We present an architecture for peer-to-peer energy markets which can guarantee that operational constraints are respected and payments are fairly rendered, without relying on a centralized utility or microgrid aggregator. We demonstrate how to address trust, security, and transparency issues by using blockchains and smart contracts, two emerging technologies which can facilitate decentralized coordination between non-trusting agents. While blockchains are receiving considerable interest as a platform for distributed computation and data management, this is the first work to examine their use to facilitate distributed optimization and control. Using the Alternating Direction Method of Multipliers (ADMM), we pose a decentralized optimal power flow (OPF) model for scheduling a mix of batteries, shapable loads, and deferrable loads on an electricity distribution network. The DERs perform local optimization steps, and a smart contract on the blockchain serves as the ADMM coordinator, allowing the validity and optimality of the solution to be verified. The optimal schedule is securely stored on the blockchain, and payments can be automatically, securely, and trustlessly rendered without requiring a microgrid operator.
As decentralized renewable energy has been installed into the present grid, millions of consumers and prosumers interacting each other over power grid. The variety of needs for exchanging energy would arise based on each customers' situation. The future electricity grid should be a bi-directional system with interconnected using distributed energy management software. Being able to provide a secure and decentralized control to these autonomous, peer-to-peer exchanges is one of the biggest challenges. We propose to use Blockchain-based electricity trading system with Digitalgrid router as an underlying platform because it could fit these requirements. Digitalgrid router, which consists back-to-back bi-directional digital inverters with software-based control, enables us to realize power exchange.
Jun 1, 2017·2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Eleonora Riva Sanseverino, Maria Luisa Di Silvestre, Pierluigi Gallo, Gaetano Zizzo · 5 authors
In recent years novel models for energy distribution appeared and islanded microgrids quest for new ways to exchange energy between consumers and producers without the need of central authorities. The blockchain mechanism has emerged as a distributed solution for recording energy transactions in power systems. The blockchain has been used to permit users bartering and selling energy and to keep track of such exchanges without exposing them to tampering. In this work, we consider a novel application of the blockchain in islanded microgrids that includes also annotating energy losses caused by energy transactions, in order to have a more realistic matching between the physical status of the energy grid and the consequent costs attributed to users. To validate our novel use of the blockchain, we carried out simulated experiments for an exemplary islanded microgrid, in which 3 main generators supply 6 load nodes. This validates the compatibility of this new cost attribution model with the supporting physical infrastructure. Preliminary results demonstrate that the superposition of energy transactions in a microgrid changes the distribution of losses in all paths, eventually due to the large reactive flows created by PV systems.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy Resources (DERs). The strategy that maximizes the revenue for each individual DER is the one in which the DER operates at capacity, injecting all available power into the grid. However, when the DER penetration is high and the consumption low, this strategy may lead to power surplus that causes voltage increase over recommended limits. In order to create incentives for the DER to operate below capacity, we propose a proportional-fairness control strategy in which (i) a subset of DERs decrease their own power output, sacrificing the individual revenue, and (ii) the DERs in the subset are dynamically selected based on the record of their control history. The trustworthy implementation of the scheme is carried out through a custom-designed blockchain mechanism that maintains a distributed database trusted by all DERs. In particular, the blockchain is used to stipulate and store a smart contract that enforces proportional fairness. The simulation results verify the potential of the proposed framework.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy\nResources (DERs). The strategy that maximizes the revenue for each individual\nDER is the one in which the DER operates at capacity, injecting all available\npower into the grid. However, when the DER penetration is high and the\nconsumption low, this strategy may lead to power surplus that causes voltage\nincrease over recommended limits. In order to create incentives for the DER to\noperate below capacity, we propose a proportional-fairness control strategy in\nwhich (i) a subset of DERs decrease their own power output, sacrificing the\nindividual revenue, and (ii) the DERs in the subset are dynamically selected\nbased on the record of their control history. The trustworthy implementation of\nthe scheme is carried out through a custom-designed blockchain mechanism that\nmaintains a distributed database trusted by all DERs. In particular, the\nblockchain is used to stipulate and store a smart contract that enforces\nproportional fairness. The simulation results verify the potential of the\nproposed framework.\n
Cherrelle Eid, Paul Codani, Yannick Pérez, Javier Reneses · 5 authors
In many electric systems worldwide the penetration of Distributed Energy Resources (DER) at the distribution levels is increasing. This penetration brings in different challenges for electricity system management; however if the flexibility of those DER is well managed opportunities arise for coordination. At high voltage levels under responsibility of the system operator, trading mechanisms like contracts for ancillary services and balancing markets provide opportunities for economic efficient supply of system flexibility services. In a situation with smart metering and real-time management of distribution networks, similar arrangements could be enabled for medium- and low-voltage levels. This paper presents a review and classification of existing DER as flexibility providers and a breakdown of trading platforms for DER flexibility in electricity markets.
Nicolas Gensollen, Vincent Gauthier, Monique Becker, Michel Marot
In the context of the smart grid, we propose in this paper an algorithm that forms coalitions of agents, called prosumers, that both produce and consume. It is designed to be used by aggregators that aim at selling aggregated surplus of production of the prosumers they control. We rely on real weather data sampled across stations of a given territory in order to simulate realistic production and consumption patterns for each prosumer. This enables us to capture geographical correlations among the agents while preserving the diversity due to different behaviors. As aggregators are bound to the market operator by a contract, they seek to maximize their offer while minimizing their risk. The proposed graph-based algorithm takes the underlying correlation structure of the agents into account and outputs coalitions with both high productivity and low variability. We show that the resulting diversified coalitions are able to generate higher benefits on a constrained energy market, and are more resilient to random failures of the agents.
The penetration level of the renewable energy resources (RER), such as wind power turbines and solar photovoltaic generation, in interconnected power systems has been increased in many countries. A high penetration level of RERs causes some problems to the grid operator, e.g., lack in primary reserve. Due to environmental concern and energy security risk, many countries around the world decided to increase their electric vehicles (EV) in the near future which provides a good chance to use them as a mobile battery energy storage system (BESS). This paper proposes a new scheme to provide necessary primary reserve from electric vehicles by using hierarchical control of each individual vehicle. An EV aggregator based on the vehicle's information such as the required state of charge (SOC) for the next trip, departure time, and initial SOC is proposed. The proposed aggregation scheme determines the primary reserve and contracts it with system operator based on electricity market negotiation. The effectiveness of the proposed scheme is shown by the several simulation studies in the Taiwan power (Tai-power) system to enhance frequency nadir and steady state frequency after a large disturbance.
The smart grid is widely considered as an efficient and intelligent power system. With the aid of communication technologies, the smart grid can enhance the efficiency and reliability of the grid system through intelligent energy management. However, with the development of new energy sources, storage and transmission technologies together with the heterogeneous architecture of the grid network, several new features have been incorporated into the smart grid. These features make the energy trading more complex and pose a significant challenge on designing efficient trading schemes. Based on this motivation, in this paper, we present a comprehensive review of several typical economic incentive approaches adopted in the energy-trading control mechanisms. We focus on the technologies that address the challenges specific to the new features of the smart grid. Furthermore, we investigate the energy trading in a new cloud-based vehicle-to-vehicle energy exchange scenario. We propose an optimal contract-based electricity trading scheme, which efficiently increases the generated profit.
Demand Response (DR) is considered a promising approach to cope with the increasing variability in power grids due to the penetration of renewable energy sources. However, it still remains a challenge to manage the aggregation of a large number of heterogeneous loads to achieve a desired response, especially at a fast time scale. In this paper, we present a system-level modeling and control design approach for DR management in smart grids, by following a contract-based methodology. Given a set of flexible DR loads, capable of adapting their power consumption upon external requests, we find a strategy for an aggregator to optimally track a DR requirement by combining the individual contributions of the DR components. In our framework, both the design requirements and the DR components' interfaces are specified by assume-guarantee contracts expressed using mixed-integer linear constraints. Contracts are used to formulate an optimal control problem, which is solved repeatedly over time, in a receding horizon fashion. We illustrate the effectiveness of our methodology for a set of DR components including fans and pumps, showing that it enables modular development of non-disruptive DR control schemes.
Samira Rahnama, Jan Dimon Bendtsen, Jakob Stoustrup, Henrik Rasmussen
Exploitation of flexible consumption in the future smart grid requires new actors and infrastructure. In this paper, we propose a hierarchical setup in which a central controller, a so-called “aggregator,” is responsible for managing the flexibilities of industrial thermal loads via a contract-based direct control policy. The aggregator manipulates the consumption profile in an optimal and robust manner in order to provide upward and downward regulating power services. To this end, we consider a robust model predictive control design at the aggregator. The performance of the proposed controller is evaluated by simulating specific case studies involving a supermarket refrigeration system and a heating, ventilation, and air conditioning chiller in conjunction with an ice storage. In addition, we provide a comparison between heterogeneous and homogeneous aggregation of different thermal loads through simulation examples.
India today needs to have around 2,OO,OOO MW of power to meet its current energy needs, but it is able to provide only about two third of it. Additional finances are difficult to come by and the infrastructure is often not available to make it reach the remote areas. Heavy roistering in city areas has been a perpetual feature in some states. Many of the dwellers of small cities have come to depend on what is called an 'inverter' and its associated battery based storage system to cope up with the frequent power outages. Seen from another perspective these systems only lack the solar panels to become completely self contained power systems. Thus addition of solar panels to these will be only an incremental cost. By encouraging this approach several problems can be solved all the same time. First of all this additional investment will be from the users themselves. Next the power generated will be environmentally friendly and the regular power supply and the grid may need to be used sparingly. These storage based systems may become parts of Smart Grids for the future as they may be further evolved to feed power into the grid.Evaluation of the performance of these systems has been studied through simulation and the economics of the system has been investigated under various conditions for typical users. The proposed system has been compared with the early telecom systems in India that were based on land lines and could not be expanded fast enough. Later the privatized and decentralized wireless based approach provided the desirable solutions.
Vivek Kuthanazhi, Anil Kottantharayil, N. C. Narayanan
Decentralization of energy planning through local self-governments has become a possibility since the development of solar photovoltaics and other small scale power generation technologies. The state of Kerala, India is well known for its success stories in decentralized administration of villages through panchayati raj1institutions. Panchayats in Kerala have proved their efficiency in the past by handling development projects, hence the scope for implementing decentralized PV power plants in a panchayat scale in Kerala is quite high. A study was conducted at Chendamangalam gram panchayat, Kerala, India to assess the electricity demand and rooftop PV power generation potential of a typical panchayat located in the low-lands of Kerala. The changing trends in electricity consumption due to the use and spread of new appliances and 100% grid extension to the villages could be discerned. Appliances like televisions, ceiling fans, water pumps, washing machines, electric mixers, refrigerators etc has penetrated well in this area. Inverter based power back up systems and new high power equipments like induction cookers, air conditioners, water heaters etc. are increasingly being used by the domestic consumers, which indicate a possible leap in electricity demand in the near future. The study could conclude that the collective shade free rooftop area from nearly 6500 buildings in the panchayat can support nearly 11.3 MW rooftop PV installations and it is more than enough to meet the current energy demands of the panchayat. Innovative design of custom PV solutions and institutionalization of operation and maintenance, supported with clear government policies and finance options can help in transforming a panchayat into an energy surplus entity.
This paper deals with a decentralized control of smart grid by using overlapping information for load frequency of power networks introducing distributed power generations. The control objective is to minimize the cost function of load frequency control problem. We expand the state space of the system of power networks and propose a decentralized state feedback control of subsystems for the expanded system. Then we contract the decentralized feedback law to match the original system. Finally, we show the effectiveness of the load frequency control by using the proposed decentralized control method through the simulation result of decentralized large scale power network systems.