A Real-Time Dynamic Pricing Algorithm for Smart Grid With Unstable Energy Providers and Malicious Users

Tang, Qiang; Yang, Kun; Zhou, Dongdai; Luo, Yuansheng; Yu, Fei

doi:10.1109/jiot.2015.2452960

Cited by 62 publications

(37 citation statements)

References 15 publications

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“…[37] examined the effect of energy storage on the SG in terms of global social welfare, considering that agents have homogeneous efficiency and running costs. The work in [26,53] shows mechanisms for social welfare calculations in a DR environment.…”

Section: Auctions In the Electricity Systems And The Preston Mcafeementioning

confidence: 99%

“…A common aspect in [10,16,19,26,37,[52][53][54] is that they do not take into account the welfare of the utility company itself. It is evident that a great part of the social welfare losses in current applications lie with the utility companies, as they are resistant against energy trade from local prosumers in decentralized generation structures.…”

Section: Auctions In the Electricity Systems And The Preston Mcafeementioning

confidence: 99%

“…Pricing freedom is fully guaranteed in [3,34]. In [53], a power market scheduling center (PMSC) is proposed, which manages all the energy providers and makes them provide a unified price to the subscribers, and energy providers generate the optimal quantity of electricity to get maximum utilities. In [41], aggregators provide DR services to the operator and guarantee a reduced electricity bill to the end users, negotiating with both sides in order to maximize its own profit.…”

Section: Comparison With the State-of-the-art Privacy And Trading Sysmentioning

confidence: 99%

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Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks

Milanezi

Costa

Garcez

et al. 2020

Sensors

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Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user's electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers' identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms of data security, we adopt the Advanced Encryption Standard (AES) 128 bit with Exclusive-OR (XOR) keys due to their reduced computational complexity, allowing fast processing. Our framework outperforms the state-of-the-art solutions in terms of privacy protection and trading flexibility in a prosumer-to-prosumer design.2 of 25 consists of obfuscating the instantaneous consumption pattern of each consumer [5,6]. This is generally accomplished by hiding the instantaneous power consumption of the client as fine-grained data can reveal in detail the lifestyle of the consumer [7,8]. However, the profile of traded energy also delivers relevant information about prosumers to their neighbors. As in [9], the ability to link the bids to individual consumers allows the untrusted entity to build up a profile of the consumer's behavior. In particular, the quantities of traded energy can be very informative about the economical welfare of the owner [10]. Privacy requirements dictate that prosumers cannot gain information regarding other prosumers' consumption and production-not even if they are trade partners [11]. Models dealing with energy trade directly among prosumers [3,12] limit themselves to exploiting the trade environment without discussing in detail data-security aspects related to the identities of the traders in relation to their neighbors. As a consequence, several topics related to privacy requirements are still open in SGs, such as power production and bidding in trading systems.In this paper, we consider the problem of providing data privacy for self-interested players that trade energy in the context of a Neighborhood Area Network (NAN). The energy is sold by local micro-generators and locally purchased by their neighbors, also known as the final users. Our framework deals simultaneously with SG data-security requirements and energy-trade systems. As a first contribution, the proposed framework has a privacy-preserving model which has a low computational complexity and avoids completely an unauthorized party to identify the bidders, ...

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Section: Auctions In the Electricity Systems And The Preston Mcafeementioning

confidence: 99%

Section: Auctions In the Electricity Systems And The Preston Mcafeementioning

confidence: 99%

Section: Comparison With the State-of-the-art Privacy And Trading Sysmentioning

confidence: 99%

See 1 more Smart Citation

Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks

Milanezi

Costa

Garcez

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…In real life, the load power capacity of one power supplier cannot meet the demand of multiple users, therefore, multiple power suppliers are required to provide sufficient power for users [15]. We consider smart grid with multiple power suppliers and multiple users.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Moreover, some literatures consider the irrational behavior of users and power suppliers. Therefore, the authors proposed the Mechanism of Identification and Processing (MIP) to identify and process malicious users and unstable power suppliers in the case of multiple power suppliers and users, and designed heuristic algorithm to solve problems in [15]. However, the maximum consumption of malicious users is replaced with the average amount of power consumption of non-malicious as punishment and the penalty is relatively small.…”

Section: Introductionmentioning

confidence: 99%

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Li¹,

Dai²,

Gao³

2019

Proceedings of the 1st International Conference on Business, Economics, Management Science (BEMS 2019)

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In the smart grid, users, power suppliers and Power Market Scheduling Center are the main participants. In view of the increasing demand response ability of users, an identification mechanism of punishing malicious users and unstable power providers while incenting nonmalicious users is proposed, and an optimization model to maximize social welfare is considered to study the real-time pricing problem in smart grid managed by PMSC. The model is analyzed by Lagrange dual method and finally solved by heuristic algorithm to obtain the optimal electricity price and power demand. The simulation results show that the algorithm can converge well and the reliability and stability of power system are optimized under the dual regulation of penalty and incentive. In addition, there is a positive correlation between the incentive factor and users' utility and social welfare within proper range.

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Retracted: Distributed buildings energy storage charging load forecasting method considering parallel deep learning model

Yang

Qin

et al. 2019

Concurrency and Computation

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At present, with total building energy consumption accounts for about 21.33% of the energy consumption of social terminals, the building energy consumption has a tendency to continue to grow. According to the geographical location of users and the local weather conditions, we analyze the energy resources available to users and design a multienergy complementary coupling system. We have taken full account of the use of renewable energy and recovery of waste heat resources. Large-scale increase of electrical equipment, a large number of charging load access to the grid, the power system planning, operation and operation of the electricity market will have a profound impact. The current mode of the supercapacitor and the DC bus determines the mode of operation of the converter. Based on a detailed analysis of each working mode, we design a corresponding control scheme and achieve a smooth transition and switching between modes. Simulation and experiment verify the correctness and effectiveness of the converter and hybrid energy storage control strategy. KEYWORDSbuilding energy, distributed system, energy storage, load forecast, parallel architecture INTRODUCTIONEnergy, as an important material condition for further development of human society, is also a key factor restricting politics, economy, and military. It is because of the reliable guarantee of energy that our economy can be stable and sustainable. Since the middle of the last century, especially since this century, China's energy development and people's increasing demand for energy improve the energy supply ability for the sustained and rapid development of economy, providing strong protection. However, in the whole development process, we still face the huge challenge of increasing energy bottleneck and increasing environmental pollution pressure. In order to ensure the regular supply of energy and the sustainable development of economy, China has introduced a series of policies to adjust the energy field. Since the beginning of this century, there has been changes in new energy supply situation, like lots of energy-intensive industry development, the demand for energy in the unprecedented rapid expansion trend of the development of economy and once again into the restriction condition. As the advancement of modern society and the continuous improvement of people's living standard, demand for energy will also be rising, the contradiction between energy supply and demand as well as energy resources and environment restriction will continue to exist for a long time. There is no doubt that China's energy development is facing more and more serious challenges, and the contradiction between the shortage of energy and the inefficient use of the end is becoming more and more prominent. [1][2][3] With the rapid development of urbanization, building energy consumption accounting for social goods continues to increase the proportion of the total energy consumption and is on the normal work of the national economy development and people's life, the influence of which...

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A Real-Time Dynamic Pricing Algorithm for Smart Grid With Unstable Energy Providers and Malicious Users

Cited by 62 publications

References 15 publications

Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks

Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Retracted: Distributed buildings energy storage charging load forecasting method considering parallel deep learning model

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