![]() ![]() Since smart grids rely on a communication network and smart meters, they may be vulnerable to cyber attacks. ![]() None of these papers are concerned with the security of the respective systems. Īlthough those solutions are becoming more sophisticated, the smart grid can only be realised once appropriate security measures are in place. More generally, comprehensive reviews reveal the significant contribution that game-theoretic solutions offer in terms of reducing consumer costs and PAR values. Alternatively, usage of a Stackelberg game minimising both the PAR and the system total cost has also proved promising. Some consider advanced battery models and integrate forecasting errors. ![]() In particular, dynamic game-theoretic frameworks have been proposed to optimise energy cost using their Nash equilibrium. Taking advantage of smart meters, energy storage, and trading strategies, a variety of energy consumption scheduling techniques aiming at optimally distributing daily power consumption have been put forward to reduce a smart grid’s peak-to-average ratio (PAR) of the aggregated load. Efficient management of these microgrids requires a two-way communication system between suppliers and consumers, so that those smart grids can exploit distributed information for storage scheduling and pricing purposes. Accordingly, the concept of ‘microgrids’ was introduced to facilitate distribution by dividing the power grid into several smaller local grids. Furthermore, local electricity generation reduces substantially power dissipation and transmission costs. For instance, storing energy during off-peak times eases supply during peak hours where there is high demand. Advancements in energy storage and renewable energy generation provide further opportunities to devise smarter and efficient power grids. Traditional Demand-Side Management has designed strategies to change consumers’ consumption patterns so that they better match energy generation profiles: these include peak clipping, load shifting, and flattening consumers’ loads. Therefore, management of consumption and production plays a crucial role to facilitate power distribution as well as reduction in cost for both suppliers and consumers. However, their inherent intermittency and unpredictability make their integration into the power grid particularly difficult. On the other hand, with the increase in greenhouse gases that impact negatively on the Earth’s ecosystem, better exploitation of renewable energy sources is seen as a way to reduce their emissions. This is an expensive solution as some of those resources are only exploited sporadically. Indeed, since electricity suppliers must meet customers’ demand during peak hours, they traditionally invest in power generation capacity able to sustain those high power consumption periods. The practical outcomes of these results for the utility company are discussed in detail, and a proposal is made, suggesting how the generic model may be applied to other scenarios.ĭuring the last decade, the rise of the smart grid has shown significant potential to address not only the traditional grid problems but also support the development of power generation from renewable sources. Informed by these findings, a generic security game is devised and solved, revealing the existence of several Nash equilibrium strategies. Monitoring strategies that the utility company may employ in order to detect the attacks are proposed, and a game-theoretic approach is used to support the utility company’s decision-making process for the allocation of their defence resources. The existence of a novel class of false data injection attacks that are based on modifying forecasted demand data is demonstrated, and the impact of the attacks on a typical system’s parameters is identified, using a simulated scenario. This paper is concerned with the security of energy management systems which are expected to be implemented in the future smart grid. The introduction of advanced communication infrastructure into the power grid raises a plethora of new opportunities to tackle climate change. ![]()
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