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Battery Energy Storage (BES) technology has a major role to play in the upcoming energy transition, especially when it is coupled with variable Renewable Energy Sources (RES) facilities such as solar photovoltaic (PV) systems. On the other hand, financial compensation and legislative barriers currently rendering storage technology, prevent it to become a profitable and reliable solution for energy system integration. This paper outlines the primary targets of StoRES project towards developing a technical solution for PV systems in conjunction with BES. For this purpose, coupled PV-BES residential storage systems were developed in six countries, aiming at optimizing the utilization of storage towards achieving higher PV penetration. Another focus of this paper is the implementation of a community storage system which was installed in Cyprus. This is connected to the same distribution feeder supplying the local residential pilot systems in order to make a credible comparison between the centralized and distributed storage. 1 6

This study details a comprehensive storage-sizing methodology to allow a concentrating solar power plant to reliably integrate in the Cyprus power system which is classified as small and isolated. The need for providing a storage solution arises from the fact that large quantities of renewable energy sources may impose certain challenges on how isolated systems operate. Developing solutions to these challenges will enable higher penetrations of renewable generation sources on such systems and the future growth of renewable energy. To this extent, the methodology described in this study pertains to clear and explicit steps required to provide sufficient evidence toward the reliable integration of a large-scale solar-dependent plant through an appropriately sized battery energy storage system.

Currently, the deployment of PV technology in local distribution grids is usually done in an unplanned way without performing the required studies and this may induce power quality issues as penetration increases. The utilisation of accurate simulation models is therefore of great importance in an attempt to assess the real consequences of localised PV production. A generic PV system model for transient studies, the parameters of which can be tuned using transient data is proposed. The model is tuned and validated using transient data obtained from a detailed PV system circuit topology. The main novelty of this work lies in the fact that the proposed model can be tuned in order to represent accurately the dynamic behaviour of PV systems for both balanced and unbalanced conditions. Harmonics are also incorporated into the model to highlight its capability for use in complete power quality studies. The developed model is used along with the detailed PV system model to assess the voltage transient response of a distribution grid busbar. Finally, the transient behaviour of the distribution grid busbar having different grid impedance values is also evaluated utilising the proposed model. The expected and observed results are compared by means of the Theil Inequality coefficient depicting good agreement.

This review investigates the potential of photovoltaics in southern Europe and Middle East/North Africa in terms of PV status and policies/initiatives for PV market development in the region. In some Sunbelt countries, PV has become a competitive alternative for electricity generation resulting from a combination of high solar resource, decreasing PV system costs and high fuel prices. The PV levelized cost of electricity has fallen in some regions to 0.08 €/kWh whilst retail electricity prices are almost three times higher in some cases attesting to the ideal conditions in the region for PV uptake. In grid parity regions of south Europe, incentives such as feed-in-tariffs have served their purpose. Net metering and self-consumption are proving to be good solutions for driving effectively the PV market as evidenced for the case of Cyprus. In MENA countries, the renewables policy landscape, although still at an exploratory phase, is rapidly developing providing the backbone for a large number of new PV projects. This reflects the region's commitment to meet its ambitious national targets regarding PV. Overall, the timing for the whole region is excellent to achieve energy sustainability, once better policies are adopted and challenges regarding grid integration and reliability are addressed.

Simulation tools offer a wide range of prospective advantages that give utilities and system operators the ability to improve power quality and operational costs. The use of such tools can make the analysis/study of complex power networks simpler, giving valuable answers about the power quality behaviour of electricity networks in the presence of intermittent renewable energy generation and can help in reducing undesirable energy losses. In this work, steady-state simulations are performed by undertaking measurement investigations and model development in order to assess the impact of such studies on system planning and operation. By using DigSILENT PowerFactory, typical feeders of Nicosia district, Cyprus are realized into circuit form and simulated while considering demand and renewable energy production time series measurement data. The aim of the paper is to reveal the operational benefit of using design and analysis tools for proactive or corrective actions. From the simulations, it has been shown that network reconfiguration tasks lead to the reduction of power losses which can inevitably create an economic benefit for electricity utilities. In addition, simulation tools can help utilities meet challenging voltage regulation requirements/issues. One example of eliminating voltage violations through transformer tap optimization is also provided.

In isolated electricity networks the penetration of renewable energy sources offers, among others, the advantage of distributed electricity. At the same time, as penetration levels increase, controls and regulations need to be imposed in order to alleviate rising grid integration issues. Some of these can be prevented through the use of dynamic tariffs enabling Demand Side Management. In this work, a new tool for the optimization of dynamic tariffs is developed. This is based on statistical analysis of the consumption profiles and optimization procedures, aiming to derive the most appropriate Time-of-Use (ToU) tariffs. The consumption profile analysis performed on three hundred prosumers in Cyprus showed strong correlation between the measured and the average consumption profiles while the self-consumption rate of existing prosumers is averaged to 30%. The developed dynamic ToU blocks in comparison with the load curve exhibit a mean absolute percentage error and root mean square error of 6.22% and 12.32%, respectively.

The distribution grid structure is expected to change in the upcoming years with the further penetration of renewable energy sources (RES). Most of the energy needs will be covered by local distributed generators (DG) responsible also for maintaining good levels of power quality and grid stability. As a consequence, measures for regulating the voltage within acceptable levels will be required as well as storage to allow proper utilization of produced energy and to ensure that the distribution grid operates in an uninterruptable and healthy way. In this work, a new voltage regulation scheme inspired by Thevenin's Theorem is developed and presented. The well-known dynamic power factor method is modified accordingly to provide a variable lower limit, which is defined by the Thevenin equivalent impedance (TEI) measured at the point of common coupling with the electricity grid. The new voltage regulation scheme is incorporated into the control circuit of a verified Photovoltaic (PV) system model for its further evaluation via computer simulations.

The electricity grid is unidirectional operating in a passive way and consequently it is not yet ready to accept high penetration of renewable energy sources (RES). Further research is required to assess the impact of distributed Photovoltaic (PV) generation on power quality and establish the necessary measures for the restructuring of the electricity grid to ensure its optimum operation. In this paper, appropriate models are developed in order to assess the effects of PV generation. Thevenin's theorem is used to develop the equivalent circuit representing the exact distribution grid behaviour. The Thevenin equivalent circuit in combination with a verified PV system model are employed to study the power quality response of the distribution grid in the presence of PV via simulation and the results are compared to actual measurements yielding good agreement.

The solar irradiance dependent level of harmonic distortion due to PV generation is investigated through a combination of experimental and simulation studies. The expected growth of connection densities of PV systems in distribution networks coupled to the environmental conditions and in particular the fluctuations in solar irradiance can lead to undesirable variations of power and supply quality. In order to be able to predict the harmonic pollution due to PV generation, measurements of power quality indices were carried out at the output of a PV system for a period of 2weeks. Then, a typical distribution system was modeled using the statistically obtained outcome of the measurements from the PV system. From the simulation of the chosen distribution system we obtained results for voltage distortion and categorized them based on solar irradiance levels. The procedure was then validated using the EN50160 analysis approach. The most extreme case, the high solar irradiance condition, was subsequently used for the simulation of different concentration scenarios, in order to assess the concentration limits set by power quality indices and the results are presented. " 42 1 285 298

In this paper the thermal behaviour of distribution power substations is examined. Typical substation and transformer designs are modeled and their thermal behaviour is simulated using the finite element method. The results obtained are compared with on-site measurements in order to verify the model used. The effect of several design parameters is subsequently analysed. Therefore, it is possible to provide design guidance and test possible design options before these are approved for construction. Furthermore, it is possible using the model developed to carry out a sensitivity analysis by examining the effect of varying several parameters (the size and shape of the openings, the material of construction etc). The paper compares measured and simulation results, which verify that the predictions of the simulation are in good agreement with on-site measurements. (5 pages)

Partial discharge (PD) classification in power cable accessories and high voltage equipment in general is essential in evaluating the severity of the damage in the insulation. In this article, the PD classification was realised as a two-fold process. Firstly, measurements taken from a high-frequency current transformer (HFCT) sensor were represented as features by means of a transformation to the classifier and secondly, the probabilistic neural network (PNN) classifier itself was capable of effectively recognising features coming from different types of discharges. The feature that was used as a fingerprint for PD characterisation was extracted from the moments of the probability density function (PDF) of the wavelet coefficients at various scales, obtained through the wavelet packets transformation. The PNN classifier was used to classify the PDs and assess the suitability of this feature vector in PD classification. Four types of artificial PDs were created in a high voltage laboratory, namely corona discharge in air, floating discharge in oil, internal discharge in oil and surface discharge in air, at different applied voltages, and were used to train the PNN algorithm. The results obtained here (97.49, 91.9, 100 and 99.8% for the corona, the floating, the internal and the surface discharges, respectively) are very encouraging for the use of PNN in PD classification with this particular feature vector. This article suggests a feature extraction and classification algorithm for PD classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, and achieved very high levels of classification.

In today's competitive power transmission and distribution (T&D) industry the need for predictive and scheduled maintenance of the infrastructure has become a vital necessity. On-line condition monitoring of underground cables and switchboards for the dominant failure mechanism of Partial Discharge (PD) has been in use for some time now. It has been shown that on-line measurements for monitoring the activity and the degradation severity of the PD can not be calibrated in terms of their charge (pC). Although the direct interpretation of the measured voltage gives some indication, for more profound results specific locations have to be monitored over time to record the evolution of the amplitude and/or phase shift (trending). For these reasons a pilot on-line cable monitoring system is currently being implemented in a substation of the Electricity Authority of Cyprus (EAC) on selected breakers of the 11 kV switchboard. This system will alleviate the need for the physical presence of expert personnel on site, as measurements from sensors that will be non-invasively installed will automatically be recorded and processed on a continuous basis thus allowing potential dangerous PD events to be captured. Furthermore, the proposed system will implement permanent capacitive couplers that offer better sensitivity compared to other sensors. In this paper the setup and calibration of these sensors, together with some preliminary results will be presented. (4 pages)

Partial Discharge (PD) classification in power cables and high voltage equipment is essential in evaluating the severity of the damage in the insulation. In this paper, the Probabilistic Neural Network (PNN) method is used to classify the PDs. After the algorithm has been trained it uses the input vector, which contains the features that would be used for classification, to calculate the probability density function (pdf) of each class and together with the assignment of a cost for a misclassification the decision that minimizes the expected risk is taken. The maximum likelihood training is employed here. The success of this particular method for classification is asserted. This method has the advantage over Multilayer Neural Network that it gives rapid training speed, guaranteed convergence to a Bayes classifier if enough training examples are provided (i.e. it approaches Bayes optimality), incremental training which is fast (i.e. additionally provided training examples can be incorporated without difficulties) and robustness to noisy examples. The results obtained here (99.3%, 84.3% and 85.5% for the corona, the floating in oil and the internal discharges respectively) are very encouraging for the use of PNN in PD classification.

Renewable energy sources are expected to have a considerable share in the global energy mix over the next years and consequently further research is required to enhance the planning strategies, modify prudently the existing standards and set quality levels on delivered power in order to accommodate the penetration of these technologies. Depending on the distribution grid dynamics and the load demand, the amplitude of voltage may vary significantly, and therefore proper simulation models are required for performing dedicated studies. In this study, a simplified and accurate model representing the distribution grid dynamics is introduced for power quality studies in the presence of distributed photovoltaic (PV) generators. The proposed simplified distribution grid model (SDGM) is validated using measurements and it is then used along with a verified PV system model to estimate the voltage variation and PV capacity of the distribution grid under investigation. Moreover, a sensitivity analysis is performed by varying the parameters of the SDGM to assess how the PV capacity is altered. As a last step, common voltage regulation schemes are analysed through the use of the proposed model, validating operational modes that can accommodate high distributed PV capacities.

The high penetration of the Renewable Energy Sources and other emerging technologies likely to be installed in future power grids will pose new operational challenges to grid operators. One of the main issues expected to affect the operation of the power grid is the impact of inverter-based technologies to the power system inertia and, hence, to system stability. Consequently, the main challenge of the future grid is the evaluation of the frequency stability in the presence of inverter-based systems and how the aforementioned technology can support frequency stability without the help of the rotating masses of the traditional power grid systems. To assess the above problem, this paper proposes a methodology to evaluate the frequency stability in a projection of the real distribution grid in Cyprus with the time horizon to be the year 2030. The power grid under investigation is evaluated with and without the presence of smart hierarchical controllers for providing support to the power system under disturbance conditions. The advanced controllers were applied to manage the available power resource in a fast and effective manner to maintain frequency within nominal levels. The controllers have been implemented in two hierarchical levels revealing useful responses for managing low-inertia networks. The first is set to act locally within a preselected area and the second level effectively supporting the different areas for optimal operation. After undertaking a significant number of simulations for time-series of one year, it was concluded from the results that the local control approach manages to minimize the frequency excursion effectively and influence all related attributes including the rate of change of frequency (RoCoF), frequency nadir and frequency zenith.