Cooperatives for demand side management

We propose a new scheme for efficient demand side management for the Smart Grid. Specifically, we envisage and promote the formation of cooperatives of medium-large consumers and equip them (via our proposed mechanisms) with the capability of regularly participating in the existing electricity markets by providing electricity demand reduction services to the Grid. Based on mechanism design principles, we develop a model for such cooperatives by designing methods for estimating suitable reduction amounts, placing bids in the market and redistributing the obtained revenue amongst the member agents. Our mechanism is such that the member agents have no incentive to show artificial reductions with the aim of increasing their revenue

Electricity market design for the prosumer era

Prosumers are agents that both consume and produce energy. With the growth in small and medium-sized agents using solar photovoltaic panels, smart meters, vehicle-to-grid electric automobiles, home batteries and other ‘smart’ devices, prosuming offers the potential for consumers and vehicle owners to re-evaluate their energy practices. As the number of prosumers increases, the electric utility sector of today is likely to undergo significant changes over the coming decades, offering possibilities for greening of the system, but also bringing many unknowns and risks that need to be identified and managed. To develop strategies for the future, policymakers and planners need knowledge of how prosumers could be integrated effectively and efficiently into competitive electricity markets. Here we identify and discuss three promising potential prosumer markets related to prosumer grid integration, peer-to-peer models and prosumer community groups. We also caution against optimism by laying out a series of caveats and complexities

Autonomous trading in modern electricity markets

The smart grid is an electricity grid augmented with digital technologies that automate the management of electricity delivery. The smart grid is envisioned to be a main enabler of sustainable, clean, efficient, reliable, and secure energy supply. One of the milestones in the smart grid vision will be programs for customers to participate in electricity markets through demand-side management and distributed generation; electricity markets will (directly or indirectly) incentivize customers to adapt their demand to supply conditions, which in turn will help to utilize intermittent energy resources such as from solar and wind, and to reduce peak-demand. Since wholesale electricity markets are not designed for individual participation, retail brokers could represent customer populations in the wholesale market, and make profit while contributing to the electricity grid’s stability and reducing customer costs. A retail broker will need to operate continually and make real-time decisions in a complex, dynamic environment. Therefore, it will benefit from employing an autonomous broker agent. With this motivation in mind, this dissertation makes five main contributions to the areas of artificial intelligence, smart grids, and electricity markets. First, this dissertation formalizes the problem of autonomous trading by a retail broker in modern electricity markets. Since the trading problem is intractable to solve exactly, this formalization provides a guideline for approximate solutions. Second, this dissertation introduces a general algorithm for autonomous trading in modern electricity markets, named LATTE (Lookahead-policy for Autonomous Time-constrained Trading of Electricity). LATTE is a general framework that can be instantiated in different ways that tailor it to specific setups. Third, this dissertation contributes fully implemented and operational autonomous broker agents, each using a different instantiation of LATTE. These agents were successful in international competitions and controlled experiments and can serve as benchmarks for future research in this domain. Detailed descriptions of the agents’ behaviors as well as their source code are included in this dissertation. Fourth, this dissertation contributes extensive empirical analysis which validates the effectiveness of LATTE in different competition levels under a variety of environmental conditions, shedding light on the main reasons for its success by examining the importance of its constituent components. Fifth, this dissertation examines the impact of Time-Of-Use (TOU) tariffs in competitive electricity markets through empirical analysis. Time-Of-Use tariffs are proposed for demand-side management both in the literature and in the real-world. The success of the different instantiations of LATTE demonstrates its generality in the context of electricity markets. Ultimately, this dissertation demonstrates that an autonomous broker can act effectively in modern electricity markets by executing an efficient lookahead policy that optimizes its predicted utility, and by doing so the broker can benefit itself, its customers, and the economy.Computer Science

State of the Art and Trends Review of Smart Metering in Electricity Grids

Climate change, awareness of energy efficiency, new trends in electricity markets, the obsolescence of the actual electricity model, and the gradual conversion of consumers to prosumer profiles are the main agents of progressive change in electricity systems towards the Smart Grid paradigm. The introduction of multiple distributed generation and storage resources, with a strong involvement of renewable energies, exposes the necessity of advanced metering or Smart Metering systems, able to manage and control those distributed resources. Due to the heterogeneity of the Smart Metering systems and the specific features of each grid, it is easy to find in the related literature a wide range of solutions with different features. This work describes the key elements in a Smart Metering system and compiles the most employed technologies and standards as well as their main features. Since Smart Metering systems can perform jointly with other activities, these growing initiatives are also addressed. Finally, a revision of the main trends in Smart Metering uses and deployments worldwide is included.his work has been partially supported by the Spanish Ministry of Economy and Competitiveness (project TEC2015-67868-C3-1-R), the University of the Basque Country (UPV/EHU) within the program for the specialization of the postdoctoral researcher staff, and Microgrids with Renewable Distributed Generation (MIGEDIR) (project 713RT0468), funded by the Science and Technology for Development Iberoamerican Program (CYTED)

The Next-Generation Retail Electricity Market in the Context of Distributed Energy Resources: Vision and Integrating Framework

The increasing adoption of distributed energy resources (DERs) and smart grid technologies (SGTs) by end-user retail customers is changing significantly both technical and economic operations in the distribution grid. The next-generation retail electricity market will promote decentralization, efficiency, and competitiveness by accommodating existing and new agents through new business models and transactive approaches in an advanced metering infrastructure (AMI). However, these changes will bring several technical challenges to be addressed in transmission and distribution systems. Considerable activities have been carried out worldwide to study the impacts of integrating DERs into the grid and in the wholesale electricity market. However, the big vision and framework of the next-generation retail market in the context of DERs is still unclear. This paper aims to present a brief review of the present retail electricity market, some recent developments, and a comprehensive vision of the next-generation retail electricity market by describing its expected characteristics, challenges, needs, and future research topics to be addressed. A framework of integrating retail and wholesale electricity markets is also presented and discussed. The proposed vision and framework particularly highlight the necessity of new business models and regulatory initiatives to establish decentralized markets for DERs at the retail level as well as advances in technology and infrastructure necessary to allow the widespread use of DERs in active and effective ways

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Peer-to-peer and community-based markets: A comprehensive review

The advent of more proactive consumers, the so-called "prosumers", with production and storage capabilities, is empowering the consumers and bringing new opportunities and challenges to the operation of power systems in a market environment. Recently, a novel proposal for the design and operation of electricity markets has emerged: these so-called peer-to-peer (P2P) electricity markets conceptually allow the prosumers to directly share their electrical energy and investment. Such P2P markets rely on a consumer-centric and bottom-up perspective by giving the opportunity to consumers to freely choose the way they are to source their electric energy. A community can also be formed by prosumers who want to collaborate, or in terms of operational energy management. This paper contributes with an overview of these new P2P markets that starts with the motivation, challenges, market designs moving to the potential future developments in this field, providing recommendations while considering a test-case

Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading

Peer-to-Peer (P2P) energy trading can facilitate integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail

An electricity market with fast bidding, planning and balancing in smart grids

In future energy systems, peaks in the daily electricity generation and consumption are expected to increase. The "smart grid" concept aims to maintain high levels of efficiency in the energy system by establishing distributed intelligence. Software agents (operating on devices with unknown computational capabilities) can implement dynamic and autonomous decision making about energy usage and generation, e.g. in domestic households, farms or offices. To reach satisfactory levels of efficiency and reliability, it is crucial to include planning-ahead of the energy-involving activities. Market mechanisms are a promising approach for large-scale coordination problems about energy supply and demand, but existing electricity markets either do not involve planning-ahead sufficiently or require a high level of sophistication and computing power from participants, which is not suitable for smart grid settings. This paper proposes a new market mechanism for smart grids, ABEM (Ahead- and Balancing Energy Market). ABEM performs an ahead market and a last-minute balancing market, where planning-ahead in the ahead market supports both binding ahead-commitments and reserve capacities in bids (which can be submitted as price functions). These features of planning-ahead reflect the features in modern wholesale electricity markets. However, constructing bids in ABEM is straightforward and fast. We also provide a model of a market with the features mentioned above, which a strategic agent can use to construct a bid (e.g. in ABEM), using a decision-theoretic approach. We evaluate ABEM experimentally in various stochastic scenarios and show favourable outcomes in comparison with a benchmark mechanism

Service Orientation and the Smart Grid state and trends

The energy market is undergoing major changes, the most notable of which is the transition from a hierarchical closed system toward a more open one highly based on a “smart” information-rich infrastructure. This transition calls for new information and communication technologies infrastructures and standards to support it. In this paper, we review the current state of affairs and the actual technologies with respect to such transition. Additionally, we highlight the contact points between the needs of the future grid and the advantages brought by service-oriented architectures.