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This paper presents the solution of Markov chain reliability models with a large state-space. To specify a system reliability model, we use our previously proposed methodology, which is based on the Stochastic Automata Networks formalism. We model parts of the system by arrowhead matrices with functional transition rates. As a result, the infinitesimal generator matrix of the reliability model has a distinctive structure. In this paper, we demonstrate that a block Gauss–Seidel method can be applied very efficiently to such a structure. The application of the proposed methodology is illustrated by an example of a standard 3/2 substation configuration. Even though its Markov chain reliability model has almost two million states, its steady-state probabilities can be estimated in just a few seconds of CPU time. [ABSTRACT FROM AUTHOR]

In this paper, stochastic automata networks (SANs) formalism to model reliability of power systems substations is applied. The proposed strategy allows reducing the size of state space of Markov chain model and simplifying system specification. Two case studies of standard configurations of substations are considered in detail. SAN models with different assumptions were created. SAN approach is compared with exact reliability calculation by using a minimal path set method. Modeling results showed that total independence of automata can be assumed for relatively small power systems substations with reliable equipment. In this case, the implementation of Markov chain model by a using SAN method is a relatively easy task. [ABSTRACT FROM AUTHOR]

The article proposes a multi-project Baltic States – Continental Europe Synchronous Interconnection Scenario for 2014–2027, with the insight to the former development of the Baltic Power System and a short listing of synchronous interconnection precedents in Europe. The study identifies and discusses the major operational challenges for the Baltic Power System in synchronously connecting the Continental European Network (CEN) via the recently commissioned Polish–Lithuanian tie LitPol Link1 and the projected LitPol Link2. The HVDC converter stations on asynchronous ties with Russia, Belarus and Nordic systems are recommended for the exchange of frequency containment and restoration reserves, notably in the DC-supported island operation condition of the Baltic Power System. [ABSTRACT FROM AUTHOR]

The paper presents a novel method for statistical quantification of wind power variation based on a new concept of homogeneous generation periods (HGPs). It starts with the state-of-the-art review of approaches addressing the quantification of wind power variation. The suggested method is based on identification of (a) wind generation gradients (positive, negative, insignificant and ineligible) for the time steps and (b) HGPs (increasing, decreasing, constant and null-generation). In result, the method provides a statistical evaluation on variation of wind generation process in observation period in terms of statistical characteristics of HGPs. The validation of method is performed on a numerical set-up representing Lithuanian wind power cluster in a windy 13-day period. The validation results point to the effectiveness of the suggested method for the ex-post quantification of wind generation variation in a short-term time span. [ABSTRACT FROM AUTHOR]

The rapid development of renewable energy sources and electricity storage technologies is further driving the change and evolution of traditional energy systems. The aim is to interconnect the different electricity systems between and within countries to ensure greater reliability and flexibility. However, challenges are faced in reaching it, such as the power grid complexity, the system control, voltage fluctuations due to the reverse power flow, equipment overloads, resonance, incorrect island setting, and the diversity of user needs. The electricity grid digitalization in the market also requires the installation of smart devices to enable real-time information exchange between the generator and the user. Inverter-based distributed generation (DG) may be used to control the grid voltage. Smart PV inverters have the capability to supply both inductive and capacitive reactive power to control the voltage at the point of interconnection with the grid, and only technical parameters of smart PV inverters limit this capability. Reactive power control is related to ensuring the quality of voltage in the electricity distribution network and compensating reactive power flows, which is a technical–economic aspect. The goal of this research is to present an analysis of controllers that supply reactive power to the electrical grid via PV systems. This research analyzes recent research on local, centralized, distributed, and decentralized voltage control models in distribution networks. The article compares various approaches and highlights their advantages and disadvantages. The voltage control strategies and methodologies mentioned in the article can serve as a theoretical foundation and provide practical benefits for PV system development in distribution networks. The results of the research show that the local voltage control approach, as well as linear and intelligent controllers, has great potential. [ABSTRACT FROM AUTHOR]

As the number of available renewable energy sources has increased annually, there has been a corresponding rise in the levels of pollution created by traditional electricity generation, ultimately contributing to breaking down the stability of the electrical system at large. Therefore, there is an increasing need to integrate the use of nonpolluting electricity sources, such as pumped storage hydropower plants (PSHP), to ensure the stability of the power system and to maintain the frequency of the system from year-to-year. This paper addresses the issue of PSHP being unsuitable for providing Frequency Containment Reserve (FCR) services and proposes real measurements of the aggregation approach to obtain different data arrays. Based on this, the proposed methodology is orientated toward obtaining transfer functions that were developed using the parametric identification models, and the efficiency of these functions was thoroughly investigated. The proposed transfer function in this paper, in combination with battery energy storage system (BESS) technologies, would allow PSHP technologies to occupy a space in the ancillary services market by providing FCR, Frequency Restoration Reserve (FRR), and Replacement Reserve (RR) services. The performance of the function activated in the BESS is positively validated using the Simulink modeling environment. [ABSTRACT FROM AUTHOR]

The traditional unidirectional, passive distribution power grids are rapidly developing into bidirectional, interactive, multi-coordinated smart grids that cover distributed power generation along with advanced information communications and electronic power technologies. To better integrate the use of renewable energy resources into the grid, to improve the voltage stability of distribution grids, to improve the grid protection and to reduce harmonics, one needs to select and control devices with adjustable reactive power (capacitor batteries, transformers, and reactors) and provide certain solutions so that the photovoltaic (PV) converters maintain due to voltage. Conventional compensation methods are no longer appropriate, thus developing measures are necessary that would ensure local reactive and harmonic compensation in case an energy quality problem happens in the low voltage distribution grid. Compared to the centralized methods, artificial intelligence (heuristic) methods are able to distribute computing and communication tasks among control devices. [ABSTRACT FROM AUTHOR]

It is essential for the electricity sector to analyze and determine the distribution capacity throughput and apply new methods aimed at increasing the capacity of the transmission system. Consequently, the transition to modern electricity networks is two-sided, i.e., involving technological and social modifications. The demand response (DR) redistributes consumption away from peak times when grid load and costs are the highest. It incentivizes customers to use electricity when supply is high and inexpensive due to various market mechanisms. The present DR policy proposals stress the importance of fostering behavioral change through competitive pricing and customer participation in reducing carbon emissions and implementing smart energy solutions (including monitoring tools, such as smart meters and applications). The internet of things (IoT) has been applied to ensure adaptive monitoring of energy consumption and cost-effective and adequate demand-side management (DSM). The article is based on the research of the most recent sources of DR implementation methods applied at the power distribution level. It explains the main concepts, classifications, and entities implementing DSM programs, and suggests new visions and prospects for DSM and DR. Moreover, it discusses the application of blockchain technology potential for the internet of energy. [ABSTRACT FROM AUTHOR]

Abstract: In this article we present a short-term (short-transient) dynamic stability assessment methodology for generators of a power system at characteristic/relevant operation modes. The suggested methodology combines a classical simulation methodology and Bayesian approach, the latter being widely applied in a variety of areas nowadays. The proposed methodology reduced the number of calculations and the respective cut in computational time, enabled obtaining quite precise results in case of the lack of real measurements. The idea was to replace the major portion of calculations with a mathematical model of the power system by estimation procedure. As for the specification of its features, the methodology takes into account characteristic operation modes of the system in annual cycle and uses dependency functions of the generators relating dynamic stability reference characteristics with the estimated characteristics. The estimated dynamic stability characteristics of the same generators were found with the Bayesian-approach-based estimation model which was trained by data sequence of true points from the reference characteristics. The performance of the methodology was examined by testing the dynamic stability of the generators of the power system and statistically analysing the test results. In summary, it can be reasonably argued that the best estimates were produced when the estimation model was trained with one dynamic stability reference characteristic and three true points of the characteristic for the considered generator. The verification of the suggested methodology for the aforementioned test system revealed that it reduces the computational time by several times, in comparison to “classical” methodology (based only on mathematical modelling of the power system). [Copyright &y& Elsevier]