Search

Accurate photovoltaic (PV) power forecasting is an essential tool that enables the efficient integration of solar electricity and energy trading. This work proposes a novel methodology for the implementation of a forecasting tool that provides aggregated PV production day‐ahead forecasts for the PV systems installed at a distribution level. Specifically, the tool is a cloud‐based platform, comprising of a data quality block, a weather forecasting model, a machine learning power prediction step and an up‐scaling aggregation stage. In this context and in the absence of a fully observable distribution system, the aggregated PV generation was estimated using a clustering approach and up‐scaling the measured generation of reference systems to the aggregated installed capacity. The results demonstrated that the implemented tool exhibited high forecasting accuracies, lower than 10% given by the mean absolute percentage error when applied to the distribution system of Cyprus. Furthermore, the comparative benchmarking of the up‐scaling techniques against the estimated aggregated PV generation demonstrated that the best‐performing approach was the hybrid model, which provided a normalised root mean square error of 10.29% and mean absolute percentage error of 9.11%. Finally, useful information is provided for establishing a robust day‐ahead forecasting methodology that is based on an optimal supervised learning and hybrid up‐scaling approach.

The distributed and stochastic nature of Renewable Power Sources is certainly forming considerable challenges for the operation of the power system. Specifically, the stability of the system can be jeopardized when the penetration of inverter-based systems is high. Storage and the proper design of controllers is seen as part of the solution for supporting the future expansion of distributed systems. Thus, control strategies need to be designed to provide the appropriate support to the system and be capable of keeping the variation of the frequency within limits to keep the reliability of the system as high as possible. The main challenge is the appropriate parameterization of these distributed controllers and their coordination under the integrated grid approach in securing the stability of the system at all times. In this paper, a smart energy controller is utilized and incorporated into the projection case study for Cyprus’ real distribution grid for the year 2050 to evaluate its behavior and identify possible weaknesses in its usage. It was found that the parameterization and not only the architecture of such controllers is crucial in coping with the frequency variation and stability problem. From the simulation work and recorded results, it was observed that the smart energy controllers can maintain frequency variation within the desirable range when the parametrization of the controllers is chosen appropriately. This specific observation highlights the need to evaluate and configure the smart controllers while operating in the field, and possibly further research is required to provide the advanced capability to such systems to adjust dynamically during field operation, thereby achieving better response during abnormal conditions.

Along with the increasing share of non-synchronous power sources, the inertia of power systems is being reduced, which can give rise to frequency containment problems should an outage of a generator or a power infeed happen. Low system inertia is eventually unavoidable, thus power system operators need to be prepared for this condition. This paper addresses the problem of low inertia in the power system from two different perspectives. At a system level, it proposes an operation planning methodology, which utilises a combination of power flow and dynamic simulation for calculation of existing inertia and, if need be, synthetic inertia (SI) to fulfil the security criterion of adequate rate of change of frequency (RoCoF). On a device level, it introduces a new concept for active power controller, which can be applied virtually to any power source with sufficient response time to create synthetic inertia. The methodology is demonstrated for a 24 h planning period, for which it proves to be effective. The performance of SI controller activated in a battery energy storage system (BESS) is positively validated using a real-time digital simulator (RTDS). Both proposals can effectively contribute to facilitating the operation of low inertia power systems.

This paper summarises results and experiences from several demonstration projects across European countries in the field of battery energy storage system (BESS) integration to the power system. These research projects are selected among research institutes and universities that are part of the European Energy Research Alliance (EERA) Joint Program on Smart Grids. The paper categorizes these projects according to the demonstrated applications of BESS and then reviews specific aspects of each project. This paper provides an opportunity to find out the summary of the most recent results as well as challenges and open research questions in projects focusing on different BESS application in the power system.

This paper provides an overview of methods for including Battery Energy Storage Systems (BESS) into electric power grid planning. The general approach to grid planning is the same with and without BESS, but when BESS is included as an alternative, other methods are necessary, which adds significant complexity to the planning problem. Although recent research literature proposes a wide range of methods and models for Cost-Benefit Analysis (CBA) of BESS for grid applications, these are to a little extent applied in practice. For the research-based methods to be suitable for grid planning, they should handle timing of installations as well as sizing and siting of BESS. Moreover, they must capture long-term developments in load and generation. Finally, the CBA methods need realistic modelling of the operational benefits of BESS, taking into account multi-period AC power flow, battery degradation, and utilization for multiple grid services. Keywords: Battery storage , cost-benefit analysis , electric power grid , power system planning © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

31st European Photovoltaic Solar Energy Conference and Exhibition; 2945-2951, Integration in the power system is becoming a limiting factor to the further development of photovoltaics. Proper quantification is needed to evaluate both issues and solutions; the share of annual electricity demand is widely used but we found that some of the metrics which are related to power rather than energy better reflect the impact on networks. Barriers to wider deployment of PV into power grids can be split between local technical issues (voltage levels, harmonics distortion, reverse power flows and transformer loading) and system-wide issues (intermittency, reduction of system resilience). Many of the technical solutions to these issues rely on the inverters as actuators (e.g., for control of active and reactive power) or as interfaces (e.g., for local storage). This role requires further technical standardisation and needs to be taken into account in the planning of power networks. Forecasting, storage, and combination with other renewable sources are interdependent solutions to solve the intermittency issue. Finally, we found that PV is also an opportunity to reduce some investment required to upgrade existing power networks. Through integration with micro-grids and hybrid generators, it can form the basis of novel power systems.

The continuously increasing complexity of modern and sustainable power and energy systems leads to a wide range of solutions developed by industry and academia. To manage such complex system-of-systems, proper engineering and validation approaches, methods, concepts, and corresponding tools are necessary. The Smart Grid Architecture Model (SGAM), an approach that has been developed during the last couple of years, provides a very good and structured basis for the design, development, and validation of new solutions and technologies. This review therefore provides a comprehensive overview of the state-of-the-art and related work for the theory, distribution, and use of the aforementioned architectural concept. The article itself provides an overview of the overall method and introduces the theoretical fundamentals behind this approach. Its usage is demonstrated in several European and national research and development projects. Finally, an outlook about future trends, potential adaptations, and extensions is provided as well.

This paper presents the main objectives, approach, results and challenges achieved so far of the H2020 project PANTERA (PAN European Technology Energy Research Approach). A special highlight of the work carried out in the Balkan region considering the first PANTERA workshop in Sofia, Bulgaria is given. Based on analysis of the results achieved, the potential for improvements and future steps are elaborated.

With the increasing availability of DC consumable appliances as well as the increasing penetration of direct current (DC) Distributed Energy Resources (DERs) such as photovoltaics (PV) and Energy Storage Systems (ESS), the future yields to the concept of DC power distribution systems. In the developed world, as the conventional distribution grids are based on AC, a hybrid approach of AC and DC grids and assets seems to be a good approach. Therefore, an increasing attention on the utilization of hybrid DC -AC nanogrids is expected to hostsmart building enabling technologies and to accommodate high RES penetration and gain technoeconomical advantages This paper explores and analyzes these advantages focusing on the case study of the hybrid nanogrid of the University of Cyprus and examines the economic gains of the system based on a techno-economic analysis of the FOSS Research Centre for Sustainable Energy nanogrid. The main outcome of this study is that the penetration of the photovoltaic system as well as the energy storage system connected to the DC busbar of an hybrid architecture, can play an important role to the reduction of the imported energy from the grid and increase the self-consumption with the energy transferred directly to the load.

This paper presents a concept for flexible and self-adaptable classification of ETIP SNET technologies and functionalities that form the basis to analyze the research and innovation (R& I) progress towards the achievement of decarbonised smart grid network by 2050. Based on analysis of the currently adopted “static” classification of ETIP SNET technologies, functionalities, and methodology for evaluating project results, the main fast evolving research and innovation drivers and needs are identified. A linking chain between functionalities and serving technologies is identified and a solid measurable process of quantification of the progress of functionalities is determined. As a result a methodology for transition of this process to flexible and adaptable for the ETIP SNET’s 10-year plan is proposed.

The continuously increasing complexity of modern and sustainable power and energy systems leads to a wide range of solutions developed by industry and academia. To manage such complex system-of-systems, proper engineering and validation approaches, methods, concepts, and corresponding tools are necessary. The Smart Grid Architecture Model (SGAM), an approach that has been developed during the last couple of years, provides a very good and structured basis for the design, development, and validation of new solutions and technologies. This review therefore provides a comprehensive overview of the state-of-the-art and related work for the theory, distribution, and use of the aforementioned architectural concept. The article itself provides an overview of the overall method and introduces the theoretical fundamentals behind this approach. Its usage is demonstrated in several European and national research and development projects. Finally, an outlook about future trends, potential adaptations, and extensions is provided as well.