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On the deployment of Virtual Power Plants

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A Virtual Power Plant (VPP) is a concept derived from the ‘Virtual Utility’ metaphor used by Awerbuch and Preston [1] in the late 1990’s to describe the aggregation of distributed energy generators and consumers typically located in the distribution network of the grid. The key challenges identified by [2,3] are as follows (with my comments):

  • A clear definition of the key characteristics of the control interface exported by distributed energy resources (DER), which could be generators or controllable loads. How could such interfaces lead to portfolios of DERs be defined for the overarching CVPPs (Commercial VPPs) and TVPPs (Technical VPPs)?

    A possible answer to this would probably be to produce a clear ontology and a language to express the capabilities of the DERs and their feasible connections and conflicts. Does an ontology already exist to express DER capabilities and controllability? What would be the best formalism to express the feasible associations/conflicts among the DERs? Representations of plans (e.g., TAEMS) for multi-agent teamwork come to mind as these have been used to express such issues in very dynamic and uncertain settings (military – the COORDINATORS programme)
    as in the smart grid.
  • Distribution energy management – i.e., how to make sure the energy produced or used in the distribution network is properly managed to avoid overloading lines and keep voltage levels stable.

    The authors in [2] show, using optimal power flow equations, how the output from a VPP can be significantly affected by the conditions on the network. Power ouput may have to be severely curtailed by the distribution system operator (DSO) who would be mimicking the role of a TSO (transmission network operator) as it is on the tranmission network at the moment. Wouldn’t this unravel as the number of DERs scales to hundreds of thousands as consumers start using smart meters and solar panels in their home? The challenge would be to design distributed control mechanisms to ensure lines are not going to be overloaded as a result of (un)-coordinated actions (production/consumptions) by individuals.

  • Providing a commercial and regulatory framework – i.e., how to ensure the energy produced/consumed is paid for/billed for exactly.
    Aggregating resources technically is a different challenge from the commercial aggregation given that each individual resource is potentially owned by a different company which will try to maximise its profits. It seems, so far, that each DER will only get paid for what it produces at the end of the day, no matter what the others in the VPP produce. However, this is not entirely sane given that each DER is serving to compensate for others’ inability to produce at certain times as pointed at in [3]. Given the increasing heterogeneity of DERs, it can be expected that the negotiation power of some of these bigger/more reliable DERs will push others to share parts of their earnings with them. This points to the need to devise payoff sharing mechanisms that users are comfortable with. Cooperative game theory points to different ways of doing this through solution concepts such as the Core/Kernel/Shapley value but these tend to be intractable or rely on some simplifying assumptions about the actors’ utility functions. In the smart grid, solution concepts that are computable in real-time will be needed.

  • Providing the communication platform for all the components of the VPP to talk to each other.
    Since the VPP is likely to be composed of lots of individual actors it is important to design the communication infrastructure such that it is robust to failures but also to delays in comms. Conversely, the decision making algorithms of individual components would need to be able to manage any latency or failure in the communication infrastructure in order to guarantee stability.

 

[1] Awerbuch, S. and Preston, A.M., (1997) “The virtual utility: Accounting, technology \& competitive aspects of the emerging industry”, Kluwer Academic Pub.

[2] Pudjianto, D.; Ramsay, C.; Strbac, G.; , “Virtual power plant and system integration of distributed energy resources,” Renewable Power Generation, IET , vol.1, no.1, pp.10-16, March 2007 , URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4159950&isnumber=4159947

[3] Dimeas, A.L.; Hatziargyriou, N.D.; , “Agent based control of Virtual Power Plants,” Intelligent Systems Applications to Power Systems, 2007. ISAP 2007. International Conference on , vol., no., pp.1-6, 5-8 Nov. 2007 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4441671&isnumber=4441582

Written by agentsinthesmartgrid

February 15, 2011 at 10:25 am

Posted in microgrids