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This paper presents findings on participants of a massive open online course named "Educational Robotics for all" developed under Open edX platform. The document describes the organization and structure of the MOOC and some of its preliminary results. As an example, Module 2 about Gender and STEAM is presented and discussed.

The idea of creation of more decentralized power system has been circulating for a while, but started to materialise only during the recent years, when massive introduction of support schemes for RES has started to move more and more generation into the distribution network. Apart from the environmental benefits, this has created several challenges for planning and operation of the conventional power system. Furthermore, the growing recognition of necessity for optimization across different energy carriers for example “ETIP SNET Vision 2050” is also pointing towards more and more decentralized system. This chapter presents an overview of the main architectures and concepts for smart decentralized energy systems, through the critical analysis of recent documents such as Pan-European roadmaps (ETIP-SNET) and scenarios (TYNDP2020), results of R&D projects and regulatory documents (“Clean Energy for all Europeans”). The chapter is organized in four parts and starts with background for decentralization: driving forces, trends, and foreseen benefits as well as potential challenges and pitfalls. The second section starts with an overview of different levels of decentralization. The decentralized architecture combined with new ICT infrastructure (including machine learning), opens possibility for new and more efficient control approaches (balancing and voltage). This issue has been studied for example in ELECTRA IRP project, elaborating a cellular structure with dedicated set of novel controls for the power system. This section will further look at the market alternatives and the areas with several unresolved issues and gaps, which must be explored further and require an immediate attention from the research community. The following section will present views of several key stakeholders on decentralization of the power system. It appears that transformation to partially or fully decentralized power system will require certain changes of the present and creation of new roles and responsibilities among actors on the power market. Some of these modifications has been already introduced and formalised in the most recent recast of “Clean Energy for all Europeans.” The section will further present somewhat different opinions about this among the involved stakeholders, which have been expressed in several position papers. The final section makes conclusions and links the content to other chapters of the book.

This chapter provides insights into the participation of distributed energy resources (DERs) in the electricity markets. The massive integration of distributed energy generation coming from renewable energy sources (RES) with intermittent character, together with the empowering of the customers and the emergence of new agents, such as electric vehicles, are forcing the power systems to evolve. In this context, the provision of flexibility services that has been traditionally done by a reduced number of big generation plants will be also done by the new DERs. Throughout the chapter, a review of the possibilities of the DERs to provide flexibility services, the needs of those services in the future power systems and the current market framework will be reviewed. Eventually, the need to develop market-based solutions (local energy markets) to overcome the limitations of DERs participation in the current electricity markets will be analyzed.

The pedagogy of science, technology, engineering, arts, and mathematics (STEAM) can be easily developed by using robotics and computational thinking tools. Also, inclusion and integration of diverse groups of students can be promoted using these tools. Today we can find many tools for teaching robotics. This kind of tools allow us to promote innovation and motivation of students. In this way, students will be able to work during the learning process in an innovative and motivating way. Since it is increasingly common to find robots in our daily lives, it is important to integrate robots into education as well. There are already cooking robots, autonomous cars, vacuum cleaner robots in houses and gardens, or prostheses. This paper describes a course focused on a combination of teaching methodologies, educational robotics tools, and a student learning management methodology, all within an inclusive framework to strengthen the presence of women and other under-represented groups in engineering.

This chapter deals with the coupling of smart grid laboratories for joint experiments. Therefore, various possibilities are outlined and a reference implementation is introduced. Finally, the vision of a distributed, virtual research infrastructure is presented.

Climate change motivated by human activities constitutes one of the main challenges of this century. To cut carbon emissions to mitigate its dangerous effects, the current energy generation mix should be shifted to renewables sources. The main drawback of these technologies is their intermittency that will require storage systems to fully integrate them in the generation mix, allowing them to be more controllable. In recent years great progress to develop an effective and economically feasible energy storage systems, particularly motivated by the recent rise of demand for electric transportation has been made. Lithium-ion (Li-ion) battery prices have fallen near 90% over the past decade, making possible the affordability of electric vehicles and transforming the economics of renewable energy. In this paper, we evaluate the energy storage requirements for a carbon-free scenario in Spain, analyzing the CO2 emissions reduction.

This article presents an integrated storage management strategy with photovoltaic systems connected to the grid, to provide voltage regulation and losses reduction in the low voltage feeder, minimising the power supplied by the network upstream of the main transformer. A new control algorithm for battery energy storage systems (BESS) is presented embedding as a battery management algorithm for charging and discharging process. The charging of the storage system is defined by the optimization of the αk coefficient to establish the value of charging threshold power, in a distributed manner, to maximise the use of photovoltaic systems. The discharging process occurs by a given σ coefficient. A standard network model from CIGRE was used for the validation of the management strategy. It was modified with real profiles of load and irradiance with a minute resolution to adapt it to the using of the quasi-static load flow in MATLAB/Simulink. As a result, by integrating 67% of PV along with 442 kWh of BESS with its management algorithm, power import from the grid decreases up to 49.3%. The authors would like to thank the University of the BasqueCountry and TECNALIA for supporting the work done at the Universityof the Basque Country under research grant by the Carolina Foundation.

The growth of distributed energy resources in power systems, mainly converter-coupled generators, has forced the evolution of grid codes, increasing the requirements to be fulfilled by the generators before their connection to the mains. Solving this problem is crucial to guarantee the reliability and stability of the power system. Current standards force the generators to remain connected when facing voltage and/or frequency disturbances and, in some advanced grid codes, also when the generators are facing transient phase jumps produced as a consequence of those disturbances. If considering that the increment of the distributed generation is mainly done at a distribution level, it is unrealistic to consider voltage and frequency events as decoupled phenomena in the testing and certification procedures, as it is currently done. The testing device proposed in this paper is able to reproduce voltage, frequency and phase jumps disturbances of a controlled value simultaneously, being able to reproduce the real grid behavior reliably. Its design is based on standard components with a simple control system, which makes it easily replicable and scalable up to the power of the device to be tested. Therefore, the proposed device is an interesting commercially competitive testing equipment suitable for certification. This work has been funded by the Spanish Ministry of Economy and Competiveness under research grants PN-ENE2009-13276 and BES- 2010-034386.

Widespread application of residential photovoltaic (PV) systems and electric vehicles (EVs) has led the distribution system operators (DSOs) to face new technical challenges such as overloading and significant voltage variations, especially on low voltage (LV) grids. This adverse effect may be mitigated by employing the aggregators as intermediary actors to coordinate the operation at the distribution level. Therefore, this paper proposes a centralised coordination strategy to mitigate both PV and EV impacts, such as voltage rising/dropping at noon or evening, respectively, by defining the optimal export limit of PV power and EVs charging among multiple aggregators at the DSO level. The latter is in charge to dictate the optimal aggregated signals to every aggregator by employing a mixed-integer quadratic programming (MIQP) approach. The aggregated PV power is evenly managed for each aggregator by weighting. Two convex optimisation models are defined to satisfy both power and voltage constraints of the LV network. Each proposed optimisation approach can be utilised when there is or no detailed information about the LV network topology. The concepts discussed in this paper are tested on a real low voltage network considering a critical penetration level of EVs and PVs.

This study is intended to show the future voltage control strategy designed in the framework of the ELECTRA Integrated Research Programme (IRP) project for the web-of-cells (WoC) concept. This scheme, called post-primary voltage control, aims to keep the node voltages at any time within the bands defined by the regulations and to minimise the power losses in the system by calculating the optimal voltage set-points for the different nodes. The reactive power will mainly be used to restore the voltages but also active power could be delivered in some cells depending on their voltage levels. Different operating modes of the voltage control will be discussed taking both planning and the real-time operation phases into account. The application of the voltage control strategy to one test grid considered as representative of the WoC structure will also be shown in this study. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007– 2013) under grant agreement no. 609687.

In order to systematically plan, specify, and execute system-level test for smart grids in a cyber-physical and multi-domain manner, the ERIGrid holistic testing approach is introduced. Also, the corresponding test description and templates are discussed.

Selected validation scenarios and corresponding test cases in the context of the ERIGrid project are presented in this chapter. Furthermore, the benefits of using the ERIGrid validation method and testing tools are discussed on the realized system validation examples.

A summary of experiences and discussion of lessons learned from using the ERIGrid system-level validation approach in various projects is provided by this chapter. Also, the main advantages and shortcomings are discussed.

The urban and interurban mobility environment has been evolving in recent decades. Traditional factors that have been pushing these changes have been changes in motorisation, residential and urban sprawl, and the spatial distribution of the population, the workplaces and other societal relevant locations. Currently, more than a half of the world population is living in cities, reaching almost 72% in the European Union (EU), and it is estimated that over 80% of the European population will live in urban areas by 2020. The growth of the cities will also generate new city mobility challenges to be solved.

The introduction of electric vehicles (EVs) is another alternative to reduce GHG emissions in these isolated systems, because these vehicles are more suitable for the short average daily distances on the islands. EVs can also contribute to integrating renewable energies in these isolated systems, becoming flexible loads and helping to reduce the peak-valley ratio and flattering the energy demand curve. Additionally, the mobility characteristics in islands make them appropriate to promote the electrification of the transportation sector. Introducing V2G as an energy storage system presents advantages such as making use of large-scale distributed storage systems; the batteries of EVs present very low cost for grid operators, easy implementation, and compatibility with the environmental policy. In this work the option of charging an EV fleet as a distributed energy storage system to increase the participation of renewable energy in an isolated power system has been presented.

Even though the Li-ion battery price has dropped significantly in recent years, this storage technology is still quite expensive and, in order to avoid overspending, this study proposes using EV's batteries as Battery Energy Storage System. One of the main disadvantages of this scheme is that the total available battery's capacity is variable, but it is dependent on the EV's mobility. In this chapter, an optimization model is developed to minimize the electricity cost purchased from the utility grid by the building manager. This optimization model takes into account several parameters: the availability of the EVs parked at the parking lot (that affects the available storage capacity, which varies at each time period, as EVs come and go along the day), the total energy consumption demanded by the building, the self -PV generation and, finally, the retail energy prices. With this information, the optimization algorithm determines how the EV batteries' charge/ discharge of all parked vehicles should be managed to minimize the cost of electricity purchased from the grid.

Electric vehicles (EVs) are a major component of future electric grids, both for the increase in electricity demand and the flexibility they can add to the grid. Vehicle-to-grid and vehicle-to-building pilots have been tested and some have been approved by grid operators, but the EVs' possibilities shall be further enhanced. In previous works, the authors proposed a peer-to-peer energy market between EVs that largely reduced the expenses of their costly day-charging. This chapter further expands the model by taking into account the long-term effects of the market, which reduce the impact of the electric grid prices forecast on the market. The ratio between EVs that offer energy and those that demand energy is shown to be a good indicator for the market price forecast. Almost all energy demand occurs in pairs zone-time in which the number of offering EVs is more than five times the number of demanding EVs, for which the market price is very close to the electricity price at night.

The performance of TSO-DSO coordination schemes depends on the characteristics of the electricity systems in which regulation reserves can be provided by both transmission and distribution resources. In order to investigate the main aspects influencing TSO-DSO interactions, three detailed electricity scenarios (related to the expected 2030 evolution of Denmark, Italy and Spain) are defined. In particular, these scenarios are designed by assuming various distribution network conditions, determining different volumes of flexibility requested by the DSO in order to carry out local services. Then, the structure of a simulation platform, aimed at testing TSO-DSO coordination schemes, is proposed. It is based on three main blocks, integrating actual market clearing, bidding and dispatching algorithms, together with a simulator for the network and all the physical power resources. Finally, the simulation results are processed by means of a cost-benefit analysis which identified the market architectures providing the highest economic benefits to the system and the main factors that influence the profitability of one TSO-DSO coordination scheme among the others. H2020, n. 691405, SmartNet

Self-consumption is a growing public demand in an energy environment with growing electricity costs and decreasing photovoltaic installation costs. Shared self-consumption is an imperative aspect for bringing self-consumption into Multi-Family Residential Buildings (MRB), where most families live. Nevertheless, current legislation in most countries does not consider shared self-consumption or does not exploit its full potential; such is the case of Spain or Portugal. This paper will present a novel optimization problem for studying the economics of a shared self-consumption installation in a MRB (composed of five family demands, a PV installation and a battery) with the aim of reducing the total bill of the MRB during an entire year. The impact on energy communities of two different types of energy policies is analysed: the remuneration scheme for the surplus energy (net metering, net billing, and exclusive self-consumption policies) and the regulation for shared self-generated energy (demand-dependent, proportional output and no sharing). It is found that the regulation for the sharing energy can be more important that the remuneration scheme, which has been the traditional target of the self-consumption policy.

This paper introduces a linear programming (LP)-based optimisation method of charging electric vehicles (EVs) in a decentralised fashion. It exploits the available photovoltaic (PV) power to charge EV batteries while maintaining the low-voltage (LV) network within its operational limits. A new energy-bound model is implemented in order to meet the connected EVs energy requirements. This model highlights two main aspects: first, the proposed formulation seeks to compute both the upper and lower energy boundaries from the arrival energy and no from zero. Second, the charging power is dynamically adjusted by combining a fixed and variable charging rate to assure the technical limits of the network. This means maximising power delivered to all EVs for a given period by optimising the charging rate of each EV connected. Besides, a network sensitivity analysis technique is developed to manage voltage and loading constraints. The accuracy of the proposed linear approximation was tested simulating two cases (moderate and high penetration level of PVs and EVs) on a real LV feeder. Results over a set of simulations for winter and summer seasons demonstrate that this method can be effectively implemented as a charging strategy and for energy planning studies. This work was supported by TECNALIA funding through its PhD scholarship program. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work.

The growing trend of introducing electric vehicles (EVs) into power systems to reduce the environmental emissions in the transport sector is gaining significant attention among electrical power system agents for two reasons: the potential grid services the EVs can offer in an aggregated manner and the possible undesirable effects of massive integration in grid operation that can increase the requirement for investment in new assets. In this context, the aggregator is the representative entity that needs to maximise the benefits in the management of these sizeable quantities of vehicles while fulfilling the requirements of grid services requested by the distribution system operator. In this study, we review the concept of EV aggregators and their potential services to the distribution network. Several studies related to EVs aggregation modelling have been analysed and classified into three groups: individual-based, population-based, and hybrid approaches. We present the current status of EVs aggregation modelling as well as future research trends. Furthermore, we discussed the performance comparison of EVs models from several manufacturers utilised in network integration studies, likewise the most relevant databases and surveys. Finally, we arranged and annexed the most relevant mathematical expressions of the reviewed approaches, thereby simplifying the comprehension of the methods. We would like to gratefully acknowledge that this study was made possible with the help of TECNALIA funding through a PhD scholarship. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work.

In future power grids, a large integration of renewable energy sources is foreseen, which will impose serious technical challenges to system operators. To mitigate some of the problems that renewable energy sources may bring, new voltage and frequency control strategies must be developed. Given the expected evolution of technologies and information systems, these new strategies will benefit from increasing system observability and resources controllability, enabling a more efficient grid operation. The ELECTRA IRP project addressed the new challenges that future power systems will face and developed new grid management and control functionalities to overcome the identified problems. This work, implemented in the framework of ELECTRA, presents an innovative functionality for the control room of the cell operator and its application in assistance with the voltage control designed for the Web-of-Cells. The voltage control method developed uses a proactive mode to calculate the set-points to be sent to the flexible resources, each minute, for a following 15-min period. This way, the voltage control method developed is able to mitigate voltage problems that may occur, while, at the same time, contributes to reduce the energy losses. To enable a straightforward utilization of this functionality, a user interface was created for system operators so they can observe the network state and control resources in a forthright manner accordingly. The work presented in this paper was funded by the ELECTRA IRP project (Seventh Framework Programme FP7 2007/2013) under grant agreement No. 609687.

Half of the global population already lives in urban areas, facing to the problem of air pollution mainly caused by the transportation system. The recently worsening of urban air quality has a direct impact on the human health. Replacing today’s internal combustion engine vehicles with electric ones in public fleets could provide a deep impact on the air quality in the cities. In this paper, real mobility information is used as decision support for the taxi fleet manager to promote the adoption of electric taxi cabs in the city of San Francisco, USA. Firstly, mobility characteristics and energy requirements of a single taxi are analyzed. Then, the results are generalized to all vehicles from the taxi fleet. An electrificability rate of the taxi fleet is generated, providing information about the number of current trips that could be performed by electric taxis without modifying the current driver mobility patterns. The analysis results reveal that 75.2% of the current taxis could be replaced by electric vehicles, considering a current standard battery capacity (24–30 kWh). This value can increase significantly (to 100%), taking into account the evolution of the price and capacity of the batteries installed in the last models of electric vehicles that are coming to the market. The economic analysis shows that the purchasing costs of an electric taxi are bigger than conventional one. However, fuel, maintenance and repair costs are much lower. Using the expected energy consumption information evaluated in this study, the total spatio-temporal demand of electric energy required to recharge the electric fleet is also calculated, allowing identifying optimal location of charging infrastructure based on realistic routing patterns. This information could also be used by the distribution system operator to identify possible reinforcement actions in the electric grid in order to promote introducing electric vehicles.

In this paper a night charging method that optimizes the recharging process of electric vehicles (EVs) depending on hourly energy price in a peer to peer (P2P) energy trading system is presented. This algorithm determines how much energy should be recharged in the battery of each EV and the corresponding time slot to do it, avoiding the discontinuities in the charging process and considering the users’ personal mobility constraints.

This paper presents the decentralized Post-Primary Voltage Control (PPVC) scheme which is introduced within the Web-of-Cells (WoC) concept in the ELECTRA IRP project. The PPVC improves the traditionally known secondary and tertiary voltage control schemes to develop a robust method coping with the emerging intermittent generation and variable loading in the distribution system. PPVC aims to utilize all available resources within a defined network area for voltage control purposes by taking loss minimization as an objective. To achieve that, the re-definition of voltage set-points in all controllable nodes within the area is performed using an Optimal Power Flow (OPF) algorithm. The proposed PPVC algorithm coordinates tap changers and other reactive power resources such as PV inverters proactively altering their settings for a recurring time-window. The settings are optimally computed by using short-term forecasted load and generation values. The PPVC algorithm has been implemented with MATLAB and the General Algebraic Modeling System (GAMS) tool for optimization and evaluated on The European CIGRÉ MV network, modified with distributed energy resources (DERs). Simulation results showing the impact of PPVC compared to the business-as-usual (BaU) way of voltage control are presented. In addition, laboratory tests coupling the GAMS-based OPF with OPAL-RT have been conducted to present the efficiency of PPVC in real-time applications.

Here, the authors analyse the operator point of view of the Web-of-Cells concept defined in the EU project ELECTRA, by identifying operator tasks into the supervision of a highly automated power system, and the information requirements to facilitate appropriate operator situation awareness. The study outlines the methodology adopted, which is based on the cognitive work analysis framework, to provide an overview of the most interesting scenarios and to summarise the requirements analysis results. In order to derive required control room functionality, a set of relevant control room scenarios have been identified based on the Web-of-Cells control concept. The authors considered scenarios that challenge traditional control schemes, scenarios that caused major failures (i.e. blackouts), and scenarios that can be expected to appear in the future. For each scenario, information concerning network layout, triggering events, physical constraints, manually/automatic operations, operators' tasks, and relevant analytics have been analysed. The work in this paper was supported by the European Commission, under the FP7 project ELECTRA (grant no: 609687).

Wind is a renewable energy resource by nature. It is clean, abundant, inexhaustible and environmentally friendly. Essentially, this study investigated the prospects of wind energy for power generation in University of Benin. Wind data from Jan 31st – Dec 31st 2013 (at 10m height) was collected from National Centre for Energy and Environment, University of Benin. Accordingly, the annual and monthly wind speed and density are estimated using the 2- parameter Weibull probability density function. From the analysis, results obtained shows that the highest mean wind speed of 1.975m/s occurred in March and the lowest monthly mean speed of 0.977m/s occurred in November. Also, the annual mean wind speed is 1.496m/s while the annual mean power density based on Weibull distribution function is 2.692W/m2 . Further results shows that the mean annual most probable wind speed and wind speed carrying maximum energy are 1.535m/s and 1.761m/s respectively. Thus, it is recommended that the institution can tap on the available wind power potential to augment its power supply.

Electrical power systems are changing their traditional structure, which was based on a little number of large generating power plants placed at great distances from loads by new models that tend to split the big production nodes in many smaller ones. The set of small groups which are located close to consumers and provide safe and quality energy is called distributed generation (DG). The proximity of the sources to the loads reduces losses associated with transportation and increases overall system efficiency. DG also favors the inclusion of renewable energy sources in isolated electrical systems or remote microgrids, because they can be installed where the natural resource is located. In both cases, as weak grids unable to get help from other nearby networks, it is essential to ensure appropriate behavior of DG sources to guarantee power system safety and stability. The grid codes sets out the technical requirements to be fulfilled for the sources connected in these electrical networks. In technical literature it is rather easy to find and compare grid codes for interconnected electrical systems. However, the existing literature is incomplete and sparse regarding isolated electrical systems and this happens due to the difficulties inherent in the pursuit of codes. Some countries have developed their own legislation only for their island territory (as Spain or France), others apply the same set of rules as in mainland, another group of island countries have elaborated a complete grid code for all generating sources and some others lack specific regulation. This paper aims to make a complete review of the state of the art in grid codes applicable to isolated systems, setting the comparison between them and defining the guidelines predictably followed by the upcoming regulations in these particular systems.