=Paper=
{{Paper
|id=None
|storemode=property
|title=Desiderata for Agent-Based Power Regulation Protocols in Smart Grids
|pdfUrl=https://ceur-ws.org/Vol-918/111110438.pdf
|volume=Vol-918
|dblpUrl=https://dblp.org/rec/conf/at/MihailescuVO12a
}}
==Desiderata for Agent-Based Power Regulation Protocols in Smart Grids==
https://ceur-ws.org/Vol-918/111110438.pdf
Desiderata for Agent-Based Power Regulation Protocols
in Smart Grids ?
Radu-Casian Mihailescu, Matteo Vasirani and Sascha Ossowski
{raducasian.mihailescu, matteo.vasirani, sascha.ossowski} @urjc.es
Abstract. In this work we focus on one particular area of the smart grid, namely,
the challenges faced by distribution network operators in securing the balance be-
tween supply and demand in the intraday market. Typically, the intraday market is
used as a mechanism for coping with various unplanned operational incidents that
may arise in the grid. It is anticipated that it will gain even more significance, as a
growing number of load controllable devices and small-scale, intermittent gener-
ators coming from renewables are expected to pervade the system. On one hand,
this means that the task of managing the network efficiently becomes increasingly
complex and stochastic due to the large number of decentralized autonomous ac-
tors embedded in the network. On the other hand, their dynamic adaptability and
capability to conform to higher volatility can lead towards compelling solutions.
In this position paper we propose a set of desiderata for a multi-agent design to
facilitate coordinating the various actors and alleviate these drawbacks.
As the network is becoming more reliant on the power generated by DERs, the role of the
balancing market is expected to gain significant importance. The goal is then to maximise the
usage of clean energy upon its availability and maintain the delicate balance between supply and
demand in real-time. In order to do so, demand should be able to adapt to the volatility in supply
and periods of high demand should be synchronized with intervals of higher generation. This can
be made possible assuming that consumers can engage in an online, self-interested negotiation
for shifting loads and thus adapting their demand. The problem is far from being trivial as the
system is ought to react in real-time to sudden changes of the aggregated generation profile in
order to balance supply from intermittent renewable resources, while complying with consumer
requirements. In the following, we give a list of prerequisites for a novel multi-agents design,
with a brief explanation for each:
• Decentralization. The benefits of applying the multi-agent systems paradigm as an approach
for distributed control of the Grid entails primarily: autonomy, scalability, flexibility, exten-
sibility, fault tolerance and reduced maintenance [Rob04]. The actors existing in the grid (i.e.
consumer loads, distributed generators) represent different owners with particular, possibly
conflicting user goals and behaviors hence, deploying an agent-based distributed control over
the system becomes highly suitable for such a scenario. Moreover, decentralization increases
the systems reliability in case of failures, enables local adaptability to dynamic situations at
runtime and allows coordination, as opposed to the more complex task of centralised man-
agement.
• Stability. Fairness. Computational and Communication Simplicity. Once the network
operator determines that a load control action needs to be executed, this information is pub-
lished and becomes available to all actors in the respective region of the grid. Normally,
?
AT2012, 15-16 October 2012, Dubrovnik, Croatia. Copyright held by the author(s).
no actor in the network would be able to handle such a request alone, thus cooperation is
required. For each action request there is a monetary incentive provided by the network op-
erator. This means that another aspect, that needs to be addressed, concerns coming up with
an individually rational and efficient payoff configuration that satisfies a notion of stability.
Here, stability entails that agents have an incentive for behaving in a certain way. The payoff
allocation scheme is resulting from running a negotiation procedure, where agents resched-
ule loads in order to meet the required constraints. It is well known that the classical stability
concepts in coalitional game theory are of high computational complexity [OR94, KG02].
Consequently, considering the real-time constraints, for the payoff distribution, the protocol
should minimize computational and communication demands.
• Dynamic environments. Confronted with the uncertainty regarding both generation and
consumption capacities, the grid operator is running a continuous prediction of both supply
and demand in the near future, in order to prepare for reductions in available supply or high-
peak demand. Thus, it is responsible for compiling production and consumption schedules to
be explicitly passed to the actors in the grid. However, these schedules are volatile in nature,
as they can be influenced by a wide variety of factors (e.g. wind speed, solar irradiance,
consumer patterns, etc.), though their accuracy improves as the time-to-prediction elapses.
Therefore, agents need to be able to reason in advance in this dynamic setting and be capable
to instantiate a solution once such a situation arises.
• Stochastic environments. It is important to note that the agents, representing both con-
sumers and producers of energy in the grid, operate within significant levels of uncertainty.
We aim to model a setting in which we consider the sources of uncertainty to be twofold.
From the agent’s perspective, on one hand the challenge is in accurately predicting its user’s
energy profile and preferences. On the other hand, in order to increase their coordination
efficiency, agents need to build a prediction with regard to the expected behavior of poten-
tial coalition partners. We intend to address both aspects in a unified approach by including
sources of uncertainty in the form of random, uncontrollable variables with probability dis-
tributions, that each agent attempts to learn in an online fashion.
• Privacy-Preserving Layer. Our intended algorithm is run distributively among agents rep-
resenting various actors in the grid, requiring that valuations of different actions to be com-
municated between them. This implies that sensitive information will become distributed
among numerous agents, without transmitting the data to a central (trusted) site. Thus, in or-
der to avoid the possibility of malicious agents attempting to learn other agents’ preference
and potentially gaming the system, our scheme is to incorporate cryptographic primitives in
order to perform secure multi-party computations. Specifically, we look at homomorphic en-
cryption schemes, which make it is possible to perform operations on cyphertexts that trans-
late to operations on the initial cleartext messages, without the need to know the encryption
key. This enables that an agent cannot decrypt any of the individual messages received, but
can however aggregate the messages using the homomorphic property and ask a subset of
the sending agents to help it decrypt the result. Specifically, we are interested in applying an
efficient additive homomorphic encryption scheme.
References
[KG02] M. Klusch and A. Gerber. Dynamic coalition formation among rational agents. IEEE
Intelligent Systems, 17(3):42–47, 2002.
[OR94] M. Osborne and A. Rubinstein. A Course in Game Theory. MIT Press, 1994.
[Rob04] D Roberts. Network management systems for active distribution networks: a feasibil-
ity study. DTI Distributed Generation Programme Contractor SP PowerSystems LTD
Contract Number KEL003100000 URN, 2004.