Klaas De Craemer

An Event-Driven Dual Coordination Mechanism for Demand Side Management of PHEVs

This paper addresses the challenges of integrating existing PHEV charging algorithms, which optimize PHEV charging per market timeslot (e.g., 15 minutes), into an environment with realistic communication conditions. To address this challenge, we propose a dual coordination mechanism, which controls a cluster of devices on two different operation levels: market operation and real-time operation. The market operation level uses an existing timeslot-based algorithm to calculate a charging schedule per timeslot. The real-time operation level translates this schedule into event-based control actions for a realistic communication environment, wherein a limited number of messages can be exchanged. A case study of 1000 PHEVs shows that it is possible to achieve results on par with the timeslot based algorithm but with significantly reduced communication with the PHEVs.

Communication overlays and agents for dependable smart power grids

Smart grids rely on a dependable information infrastructure for the monitoring and control applications. Two elements can enhance the suitability of the communication and control infrastructure for such smart grid applications. Overlay networks allow to resiliently deal with nodes that appear and disappear, as well as with the dynamic nature of the power values these nodes represent in a smart grid. Agents-based modelling allows to simulate the smart grid applications in a scalable and flexible way before deployment. The paper discusses how both approaches can be combined for simulating a more dependable smart grid.

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

ABSTRACT The charging of electric vehicles (EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid (e.g., under-voltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with event-driven control at the operational level. Different case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

Smart meters from the angles of consumer protection and public service obligations

Digital meters for electricity and gas, which are connected to an information infrastructure are an important component of the smart metering and smart grid infrastructure being deployed. Besides technical and business perspectives, such infrastructure has an impact on the consumer and on authorities that have public service obligations. This paper discusses those elements, also in the context of the assessment that is needed for the European directives 2009/72/EC and 2009/73/EC. It positions smart meters with respect to energy savings and outlines requirements for relevant cost / benefit analyses.

Integration of Distribution Grid Constraints in an Event-Driven Control Strategy for Plug-in Electric Vehicles in a Multi-Aggregator Setting

In literature, several mechanisms are proposed to prevent Plug-in Electric Vehicles (PEVs) from overloading the distribution grid [1]. However, it is unclear how such technical mechanisms influence the market level control strategies of a PEV aggregator. Moreover, the presence of multiple aggregators in the same distribution grid further complicates the problem. Often, grid congestion management mechanisms are proposed to solve the potential interference between the technical and market objectives. Such methods come at the expense of additional complexity and costs, which is not beneficial for the large scale application of demand response. In our work, we investigate this problem by combining a simple low level voltage droop controller with an event driven control strategy for the coordination of charging PEVs. The approach is evaluated in different distribution grid settings, using two different market objectives for the aggregator.

An approach towards socially acceptable energy saving policies via monetary instruments on the smart meter infrastructure

Energy savings are required, and behavioural change is a good guarantee for this. This paper presents an interdisciplinary four-step approach towards such energy savings. It is based on two types of monetary instruments (white certificates and complementary currencies), that make use of the smart meter infrastructure as a measurement platform for assessing the realised energy savings. A social component ensures that the system design will be accepted by the public at large.

Charging Electric Vehicles in the Smart Grid

High level challenges that motivate the evolution towards smart grids include (i) the anticipated electrification of transportation, including electrical vehicles (EVs), and (ii) the increasing penetration of distributed renewable energy sources (DRES). This chapter will discuss how the extra grid load stemming from the EVs can be handled, including the context of reduced control over power generation in light of DRES adoption (especially solar and wind power). After a basic introduction to common EV charging technology, we give two illustrative examples of controlling EV charging: avoiding peaks, and balancing against renewable generation. We then qualitatively present possible demand response (DR) strategies to realize such control. Finally, we highlight the need for, and underlying principles of, (smart grid) simulation tools, e.g., to study the effectiveness of such DR mechanisms.