Multi-energy systems (MESs) make it possible to satisfy consumer's energy demand using multiple coupled energy infrastructures, thus increasing the reliability of the energy supply compared to separate energy systems (SESs). To accurately and efficiently assess and improve the reliability of MESs, this paper proposes a MES reliability and vulnerability assessment method using energy hub (EH) model. The energy conversion, transmission and storage in MESs are compactly and linearly described by EH model, making reliability and vulnerability assessment of MESs tractable. Indices for MES vulnerability assessment are proposed to find the key components for improving MES reliability. Multi-parametric linear programming (MPLP) with a self-adaptive critical region set is proposed to reduce the computational burden caused by iteratively solving LP problems for a large number of samples during the assessment process. The results of a case study show that the proposed reliability and vulnerability assessment method is able to effectively evaluate the energy supply reliability of different energy sectors in MES as well as find the critical component of an MES from reliability perspective to support its planning. The proposed algorithm, i.e., MPLP with a self-adaptive critical region set, can improve the computational efficiency by an order of magnitude compared to the traditional LP method.

Most of the prosumers nowadays are constrained to trade only with the supplier under a flat tariff or dynamic time-of-use price signals. This paper models and discusses the cost-saving benefits of flex-ible prosumers as members of energy communities who can exchange electricity among peers and on the wholesale markets through a community manager. Authors propose a novel centralized post-process sharing method by introducing a two-stage mechanism which, unlike the existing methods, guarantees benefits for prosumers joining the energy community. The first stage assesses internal price calculation in three different methods: Bill Sharing Method Net (BSMN), Mid-Market Rate Net (MMRN), and Supply-Demand Ratio Net (SDRN). In their original form, prices are calculated in a single stage and the comprehensive analyses in the paper show that some members face increased cost. To solve this issue, the paper improves the methods by introducing the second stage in which the compensation methodology is defined for the distribution of savings which ensures that all community members gain benefits. Results investigate the value of inner technical flexibility of the prosumer (flexible preferences of the final consumer can reduce the cost from 3% up to 20 %). Moreover, incentives/penalties encourage the utilization of a flexible behavior to adjust the real-time consumption of prosumers’ appliances to a predefined day-ahead schedule. This type of pricing results in a lower amount of benefits sharing in the community (the reduction of 18-47% in MMRN and 49-114% in SDRN compared to existing pricing) which makes this incentives/penalties pricing more preferable. The pa-per concludes that prosumers with an excess PV production would not benefit from the internal energy ex-change in the community under BSMN due to free energy exchange between members.

With the development of technology and the decrease in prices, power systems are facing a strong growth in the number of end-users with photovoltaics (PVs), battery storages and electric vehicles (EVs). A penetration of low carbon (LC) technologies has an impact not only on the financial aspect, but also on parameters of the power quality (PQ) in the power system. Since most of end-users with renewable energy sources (RES) are connected to a low-voltage (LV) distribution network, there is a high number of single-phase loads and distributed generators (DG) that can cause unwanted effects in LV networks. According to standards, electric energy must be of a certain quality in order to avoid harmful effects on the power system, being both the network or the end-users equipment. One of the PQ parameters is the voltage unbalance. Voltage unbalance occurs in networks with the high share of single-phase loads and generators. Since most loads in households are connected to the only one phase, the voltage unbalance is constantly present in the network, even without LC technologies. Single-phase connected PVs, residential battery storages and EV charging stations can increase voltage unbalance in the system. This paper systematically analyzes a real-world LV network and different stages and shares of connected PVs, residential battery storages and EVs to different phases. The value of the voltage unbalance factor (VUF) is observed for one week in January and August in 10-min intervals. It is shown that connected systems can significantly increase the VUF and potentially cause negative impact on the equipment and the power system as a whole. In turn we analyze a three-phase connection of these new LC technologies and demonstrate how in all analyzed cases PQ values remain within boundaries defined by the EN 50160 and the IEC 61000-3-13.

The share of renewable energy sources interfaced to the bulk power system through power electronic devices is continuously increasing. As a result, the power systems of the future face challenges of stability and reduced inertia and, to maintain the stability of the low-inertia systems, various concepts of grid-forming converter control schemes have been introduced, which enable converters to behave similarly to traditional synchronous machines. As the research in this area is gaining on importance, the sheer amount of papers with models for different kinds of simulations and the complexity of control algorithms may be daunting for newcomers in this field to understand them and to start modeling such devices. Moreover, different control schemes are often erroneously used interchangeably which adds to the confusion. This papers aims to give a clear understanding of the above aspects by explaining details of modeling and initialization of grid-forming converter control schemes for power system fundamental frequency dynamic simulations (root-mean-square or RMS simulations) by using an example of a virtual synchronous machine (VSM). Starting from comparison of traditional systems and systems with a high share of converters and continuing with a functional overview of virtual inertia based converters in modern power systems, a step-by-step initialization of the static and dynamic model is given, focusing on RMS simulations. Finally, selected simulation examples are shown which illustrate main characteristics of virtual synchronous machines and their comparison to real synchronous machines. The presented dynamic model is made freely available in DIgSILENT PowerFactory format.

The success of the sustainable transformation of the energy sector, both in terms of planning and operation, relies on new entities, business models, and technologies. The shift from a relatively small number of centralized bulk producers and single direction energy flow to a decentralized multi-actor renewable system with a two-way flow of energy and multi-way flow of information needs to be accompanied by new technological solutions. Blockchain and other Distributed Ledger Technologies (DLT) represent a new technology for the energy sector, creating both opportunities and challenges for different aspects of energy systems, such as energy production, peer-to-peer (P2P) energy markets, green certificate registries, etc. Due to its decentralized nature and no need for intermediaries, DLT can facilitate energy democratization processes and decentralized energy production. In this paper, we present a systematic review of DLT principles, its theoretical background, and the most notable implementations, as well as an in-depth analysis of representative research projects and companies researching DLT use cases in the energy sector, taking into consideration technical aspects of DLT. We provide an insight into the benefits and limitations of DLT and identify technical challenges that need to be solved to enable widespread usage of DLT in energy systems. Additionally, we provide suggestions and guidelines for implementing DLT in different categories of use cases in the energy sector.

Shift of the power system generation from the fossil to the variable renewables prompted the system operators to search for new sources of flexibility, i.e., new reserve providers. With the introduction of electric vehicles, smart charging emerged as one of the promising solutions. However, electric vehicle aggregators face the uncertainty both on the reserve activation and the electric vehicle availability. These uncertainties can have a detrimental effect on both the aggregators’ profitability and users’ comfort. State-of-the art literature mostly neglects the reserve activation or it’s uncertainty. On top of that, they rarely model European markets which are different that those commonly addressed in the literature. This paper introduces a new method for modeling the reserve activation uncertainty, also termed as balancing energy procurement in the European context, based on the real historic data from the European power system. Three electric vehicle scheduling models were designed and tested: the deterministic, the stochastic and the robust. The results demonstrate that the current deterministic approaches inaccurately represent the activation uncertainty and that the proposed models that consider uncertainty, both the stochastic and the robust, substantially improve the results. Additionally, the sensitivity analysis for the robust model was performed and it demonstrates how a decision-maker can choose its level of conservativeness, portraying its risk-awareness.