Electricity

Wide-Area Power System Stabilizers (WAPSSs) are damping controllers used in power systems that employ data from Phasor Measurement Units (PMUs). WAPSSs are capable of providing high damping rates for the low-frequency oscillation modes, especially the inter-area modes. Oscillation modes can destabilize power systems if they are not correctly identified and adequately damped. However, WAPSS communication channels may be subject to failures or cyber-attacks that affect their proper operation and may even cause system instability. This research proposes a method based on an optimization model for the design of a WAPSS robust to multiple permanent communication failures. The results of applications of the proposed method in the IEEE 68-bus system show the ability of the WAPSS design to be robust to a possible number of permanent communication failures. Above this value, the combinations of failures and processing time are high and they make it difficult to obtain high damping rates for the closed-loop control system. The application and comparison of different optimization techniques are valid and showed a superior performance of the Grey Wolf Optimizer in solving the optimization problem. Full article

Enhancing electric vehicle infrastructure by forecasting the availability of charging stations can boost the attractiveness of electric vehicles. The transportation sector plays a crucial role in battling climate change. The majority of available prediction algorithms either achieve poor accuracy or predict the availability at certain points in time in the future. Both of these situations are not ideal and may potentially hinder the model’s applicability to real-world situations. This paper provides a new model for estimating the charging duration of charging events in real time, which may be used to estimate the waiting time of users at fully occupied charging stations. First, the prediction is made using the random forest regressor (RF), and then the prediction is enhanced utilizing the findings of the RF model and real-time information of the currently occurring charging events. We compare the proposed method with the RF model, which is the approach’s foundational model, and the best-performing prediction model of the light gradient boosting machine (LightGBM). Here, we make use of historical information of charging events gathered from 2079 charging stations across Germany’s 4602 fast-charging connectors. To reduce data bias, we specifically simulate prediction requests for 30% of the charging events with various characteristics that were not trained with the model. Overall, the suggested method performs better than both the RF and the LightGBM. In addition, the model’s structure is adaptable and can incorporate real-time information on charging events. Full article

In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia. Full article

We propose a method for the fault passage indication of earth faults in resonant-earthed networks, based on phase current measurements alone. This is particularly relevant for electricity distribution systems at medium-voltage levels. The method is based on the relative magnitudes of the phasor changes in the phase currents due to the fault. It is tested for various network types and operation configurations by simulating the network in pscad and using the simulated currents as the input for an implementation of the method in matlab. In over-compensated networks, the method shows reliable detection of the fault passage, with good selectivity and sensitivity for both homogeneous and mixed (cable and overhead line) feeders. However, for the less common under-compensated systems, it has limitations that are described further in this study. The method has good potential for being cost effective since it requires only current measurements, from a single location, at a moderate sampling rate. Full article

This paper presents a method for integrating industrial consumers owning compensation systems as alternative reactive power sources into grid operating processes. In remuneration, they receive a market-based provision of reactive power. The aim is to analyze the potential of reactive power compensation systems of industrial companies connected to medium-voltage (10 kV–30 kV) AC grids in order to increase the reactive power ability of distribution grids. Measurement methods and reactive power potential results of six industrial companies are presented to characterize the amount and temporal availability of their reactive power potential. The presented approach for using the decentralized reactive power potential is a centralized reactive power control method and is based on optimal power flow (OPF) calculations. An optimization algorithm based on linear programming is used to coordinate a reactive power retrieval tuned to the actual demand. The influencing quantities are the current grid status (voltage and load flow capacity reserves at grid nodes and power lines) and the current reactive power potential of the reactive power sources. The compensation impact of six measured industrial companies on an exemplary medium-voltage grid is shown by an application example. Full article

The increase in the average global temperature is a consequence of high greenhouse gas emissions. Therefore, using alternative energy carriers that can replace fossil fuels, especially for automotive applications, is of high importance. Introducing more electronics into an automotive battery pack provides more precise control and increases the available energy from the pack. Battery-integrated modular multilevel converters (BI-MMCs) have high efficiency, improved controllability, and better fault isolation capability. However, integrating the battery and inverter influences the maximum DC charging power. Therefore, the DC charging capabilities of 5 3-phase BI-MMCs for a 40-ton commercial vehicle designed for a maximum tractive power of 400 kW was investigated. Two continuous DC charging scenarios are considered for two cases: the first considers the total number of submodules during traction, and the second increases the total number of submodules to ensure a maximum DC charging voltage of 1250 V. The investigation shows that both DC charging scenarios have similar maximum power between 1 and 3 MW. Altering the number of submodules increases the maximum DC charging power at the cost of increased losses. Full article

Transportation electrification can significantly reduce carbon footprint and accelerate the modernization of aging electric infrastructure. In the U.S., the growing adoption of electric vehicles (EVs) will significantly impact the electrical grid and associated greenhouse gas emissions, but with significant differences between the balancing regions due to the diverse characteristics of their electrical grids. This work assesses the impacts associated with the increasing penetration of EVs in the U.S., considering the characteristics of the grid in the different regions, in order to discuss the needed strategies to maximize the future decarbonization benefits. The assessment considers the variation in generation mix profiles during the day in each region, as well as different charging profiles associated with home, work, and public charging. The results show that more ambitious policies for the increasing share of carbon-free generation in the regions with the highest emissions are needed, emphasizing incentives for the use of work and public charging, and ensuring effective management of the charging flexibility. Full article

This paper presents a live field experience of creating an isolated microgrid for the Expoelectric fair during 2018 and 2019. The islanded microgrid comprises a Master Inverter with grid-forming capabilities and fault management. The Master Inverter and stationary batteries, and EVs with V2G capabilities provide storage. A PV generation system supplies the microgrid. The loads are the fair booths, mainly lighting and chargers for personal mobility vehicles. All the equipment used in the experimental microgrid is from different manufacturers. The operation and control of the islanded microgrid are based on the VDE-AR-N-4105 standard. The paper also presents the operation of the Master Inverter during faults. The live field experience shows that the proposed operation method is valid for operating different converters from different manufacturers without needing any communication layer between them. The experimental results also show that faults can be handled correctly by the Master Inverter to operate the entire microgrid safely. In conclusion, islanded microgrids based on power electronics are feasible to replace diesel generators in faires, conventions or temporary events. Full article

This paper presents a novel tool for electricity planning, based on an improvement of MuSIASEM (Multiscale Integrated Analysis of the Societal and Ecological Metabolism) by incorporating a new regional analysis of the electricity metabolism across levels. An analysis of Mexico illustrates this toolkit and shows that the industry sector has economic energy intensity (EEI) with 40.3 MWh/MMXN reaching a higher value than the commerce and services sector with 0.84 MWh/MMXN. Regarding the economic labor productivity (ELP) indicator (AV/h), the industrial sector with 208.5 TMXN/Kh reached a higher value than the commercial and services sector with 114.3 TMXN/Kh. Regarding the exosomatic metabolic rate (EMR), the household sector obtained 59.3 KWh/Kh, whereas the economic sector reached 2486.4 KWh/Kh. Disaggregation of the EMR indicator into economic sectors shows that the industrial sector reached 8.4 KWh/Kh and the commercial and services sector reached 0.10 KWh/Kh. The lack of complete data for the agricultural sector does not allow us to calculate EEI, ELP, and EMR indicators accurately. This innovative approach is useful for governance because it helps us to understand and reduce asymmetries across regions in terms of electricity consumption, resulting in more social equality and a better economic equilibrium across sectors and regions. Full article

This paper presents a stochastic approach to assessing the hosting capacity for solar PV. The method is part of the optimal techniques for the integration of renewables. There are two types of uncertainties, namely aleatory and epistemic uncertainties. The epistemic and aleatory uncertainties influence distribution networks’ hosting capacity differently. The combination of the two uncertainties influences the planning of distribution networks. The study introduces and considers the epistemic probability distribution function (PDF). DSO does take levels of risk for a parameter violation when planning. Epistemic PDF is a range of values of the planning risk margin for quantifying the hosting capacity. The planning risk acknowledges that overvoltages may occur at weaker conceivable locations in a distribution network. In the paper, it has been shown that the number of customers who will be able to connect solar PV in future is influenced by the DSO’s planning risk margin. The DSO can be stricter or less strict in planning risk margin. It has been concluded that fewer customers can connect solar PV to a distribution network when a DSO takes a stricter planning risk. Alternatively, more customers can connect solar PV units for a less strict planning risk. How stricter or less strict the DSO is with the planning risk margin determines the investment needed for mitigation measures. The mitigation measures in the future will lead to not exceeding the overvoltage limit when solar PV is connected to the weaker conceivable points of the distribution network. Full article

The actual research in terms of energy focuses drastically on the use of green energy resources. Hydropower systems have been the most known green sources for years. However, the hydropower systems, which are seasonal and most exploited, do not cover the speed of increasing daily demand. The injection of solar power could be a supporting alternative, but it is only in daylight, weather dependent and intermittent. Therefore, a storage system is required. The batteries are the quick recourse. Not only the energy sector, but also the transport systems are not left behind; they are striving to turn green. Therefore, they are turning to electric vehicles (EVs) and electric moto-bicycles (EMBs). On the other hand, this option tends to be a sharply increasing demand that can be a burden to the grid, i.e., the increase in the EVs and EMBs implies increases in power demand, grid components and pressure on the grid. Fortunately, the EVs use batteries to store energy for their use. Therefore, the EVs are the power storage system, they become part of the power management system and they can save the power surplus. With the injection of PV solar power, there is no need for an extra storage system, as the EVs are charged from the grid and store the solar energy that can be used later after sunset. The bi-directional off-board charger is a solution as it allows the grid to charge the vehicle (G2V) and the vehicle to send power back to grid (V2G). The inclusion of EVs in power management introduces the concept of vehicle-to-vehicle (V2V) when one EV can charge another, and the vehicle-to-load (V2X) where the EV can supply power to EMBs or any load. The V2G, G2V, V2X, the inclusion on solar energy to the grid and the behavior of the grid in that scenario will be illustrated in this paper. Full article

The operation of electrical networks, microgrids, or heterogeneous battery systems, especially the dispatch of single units within the system, requires sophisticated power flow control strategies. If objectives such as efficiency are demanded for the operation of the energy system, typical control strategies lack the ability to verify the optimality of the operation. Dynamic programming is a widely used method for determining the global optima of trajectory problems. In the context of energy systems and power flow optimization, it is restricted to applications with a low number of states and decisions. The reason for this is the rapid growth of computational effort with increasing dimensionality of the state and decision space. The approach of iterative dynamic programming (iDP) makes dynamic programming applicable to the planning and benchmarking of complex power flow optimization problems. To illustrate this, a heterogeneous battery energy storage system is introduced for which the iDP optimizes the power split at the point of common coupling to minimize the total cumulative loss of energy. The method can be adopted for a broad range of energy systems such as microgrids, utility grids, or electric vehicles. The applicability is limited only by the computation time, which depends on the model complexity and the length of the time series. To verify the functionality of the iterative dynamic programming, its results are directly compared to those of the standard dynamic programming. The total computation time can be reduced by 98% in the tested scenario. As relevant use cases, static and dynamic methods of power sharing are validated and benchmarked. The iDP offers a novel and computationally efficient method for the design and validation of power flow control strategies. Full article

With the evolution of electromobility and heat pumps in urban areas, distribution system operators find themselves facing new challenges in reinforcing their grids. With this evolution, the power demand is developing rapidly and grid reinforcement is urgently needed. The electromobility and heat pump loads are introduced by giving the assumed development scenarios in Germany and their corresponding nominal power assumptions. Furthermore, a method for load modeling in grid planning is explained. Subsequently, several grid planning approaches are presented while dividing them into conventional and innovative planning strategies. Among the investigated innovative planning strategies are three variants of load management that regulate different load types. By analyzing several urban medium voltage grids, this contribution deduces a solid basis for distribution system operators in the form of planning guidelines. The implemented grid planning method leading to the planning guidelines is presented in detail along the contribution. Full article

Accurate electricity demand forecasting is vital to the development and evolution of smart grids as well as the reinforcement of demand side management strategies in the energy sector. Since this forecasting task requires the efficient processing of load profiles extracted from smart meters for large sets of clients, the challenges of high dimensionality often lead to the adoption of cluster-based aggregation strategies, resulting in scalable estimation models that operate on aggregate times series formed by client groups that share similar load characteristics. However, it is evident that the clustered time series exhibit different patterns that may not be processed efficiently by a single estimator or a fixed hybrid structure. Therefore, ensemble learning methods could provide an additional layer of model fusion, enabling the resulting estimator to adapt to the input series and yield better performance. In this work, we propose an adaptive ensemble member selection approach for stacking and voting regressors in the cluster-based aggregate forecasting framework that focuses on the examination of forecasting performance on peak and non-peak observations for the development of structurally flexible estimators for each cluster. The resulting ensemble models yield better overall performance when compared to the standalone estimators and our experiments indicate that member selection strategies focusing on the influence of non-peak performance lead to more performant ensemble models in this framework. Full article

This paper presents the application of heuristic methods in conjunction with graph theory in the optimal routing and sizing of underground distribution networks in georeferenced (GIS) scenarios, which are modeled and simulated in the advanced engineering tool CYMDIST. The tool allows the deployment of underground networks to facilitate the design, planning, and implementation of networks, taking into consideration distribution company regulations, thus allowing overview and future planning in the growth of distribution systems. Further, this method is modeled in real georeferenced scenarios, where the coverage of the electric service to all users connected to the network is guaranteed according to population density and energy demand while minimizing the number of distribution transformers used. The applied method considers the location of transformer chambers, the capacity and coverage of the distribution transformers, and the voltage drops over the line section, which should not exceed 5% of the nominal value as described in the ANSI C84.1 standard. Consequently, to verify the efficiency of the applied method, the limitations and restrictions of the mathematical model are considered, as well as the characteristics of the georeferenced system and a comparison with different research studies that address the subject presented here. In addition, supply coverage is guaranteed to be 100%. Full article

The increased complexity of the transmission grid can endanger the operational security of the grid. Operational risk assessment, a stochastic tool, helps to enhance security. Contingency analysis and its impact quantification are the main constituents of operational risk assessment. In this study, different graphical methods are proposed to visualize operational risk contingency-based detailed results: heat-map and risk-based contingency chart. Through the heat-map, the system operator can determine which contingencies contribute most to the operational risk and would therefore be the most threatening contingencies for operational security of the grid. The “risk-based contingency chart” allows the system operator to analyze contingency cases from the probability and impact aspect in one chart. Both tools may be used in the control room for improved operational planning. In this study of contingency analysis and various types of network studies of severity factor quantification, the IEEE 39-Bus sample network is used in Power-Factory to analyze the contingencies behavior under different operational scenarios. Full article

With the increasing number of electric vehicles, the required charging infrastructure is increasing rapidly. The lack of historical data for the charging infrastructure compromises a challenge for distribution system operators to forecast the corresponding increase in the load demand. This challenge is characterised by two main uncertainties, namely, the charging power of the charging infrastructure and its location. Expectedly, the charging infrastructure is going to include varying charging powers and is going to be installed country-wide in different area types. Hence, this contribution sets to tackle these two uncertainties by developing demand factors for the charging infrastructure according to the area type. In order to develop the demand factors, a stochastic simulation tool for the charging profiles has been run for a simulation period of 5200 weeks (100 years) for six main charging powers and seven area types for up to 500 charging points. Thus, compromising a total of over 2.1 million simulated charging profiles. The resulting demand factor curves cover the charging powers between 3.7 kW and 350 kW with 1 kW steps for a total of 348 kW steps. Furthermore, they differ according to seven area types ranging from an urban metropolis to a rural village and are developed for up to 500 charging points. Consequently, the demand factor curves serve as a base to be used for the strategic grid planning of distribution power grids while taking the future development of the charging infrastructure into account. Full article

After they reached the end of their useful EV life, lithium-ion batteries are still satisfactory for second life (SL) energy storage applications. However, the spread in their SL cell capacities may be much wider than in the EV, and this raises a question as to what type of cell voltage equalizer (EQU) should be used. Most users plan to retain the same passive EQU (PEQ) from the EV, but this means the battery capacity will be the same as the worst cell in the battery, just as it was in the EV. Unfortunately, the SL cell capacity spread may be much wider than it was in the EV, and if so, most of the cells will be under-utilized. This can be corrected by using an active EQU (AEQ) or a hybrid, such as the bilevel EQU (BEQ), to provide a capacity close to the cell average; but first, measured data is needed on the actual size of the cell capacity spread. To simplify and reduce the cost of these measurements, a new method is proposed that provides the capacities of the worst cell and the cell average. Full article