This paper proposes two decentralised, secure and privacy-friendly protocols for local electricity trading and billing, respectively. The trading protocol employs a bidding algorithm based upon secure multiparty computations and allows users to trade their excess electricity among themselves. The bid selection and calculation of the trading price are performed in a decentralised and oblivious manner. The billing protocol is based on a simple privacy-friendly aggregation technique that allows suppliers to compute their customers' monthly bills without learning their fine-grained electricity consumption data. We also implemented and tested the performance of the trading protocol with realistic data. Our results show that it can be performed for 2500 bids in less than five minutes in the on-line phase, showing its feasibility for a typical electricity trading period of 30 minutes.
Rahman et al. @cite_4 proposed a secure bidding protocol for incentive-based demand response system. However, their protocol is not fully privacy-friendly as the bidding manager, acts like a trusted party and learns all users' bids. Kounelis et al. @cite_18 introduced a platform named Helios that allows users to exchange energy in a decentralised manner using a blockchain technology and smart contracts. Uludag et al. @cite_24 proposed a distributed bidding system where only the winning bidder is disclosed to a service provider, whereas the bids of the other bidders are kept private. The same authors extended their solution to facilitate multi-winner auction mechanism @cite_46 . Although these solutions provide security and verifiability as they are based on the blockchain technology, they do not fully address users' privacy concerns as transactions could be traced and linked to users.
@cite_24 @cite_18 @cite_4 @cite_46
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One of the the most propitious enablers of the Smart Grid paradigm, and a rather low-hanging fruit, is Demand Response (DR) programs. DR is a set of courses of actions to reach and maintain the supply-demand equilibrium of the power grid from the side of the demand through price or incentive-based routines. The latter includes many programs with some bidding component. The general consensus among the experts is that the impact of the benefits is multiplied as DR program participation from the consumption side increases. However, there is an increasing awareness in public about privacy implications of many technological implementations including SG and DR deployments. In this paper, we are proposing a fully private bidding mechanism as part of a DR program to protect all the bidding details except for the winning price and winner at the end of the auction. To the best of our knowledge, ours is the first approach in the literature that accomplishes full privacy in a DR program without relying on a trusted third party. Preliminary simulation results show that the proposed mechanism presents a feasible solution for day-ahead and hour-ahead bidding mechanisms in the SG. Micro-generation promises to greatly contribute to the energy balance of the energy grid; however, so far, its market penetration is going slow due to the few, or not-existing, direct economic benefits end-users would enjoy by deploying an in-house micro-generation system. In this paper, taking advantage of the potentialities of blockchain technologies, we propose a solar energy production and distribution architecture using smart contracts, a particular distributed ledger paradigm, to support automatic energy exchanges and auctions, potentially enabling a new, open and more fruitful, under an end-user perspective, energy micro-generation market. We present the conceptual design of the approach, as well the energy grid prototype and the control layer, running on the Ethereum platform. The proposed architecture has been implemented and validated through an in-house developed test-bed. Abstract The smart grid, as an emerging cyber-physical system, is attractive because of features such as distributed energy control and robust load fluctuation management. The demand Response (DR) component in smart grids helps in maintaining demand-supply balance and in controlling consumer side electricity bills. One of the visions of smart grids is to have communication between consumers and suppliers facilitate certain types of DR strategies, e.g., demand bidding (DR-DB). DR-DB is an incentive-based DR, where certain incentives are awarded to consumers who participate in DR events. However, privacy and security in the DR-DB bidding process are of paramount importance as potentially sensitive consumer data is used during the process. In this paper, we propose a private and secure bidding protocol for incentive-based demand-response systems using cryptographic primitives without assuming any trusted third-party. We analyze the security and privacy guarantees; and show that the various stages in our proposed demand bidding are computationally feasible, in terms of cryptographic primitives, through performance evaluation on three different computing environments. The stringent requirement of the demand-supply equilibrium for delivering electricity has traditionally been dealt with a supply-side perspective, assuming that the demand is not alterable. With the promises of the smart grid, demand-side management techniques are increasingly becoming more feasible. A demand-side management technique, called demand response (DR), aims at inducing changes in electricity load in response to financial incentives, some of which involve bidding as the underlying facilitator. It is well-established that the effectiveness of the DR is proportional to the number of participants. Yet, many of the DR programs, including those involving bidding, may suffer due to consumer privacy concerns. Within this context, in this paper, we propose a distributed and multi-unit privacy guaranteeing bidding mechanism as part of a DR program without relying on any third party, trusted or not, to protect the participants’ bidding information, except obviously for the winning price and the winner exposed to the utility. To the best of our knowledge, this is the first such approach for the DR bidding programs. We provide a security analysis of our approach under the honest-but-curious and active adversary assumptions and prove the privacy assuring property.