As traditional energy resources are becoming increasingly scarce and thus more expensive (not to mention their adverse effects on the environment), the efforts towards energy generation from alternative, environmentally friendly resources and smart energy consumption are rapidly becoming concern of governments, industry and academia all over the world. The recent buzz-term smart grid symbolizes this important concept of the efficient generation, distribution and exploitation in case of electrical energy. In brief, smart grid comprises all elements of the electrical grid, but it is much more than just a collection of its parts – it is a dynamic system that interconnects them in a meaningful manner for the benefit of the end users. As such, smart grid heavily relies on communications between consumers, suppliers, smart devices and applications.
Smart grids of the future are envisioned as networks of integrated microgrids – (geographically) localized collections of generators, storage capacities and users (loads) that operate as singly entity with the goal of smart energy exploitation. With respect to this, the centralized approach for the regulation (i.e., control) of microgrid operation imposes itself naturally. However, the decentralized, distributed approach for microgrid control (known as the paradigm of multiagent systems) is a more favorable one, as it is inherently more robust and scalable. Naturally, distributed control should leverage on adequate distributed communication techniques.
A recent issue of IEEE Wireless Communications (Jun 2012), under the topic “Recent advances in wireless technologies for smart grid”, presents a couple of research articles devoted to the wireless communications within microgrid. Particularly, a generalized approach for the multiagent coordination is assessed in [1], investigating the usage of consensus algorithms for distributed dissemination of information among the agents. The idea behind consensus algorithms is a simple one – series of local exchanges among the agents should result with each agent having the same insight into the global network parameters (in other words, communicating only locally spreads information globally – a well-known phenomenon in the social networks). In turn, this allows agents to separately apply the control algorithms using the same data, harmonizing their operation to achieve the optimal performance of microgrid. As the actual communication technology, the authors suggest use of WiFi (IEEE 802.11) or ZigBee (IEEE 802.15.4). The above generalized approach can be applied to a number of issues in smart grid operation, such are:
- Economic dispatch problem,
- Decentralized invertor problem,
- Fault detection and recovery,
- Agent clock synchronization (when GPS is not used),…
Economic dispatch
A related article [2] gives a nice analysis of the economic dispatch problem when the impact of communications is included. Economic dispatch [3] is a short-term determination of the optimal output of a number of electricity generation facilities to meet the system load at the lowest possible cost, while serving power to the public in a robust and reliable manner. The authors of [2] develop a plausible cost model which, besides generation costs, cost of purchasing power and cost of generating extra power, includes both the communication costs and the impact of communication errors on the possible deviation of system operation from the optimum. It is shown that the use of distributed consensus algorithms can in general steer the system operation towards the optimum. Further, it is shown that use of communication links that interconnect distant agents (which are not directly connected by WiFi/Zigbee links) can speed up the convergence to the desired state of optimal operation, lowering the total cost. On the other hand, these “global” links are provided using cellular communications, which increases communications costs and thus increases the total costs; the overall result being that the amount of cellular link usage should be carefully selected.
Although these initial research efforts are promising, a lot remains to be done. The impact of wireless communications impairments on microgrid operation is still not adequately addressed nor experimentally verified. With respect to the latter, it remains to be seen how effectively will WiFi/ZigBee networks (which are almost exclusively operating in a star/tree topology) support the execution of the distributed consensus algorithms.
[1] H. Liang et al, “Multiagent Coordination in Microgrids via Wireless Networks”, IEEE Wireless Communications, Jun 2012
[2] H. Liang et al, “Decentralized Economic Dispatch in Microgrids via Heterogeneous Wireless Networks”, IEEE Journal on Selected Areas In Communications, July 2012
[3] http://en.wikipedia.org/wiki/Economic_dispatch
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