions.

This paper investigates the impact of natural gas pipeline congestion on the integrated gas–electricity market in Peru, focusing on short-term market dynamics. By simulating congestion by reducing the primary natural gas pipeline’s capacity, the study reveals significant patterns in production costs and load flows within the electrical network. The research highlights the critical interdependencies between natural gas and electricity systems, emphasizing how constraints in one network can directly affect the other. The findings underscore the importance of coordinated management of these interconnected systems to optimize economic dispatch and ensure the reliability of both gas and electricity grids. The study also proposes strategic public policy interventions to mitigate the financial and physical impacts of pipeline congestion, contributing to more efficient and resilient energy market operations.