Energy Analyzer Emulation for Energy Management Simulators

  • Luis GomesEmail author
  • Zita Vale
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 620)


The simulation of microgrids to testing and validate energy management methodologies are an important step to take before the massive implementation of microgrids. However, microgrids are usually unavailable for R&D centers to perform tests and validations. To solve this issue is important to get the simulations closer to the reality, using real energy analyzers and loads. However, again, R&D centers lack from funding and space to buy and mount several loads in their laboratories. To solve this issue, this paper proposes a multi-agent system simulator for microgrids and an energy analyzer emulator that can be used to emulate individual loads or entire houses, and therefore, bringing the pure simulation closer to the reality.


Energy analyzer emulator Forecasting Load emulation Multi-agent system 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1. Klessmann, C., Held, A., Rathmann, M., Ragwitz, M.: Status and perspectives of renewable energy policy and deployment in the European Union—What is needed to reach the 2020 targets?. In: Energy Policy, Volume 39, Issue 12, pp.7637–7657 (2011)Google Scholar
  2. 2. Washom, B., Dilliot, J., Weil, D., Kleissl, J. Balac, N. Torre, N., Richter, C.: Ivory Tower of Power: Microgrid Implementation at the University of California, San Diego. In: IEEE Power and Energy Magazine, vol. 11, no. 4, pp. 28–32 (2013)Google Scholar
  3. 3. Tsui, K.M., Chan, S.C.: Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing. In: IEEE Transactions on Smart Grid, vol. 3, pp. 1812–1821 (2012)Google Scholar
  4. 4. Fu, Q., Montoya, L. F., Solanki, A., Nasiri, A., Bhavaraju, V., Abdallah, T., Yu, D.C.: Microgrid Generation Capacity Design With Renewables and Energy Storage Addressing Power Quality and Surety. In: IEEE Transactions on Smart Grid, vol. 3, no. 4 (2012)Google Scholar
  5. 5. Dou, C., Lv, M., Zhao, T., Ji, Y., Li, H.: Decentralised coordinated control of microgrid based on multi-agent system. In: IET Generation, Transmission & Distribution, vol. 9, no. 16, pp. 2474–2484 (2015)Google Scholar
  6. 6. Vale, Z., Pinto, T., Praça, I., Morais, H.: MASCEM: Electricity Markets Simulation with Strategic Agents. In: IEEE Intelligent Systems, vol. 26, no. 2, pp. 9–17 (2011)Google Scholar
  7. 7. Silva, M., Morais, H., Sousa, T., Faria, P., Vale, Z.: Time-horizont distributed energy resources scheduling considering the integration of real-time pricing demand response. In: IEEE Eindhoven PowerTech, Eindhoven, pp. 1-6 (2015)Google Scholar
  8. 8. Vinagre, E., Gomes, L., Vale, Z.: Electrical Energy Consumption Forecast Using External Facility Data. In: IEEE Symposium Series on Computational Intelligence, 659–664 (2015)Google Scholar
  9. 9. Wan, C., Zhao, J., Song, Y., Xu, Z., Lin, J., Hu, Z.: Photovoltaic and solar power forecasting for smart grid energy management. In: CSEE Journal of Power and Energy Systems, vol. 1, no. 4, pp. 38–46 (2015)Google Scholar
  10. 10. Habib, H. F., Yossef, T., Cintuglu, M., Mohammed, O.: A Multi-Agent Based Technique for Fault Location, Isolation, and Service Restoration. In: IEEE Transactions on Industry Applications, no.99, pp.1–1(2017)Google Scholar
  11. 11. Rakesh, G., Pindoriya, N. M.: Simulation and experimental study of single phase PWM AC/DC converter for Microgrid application. In: 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi (2016)Google Scholar
  12. 12. Morais, H., Vale, Z., Pinto, T., Gomes, L., Fernandes, F., Oliveira, P., Ramos, C.: Multi-Agent based Smart Grid management and simulation: Situation awareness and learning in a test bed with simulated and real installations and players. In: IEEE Power & Energy Society General Meeting, Vancouver, BC, 2013, pp. 1–5 (2013)Google Scholar
  13. 13. Gomes, L., Silva, J., Faria, P., Vale, Z.: Microgrid demonstration gateway for players communication and load monitoring and management. In: Clemson University Power Systems Conference (PSC), Clemson, SC, 2016, pp. 1–6 (2016)Google Scholar
  14. 14. Gomes, L., Lefrançois, M., Faria, P., Vale, Z.: Publishing real-time microgrid consumption data on the web of Linked Data. In: 2016 Clemson University Power Systems Conference (PSC), Clemson, SC, pp. 1–8 (2016)Google Scholar
  15. 15. Canizes, B., Silva, M., Faria, P., Ramos, S., Vale, Z.: Resource scheduling in residential microgrids considering energy selling to external players. In: 2015 Clemson University Power Systems Conference (PSC), Clemson, SC, pp. 1–7 (2015)Google Scholar
  16. 16. Gomes, L., Abrishambaf, O., Faria, P., Vale, Z.: Retrofitting Approach for an Automated Load Testbed. In: ELECON Workshop – Dissemination & Transfer of knowledge (2016)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Engineering – Polytechnic of Porto (ISEP/IPP)GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innova-tion and DevelopmentPortoPortugal

Personalised recommendations