The decentralized feed-ins from distributed energy resources (DER) represent a significant change in the manner in which the power grid is used. If this leads to high loads on electrical equipment, its aging can be accelerated. This applies in particular with regard to the thermal aging of older generations of power cables, namely paper insulated lead covered (PILC) cables. This type of power cable can still be found frequently in medium voltage (MV) networks. If aging of these cables is significantly accelerated in the presence of DER, distribution system operators (DSO) could face unplanned premature cable failures and a high replacement demand and costs. Therefore, this paper investigates the thermal aging of PILC cables in a MV distribution network benchmark for different load scenarios, using standardized load profiles and representative expansion scenarios for wind power and photovoltaics plants in particularly affected network areas in Germany. A main objective of this paper is to present a methodology for estimating the thermal degradation of PILC cables. An approach is used to draw simplified conclusions from the loading of cables to their conductor or insulation temperature. For this purpose, mainly Joule losses are considered. In addition, thermal time constants are used for the heating and cooling processes. Based on the insulation temperature, thermal aging is determined using the Arrhenius law or the Montsinger rule. However, it is important to note that there is an urgent need for research on reference data in this area. For this reason, the results of the lifetime estimation presented in this paper should only be considered as an approximation if the selected reference data from the literature for the aging model are actually applicable. The lifetime assessment is performed for a highly utilized line segment of the network benchmark. Accordingly, extreme values are examined. Different operational control strategies of DSO to limit cable utilization are investigated. The results show that the expansion of DER can lead to a short but high cable utilization, although the average utilization does not increase or increases only slightly. This can lead to significantly lower cable lifetimes. The possible influence of these temporarily high loads is shown by comparing the resulting cable lifetime with previous situations without DER. It is also shown that DSO could already reduce excessive aging of PILC cables by preventing overloads in a few hours of a year. In addition to these specific results, general findings on the network load due to the influence of DER are obtained, which are of interest for congestion management.

Our current energy landscape is ever-changing, resulting from the ongoing energy transition and introducing a massive expansion of volatile generation feed-in and energy consumption (due to electrification). In turn, the energy supply’s requirements are also being affected. In this context, the energy system’s optimisation across all sectors will only grow in significance, especially in terms of future developments. Facilitating and researching methods for carrying out the aforementioned optimisation creates new demands pertaining to load flow simulation programmes. The volatility of specific participants and their interactions within existing power grids must be evaluated, wherefore the consideration of a large number of time steps but also dynamic simulations becomes inevitable. Carrying out such simulations is possible but very time-consuming. This article compared a variety of conventional load flow simulations such as the current iteration and Newton–Raphson methods and also introduced a novel, state-space based calculation approach, which boasts the potential of structurally increasing simulation speeds. Each of the method’s underlying principles, requirements, and mathematical correlations will be discussed and explained. In the second part of this article, the most important state-space equivalent circuit models of critical operating equipment are introduced. These models are essential for carrying out load flow simulation tests for an exemplary test network but could also be used for dynamic purposes. The previously showcased load flow methods were applied to a test network, with which the simulation methods should be validated. The results show that the state-space simulation has high accuracy while also being very flexible. All in all, the load flow calculation in state-space offers many advantages that could be an interesting alternative to conventional load flow simulations, especially for the analysis of complex, time series-based, and intelligently controlled smart grid power systems. In this context, the direct application of system theoretical methods for stability calculations, controllability, and dynamic system studies is to be mentioned. Optimisation options regarding the processes within the state-space calculation software still promise further significant increases in performance.

This paper presents a new method that should make it possible to determine the sensitivity of uncontrolled electrical power grids with only a modest amount of effort. Unlike most of the methods described in the literature, this method is based on an implicit description of the electrical power grid in the state space, in which the system matrices are set up using mesh equations based on a complete tree. In this case, the sensitivity matrix is not derived from the Jacobian matrix, but from the weighted inverse of the impedance matrix. It will be shown that this makes it possible to determine the sensitivity of the network independently of the operating point, under the assumption that the impedances of the network remain constant.

A novel cluster-based procedure and control principle is presented, which allows a fundamental reduction of the transmitted power down to the economic and technical minimum. The resulting, locally restricted energy use is achieved by a cluster-based approach to central assets and by a hierarchically accumulated monetary motivation of participants within the energy system. Local incentives are used to motivate grid-serving behavior, which result from the interaction of instantaneous power flow measurements and the ageing behavior, based on an asset management analysis. By accumulating the local incentives, it is also possible to influence energy flows among several clusters. This can be done with a data exchange which is reduced to a minimum.