Validating Intelligent Power and Energy Systems { A Discussion of Educational Needs

Traditional power systems education and training is flanked by the demand for coping with the rising complexity of energy systems, like the integration of renewable and distributed generation, communication, control and information technology. A broad understanding of these topics by the current/future researchers and engineers is becoming more and more necessary. This paper identifies educational and training needs addressing the higher complexity of intelligent energy systems. Education needs and requirements are discussed, such as the development of systems-oriented skills and cross-disciplinary learning. Education and training possibilities and necessary tools are described focusing on classroom but also on laboratory-based learning methods. In this context, experiences of using notebooks, co-simulation approaches, hardware-in-the-loop methods and remote labs experiments are discussed.Comment: 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS 2017

Education and training needs, methods, and tools

The importance of education and training in the domain of power and energy systems targeting the topics of cyber-physical energy systems/smart grids is discussed in this chapter. State-of-the art laboratory-based and simulation-based tools are presented, aiming to address the new educational needs

Optimal planning of hybrid energy conversion systems for annual energy cost minimization in Indian residential buildings

The increasing interest in renewables has encouraged power system planners to include the concept of hybrid energy systems in modern power industry. Besides, the modern power consumers are becoming more concerned about their energy bills which has led to the concept of hybrid energy management systems (HEMSs) for buildings to monitor, control and optimally manage energy consumptions without any waste. In this study, an optimal planning framework is proposed to determine optimal capacities and sharing of hybrid energy conversion systems (HECS) such as wind turbine, solar photovoltaic, battery energy storage and the utility grid. The objective is to maximize the net present value of the project/system which includes the cost of annual investment, operation and maintenance costs of HEMS expected to have incurred in the planning period. All the costs and parameters are considered in the Indian context, and Genetic Algorithm (GA) is adopted to solve this proposed planning framework. The simulation results obtained are compared with same obtained for conventional houses in India. The comparison shows that the proposed framework effectively reduces the electricity bills while improving its reliability

Development and Coverage Evaluation of ZigBee-Based Wireless Network Applications

Network coverage is one of the basic issues for information collection and data processing in ZigBee-based wireless sensor networks. Each node may be randomly distributed in a monitoring area, reflecting the network event of tracking in ZigBee network applications. This paper presents the development and coverage evaluation of a ZigBee-based wireless network application. A stack structure node available for home service integration is proposed, and all data of sensing nodes with an adaptive weighted fusion (AWF) processing are passed to the gateway and through the gateway to reexecute packet processing and then reported to the monitoring center, which effectively optimize the wireless network to the scale of the data processing efficiency. The linear interpolation theory is used for background graphical user interface so as to evaluate the working status of each node and the whole network coverage case. A testbed has been created for validating the basic functions of the proposed ZigBee-based home network system. Network coverage capabilities were tested, and packet loss and energy saving of the proposed system in longtime wireless network monitoring tasks were also verified

Competency maps: An effective model to integrate professional competencies across a STEM curriculum

Curricula designed in the context of the European Higher Education Area need to be based on both domain-specific and professional competencies. Whereas universities have had extensive experience in developing students’ domain-specific competencies, fostering professional competencies poses a new challenge we need to face. This paper presents a model to globally develop professional competencies in a STEM degree program, and assesses the results of its implementation after four years. The model is based on the use of competency maps, in which each competency is defined in terms of competency units. Each competency unit is described by their expected learning outcomes at three domain levels. This model allows careful analysis, revision and iteration for an effective integration of professional competencies in domain-specific subjects. A global competency map is also designed, including all the professional-competency learning outcomes to be achieved throughout the degree. This map becomes a useful tool for curriculum designers and coordinators. The results were obtained from four sources: 1) students’ grades (classes graduated from 2013 to 2016, the first four years from the new Bachelor’s Degree in Informatics Engineering at the Barcelona School of Informatics); 2) students’ surveys (answered by students when they finished the degree); 3) the government employment survey, where former students evaluate the satisfaction of the received training in the light of their work experience; and 4) the Everis Foundation University-Enterprise Ranking, answered by over 2000 employers evaluating their satisfaction regarding their employees’ university training, where the Barcelona School of Informatics scores first in the national ranking. The results show that competency maps are a good tool for developing professional competencies in a STEM degree.Peer ReviewedPostprint (author's final draft

The Sustainability Matrix: A tool for integrating and assessing sustainability in the bachelor and master theses of engineering degrees

It is vital that subjects such as the circular economy, sustainable design, green computing or environmental engineering be included in the engineering curriculum. Education for sustainable development will enable engineers to develop sustainable products and provide sustainable services, thereby leading to a beneficial result for society and making an indispensable contribution to the Sustainable Development Goals achievement. As the last stage for students in academia, Degree Theses (Bachelor’s and Master’s) provide a good tool for reviewing the sustainability competencies developed during the degree, as well as being an opportunity for applying these competencies in a holistic way. In their Degree Theses, students should be able to demonstrate that they are aware of the need to introduce and assess sustainability in their future engineering projects. This paper presents a guide aimed at helping engineering students to design and develop sustainable projects, and analyzes the first results of its use in two schools of the Universitat Polite`cnica de Catalunya—BarcelonaTech. The proposal is based on a tool referred to as “the Sustainability Matrix”, in which cells contain questions that engineering students should take into account when undertaking their Degree Theses. The questions are related to the project development, the project exploitation and the possible risks involved, three aspects in accordance with the sustainability dimensions (economic, environmental and social). The Sustainability Matrix helps students to develop sustainable projects when they graduate, and teachers to assess how sustainability is incorporated across the curriculum in the subjects they teach and in the students’ Degree Theses.This research was funded by the Spanish Ministerio de Economía y Competitividad under Grant EDU2015-65574-R, and by Spanish Ministerio de Ciencia, Innovación y Universidades, the Spanish Agencia Estatal de Investigación (AEI) and the Fondo Europeo de Desarrollo Regional (FEDER) under grant number RTI2018-094982-B-I00, from study design to submission.Peer ReviewedPostprint (published version

Incentive based Residential Demand Aggregation

From the beginning of the twenty-first century, the electrical power industry has moved from traditional power systems toward smart grids. However, with the increasing amount of renewable energy resources integrated into the grid, there is a significant challenge in power system operation due to the intermittency and variability of the renewables. Therefore, the utilization of flexible and controllable demand-side resources to maintain power system efficiency and stability has become a fundamental goal of smart grid initiatives. Meanwhile, due to the development of communication and sensing technologies, intelligent demand-side management with automatic controls enables residential loads to participate in demand response programs. Therefore, the aggregate control of residential appliances is anticipated to be feasible technique in the near future, which will bring considerable benefits to both residential consumers and load-serving entities. Hence, this dissertation proposes a comprehensive optimal framework for incentive based residential demand aggregation. The contents of this dissertation include: 1) a hardware design of smart home energy management system, 2) a new model to assess the responsive residential demand to financial incentives, and 3) an online algorithm for scheduling residential appliances. The proposed framework is expected to generate optimal control strategies over residential appliances enrolled in incentive based DR programs in real time. To residential consumers, this framework will 1) provide easy-to-use smart energy management solution, 2) distribute financial rewards by their quantified contribution in DR events, and 3) maintain residents’ comfort-level expectations based on their energy usage preferences. To LSEs, this framework can 1) aggregate residential demand to enhance system reliability, stability and efficiency, and 2) minimize the total reward costs for executing incentive based DR programs. Since this framework benefits both load serving entities and residents, it can stimulate the potential capability of residential appliances enrolled in incentive based DR programs. Eventually, with the growing number of DR participants, this framework has the potential to be one of the most vital parts in providing effective demand-side ancillary services for the entire power system

The Creation, Validation, and Application of Synthetic Power Grids

Public test cases representing large electric power systems at a high level of fidelity and quality are few to non-existent, despite the potential value such cases would have to the power systems research community. Legitimate concern for the security of large, high-voltage power grids has led to tight restrictions on accessing actual critical infrastructure data. To encourage and support innovation, synthetic electric grids are fictional, designed systems that mimic the complexity of actual electric grids but contain no confidential information. Synthetic grid design is driven by the requirement to match wide variety of metrics derived from statistics of actual grids. The creation approach presented here is a four-stage process which mimics actual power system planning. First, substations are geo-located and internally configured from seed public data on generators and population. The substation placement uses a modified hierarchical clustering to match a realistic distribution of load and generation substations, and the same technique is also used to assign nominal voltage levels to the substations. With buses and transformers built, the next stage constructs a network of transmission lines at each nominal voltage level to connect the synthetic substations with a transmission grid. The transmission planning stage uses a heuristic inspired by simulated annealing to balance the objectives associated with both geographic constraints and contingency reliability, using a linearized dc power flow sensitivity. In order to scale these systems to tens of thousands of buses, robust reactive power planning is needed as a third stage, accounting for power flow convergence issues. The iterative algorithm presented here supplements a synthetic transmission network that has been validated by a dc power flow with a realistic set of voltage control devices to meet a specified voltage profile, even with the constraints of difficult power flow convergence for large systems. Validation of the created synthetic grids is crucial to establishing their legitimacy for engineering research. The statistical analysis presented in this dissertation is based on actual grid data obtained from the three major North American interconnects. Metrics are defined and examined for system proportions and structure, element parameters, and complex network graph theory properties. Several example synthetic grids are shown as examples in this dissertation, up to 100,000 buses. These datasets are available online. The final part of this dissertation discusses these specific grid examples and extensions associated with synthetic grids, in applying them to geomagnetic disturbances, visualization, and engineering education

Situational Intelligence for Improving Power System Operations Under High Penetration of Photovoltaics

Nowadays, power grid operators are experiencing challenges and pressures to balance the interconnected grid frequency with rapidly increasing photovoltaic (PV) power penetration levels. PV sources are variable and intermittent. To mitigate the effect of this intermittency, power system frequency is regulated towards its security limits. Under aforementioned stressed regimes, frequency oscillations are inevitable, especially during disturbances and may lead to costly consequences as brownout or blackout. Hence, the power system operations need to be improved to make the appropriate decision in time. Specifically, concurrent or beforehand power system precise frequencies simplified straightforward-to-comprehend power system visualizations and cooperated well-performed automatic generation controls (AGC) for multiple areas are needed for operation centers to enhance. The first study in this dissertation focuses on developing frequency prediction general structures for PV and phasor measurement units integrated electric grids to improve the situational awareness (SA) of the power system operation center in making normal and emergency decisions ahead of time. Thus, in this dissertation, a frequency situational intelligence (FSI) methodology capable of multi-bus type and multi-timescale prediction is presented based on the cellular computational network (CCN) structure with a multi-layer proception (MLP) and a generalized neuron (GN) algorithms. The results present that both CCMLPN and CCGNN can provide precise multi-timescale frequency predictions. Moreover, the CCGNN has a superior performance than the CCMLPN. The second study of this dissertation is to improve the SA of the operation centers by developing the online visualization tool based on the synchronous generator vulnerability index (GVI) and the corresponding power system vulnerability index (SVI) considering dynamic PV penetration. The GVI and SVI are developed by the coherency grouping results of synchronous generator using K-Harmonic Means Clustering (KHMC) algorithm. Furthermore, the CCGNN based FSI method has been implemented for the online coherency grouping procedure to achieve a faster-than-real-time grouping performance. Last but not the least, the multi-area AGCs under different PV integrated power system operating conditions are investigated on the multi-area multi-source interconnected testbed, especially with severe load disturbances. Furthermore, an onward asynchronous tuning method and a two-step (synchronous) tuning method utilizing particle swarm optimization algorithm are developed to refine the multi-area AGCs, which provide more opportunities for power system balancing authorities to interconnect freely and to utilize more PV power. In summary, a number of methods for improving the interconnected power system situational intelligence for a high level of PV power penetration have been presented in this dissertation