Pricing schemes are an important smart grid feature to affect typical energy usage behavior of energy users (EUs). However, most existing schemes use the assumption that a buyer pays the same price per unit of energy to all suppliers at any particular time when energy is bought. By contrast, here a discriminate pricing technique using game theory is studied. A cake cutting game is investigated, in which participating EUs in a smart community decide on the price per unit of energy to charge a shared facility controller (SFC) in order to sell surplus energy. The focus is to study fairness criteria to maximize sum benefits to EUs and ensure an envy-free energy trading market. A benefit function is designed that leverages generation of discriminate pricing by each EU, according to the amount of surplus energy that an EU trades with the SFC and the EU's sensitivity to price. It is shown that the game possesses a socially optimal, and hence also Pareto optimal, solution. Further, an algorithm that can be implemented by each EU in a distributed manner to reach the optimal solution is proposed. Numerical case studies are given that demonstrate beneficial properties of the scheme.
Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
Singapore University of Technology and Design（新加坡科技设计大学）；State Key Lab. of Industrial Control Technology, Zhejiang University（浙江大学工业控制技术国家重点实验室）；NICTA（澳大利亚国家信息技术研究中心）；School of Engineering and Applied Science, Princeton University（普林斯顿大学工程与应用科学学院）
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
University of Queensland（昆士兰大学）；Singapore University of Technology and Design (SUTD)（新加坡科技设计大学）；University of California at Riverside（加州大学河滨分校）；Princeton University（普林斯顿大学）
This paper proposes a peer to peer (P2P), blockchain based energy trading market platform for residential communities with the objective of reducing overall community peak demand and household electricity bills. Smart homes within the community place energy bids for its available distributed energy resources (DERs) for each discrete trading period during a day, and a double auction mechanism is used to clear the market and compute the market clearing price (MCP). The marketplace is implemented on a permissioned blockchain infrastructure, where bids are stored to the immutable ledger and smart …
The advancements in smart power grid and the advocation of ``green communications'' have inspired the wireless communication networks to harness energy from ambient environments and operate in an energy-efficient manner for economic and ecological benefits. This article presents a contemporary review of recent breakthroughs on the utilization, redistribution, trading and planning of energy harvested in future wireless networks interoperating with smart grids. This article starts with classical models of renewable energy harvesting technologies. We embark on constrained operation and optimizati…
Prioritizing Consumers in Smart Grid: A Game Theoretic Approach
Singapore University of Technology and Design（新加坡科技设计大学）；Australian National University（澳大利亚国立大学）；NICTA（国家信息通信技术研究中心）；CSIRO Computational Informatics（联邦科学与工业研究组织计算信息学部门）；Princeton University（普林斯顿大学）
The current trend towards more renewable and sustainable energy generation leads to an increased interest in new energy management systems and the concept of a smart grid. One important aspect of this is local energy trading, which is an extension of existing electricity markets by including prosumers, who are consumers also producing electricity. Prosumers having a surplus of energy may directly trade this surplus with other prosumers, which are currently in demand. In this paper, we present an overview of the literature in the area of local energy trading. In order to provide structure to th…
Energy Management for a User Interactive Smart Community: A Stackelberg Game Approach
Singapore University of Technology and Design（新加坡科技设计大学）；State Key Lab. of Industrial Control Technology, Zhejiang University（浙江大学工业控制技术国家重点实验室）；NICTA（澳大利亚国家信息与通信技术学院）；School of Engineering and Applied Science, Princeton University（普林斯顿大学工程与应用科学学院）
Heating, ventilating, and air-conditioning (HVAC) systems consume a large amount of energy in residential houses and buildings. Effective energy management of HVAC is a cost-effective way to improve energy efficiency and reduce the energy cost of residential users. This work develops a novel distributed method for the residential transactive energy system that enables multiple users to interactively optimize their energy management of HVAC systems and behind-the-meter batteries. Specifically, this method effectively reduces the cost of smart homes by employing energy trading among users to lev…
This work presents the design and implementation of a blockchain system that enables the trustable transactive energy management for distributed energy resources (DERs). We model the interactions among DERs, including energy trading and flexible appliance scheduling, as a cost minimization problem. Considering the dispersed nature and diverse ownership of DERs, we develop a distributed algorithm to solve the optimization problem using the alternating direction method of multipliers (ADMM) method. Furthermore, we develop a blockchain system, on which we implement the proposed algorithm with the…
Heating, Ventilation, and Air Conditioning (HVAC) energy consumption accounts for a significant part of the total energy consumption of buildings and households. The ubiquitous adoption of distributed renewable energy and smart meters helps to decarbonize the HVAC energy consumption and improve energy efficiency. However, how to scale up HVAC energy management for a group of users while persevering users' privacy remains a big challenge. In this work, we utilize the concept of transactive energy to build a cooperative energy management system for independent HVAC units in a distributed manner.…
In smart grids, distributed energy resources (DERs) have penetrated residential zones to provide a new form of electricity supply, mainly from renewable energy. Residential households and commercial buildings with DERs have become prosumers in the local grids, since they can sell surplus power to others. Researches have been initiated to integrate and utilize DERs through better control and communication strategies. With the advances in the Internet of Things (IoT) technology, unprecedented coordination among DERs can be achieved to facilitate energy trading and transactive energy management. …
Frequency fluctuations in power grids, caused by unpredictable renewable energy sources, consumer behavior and trading, need to be balanced to ensure stable grid operation. Standard smart grid solutions to mitigate large frequency excursions are based on centrally collecting data and give rise to security and privacy concerns. Furthermore, control of fluctuations is often tested by employing Gaussian perturbations. Here, we demonstrate that power grid frequency fluctuations are in general non-Gaussian, implying that large excursions are more likely than expected based on Gaussian modeling. We …
With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the grid to perform vertical transactions, e.g., feeding in extra solar energy to the grid and providing demand response service to alleviate the grid load. Smart homes can also interact with peer users to perform horizontal transactions, e.g., peer-to-pee…
Vellore Institute of Technology（韦洛尔理工学院）；Pusan National University（釜山国立大学）；University of Oulu（奥卢大学）；Indian Institute of Technology Madras（印度理工学院马德拉斯分校）
Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such as power generation (e.g., wind turbines), transmission and distribution (microgrids and fault detectors), load management (smart meters and smart electric appliances). Thanks to recent advancements in big data and computing technologies, Deep Learning (DL) can be leveraged to lea…
We consider a scenario where a retailer can set different prices for different consumers in a smart grid. The retailer's objective is to maximize the revenue, minimize the operating cost, and maximize the consumer's welfare. The retailer wants to optimize a convex combination of the above objectives using price signals specific to each consumer. However, variability in unit prices across consumers is bounded by a parameter $η$, hence limiting the discrimination. We formulate the pricing problem as a Stackelberg game where the retailer is the leader and consumers are followers. Since the retail…
Three-Party Energy Management With Distributed Energy Resources in Smart Grid
Singapore University of Technology and Design（新加坡科技设计大学）；Zhejiang University（浙江大学）；National ICT Australia（澳大利亚国家信息与通信技术管理局）；Australian National University（澳大利亚国立大学）；Princeton University（普林斯顿大学）
