Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
In this paper, a framework is proposed for integration of peer-to-peer (P2P) trading-based local energy market (LEM) with the blockchain technology. The proposed LEM model allows prosumers and consumers to trade electricity among each other ensuring the presence of the retailer and network utility – who are also essential parts of a P2P network. The P2P contracts settled between various prosumers and consumers are governed by mutually agreed upon smart contracts – which are then written in an Ethereum blockchain to record and store bidding history, P2P transactions, and settlements. An effective formulation is also presented to capture P2P trading quantities and prices among participating prosumers and consumers in a decentralised fashion with an appropriate analysis of financial viability. Finally, a case study is conducted in a real Australian context; in which the engagement of both prosumers and consumers are taken into account, and the performance of the proposed blockchain-enabled LEM is compared with business-as-usual (BAU) to demonstrate the model's superiority.
Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
This paper presents a local energy market (LEM) model to conduct peer-to-peer (P2P) energy trading between a number of participants by dint of the Ethereum-based blockchain technology. The proposed LEM mechanism is structured by considering relevant functional constraints while energy trading is arranged between several participants in the presence of other stakeholders including energy retailer and network operator. LEM participants’ mutual bidding intended P2P trading, actual settlement, and final billing are executed using the smart contracts in Ethereum blockchain to record LEM transactions and related data in an unchangeable and distributed fashion. Lastly, a case study is performed in an Australian suburb with 300 LEM participants, and the simulation results are benchmarked with an existing business-as-usual (BAU)scenario. The simulation results outline that the formulated LEM mechanism 1) reduces the electricity cost of participants remarkably while improving their self-sufficiency, 2) minimises power grid export and import, and 3) retains income margins for the energy retailer and network operator.
Abstract Distributed renewable energy supply (RES) is a new pattern for the transformation of power grids. As a characteristic case of RES, microgrids have an advantage in convenient operation. However, the energy management of microgrids remains as a major concern. With the emergence of the decentralized paradigm, blockchain potentially provides a reliable energy data metering and payment for the whole life cycle of energy management. In particular, the demand response (DR) in the microgrid can stimulate demanders to spontaneously manage their load consumption and maintain the balance of the energy trading market. To achieve optimal DR, a dynamic pricing strategy under the blockchain and game‐theoretic approach is proposed. First, the blockchain‐based architecture is applied to ensure the reliability of energy data and lay a foundation of binding agreements for games. Then, the pricing mechanism under the cooperative game is formulated to optimize DR. Moreover, to help resolve the optimal response quantity and reduce the supply punishment of the RES providers, the DR requires accurate forecasting of the energy generation and consumption profiles. Therefore, an ensemble method Long Short‐Term Gate Support (LSTGS) is designed to forecast the RES and load power for intelligent agent to make decision on effective energy scheduling and DR. Taking the classic distributed energy context as a case study, we demonstrate the effectiveness of our approach and show that it can achieve DR profits maximized and improve the stability of the energy‐trading market.
Demand flexibility plays a pivotal role in modern power systems with high penetration of variable energy resources. In recent years, one of the fastest-growing flexible energy demands has been proof-of-work-based cryptocurrency mining facilities. Due to their competitive ramping capabilities and demonstrated flexibility, such fast-responding loads are capable of participating in frequency regulation services for the grid while simultaneously increasing their own operational revenue. In this paper, we investigate the physical and economic viability of employing cryptocurrency mining facilities to provide frequency regulation in large power systems. We quantify mining facilities' operational profit, and propose a decision-making framework to explore their optimal participation strategy and account for the most influential factors. We employ real-world ERCOT ancillary services data in our case study to investigate the conditions under which provision of frequency regulation in the Texas grid is profitable. We also perform transient level simulations using a synthetic Texas grid to demonstrate the competitiveness of mining facilities at frequency regulation provision.
Seyed Amir Alavi, Mehrnaz Javadipour, Ardavan Rahimian, Kamyar Mehran
Abstract The privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for third‐party data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for end‐users; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyber‐physical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in real‐time by information received from trusted nodes of the Tangle distributed network anonymously. A small‐scale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO real‐time simulator and open‐source software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time.
Younes Zahraoui, Tarmo Korõtko, Argo Rosin, Hannes Agabus
Electricity generation using distributed renewable energy systems is becoming increasingly common due to the significant increase in energy demand and the high operation of conventional power systems with fossil fuels. The introduction of distributed renewable energy systems in the electric grid is crucial for delivering future zero-emissions energy systems and is cost-effective for promoting and facilitating large-scale generation for prosumers. However, these deployments are forcing changes in traditional energy markets, with growing attention given to transactive energy networks that enable energy trading between prosumers and consumers for more significant benefits in the cluster mode. This change raises operational and market challenges. In recent years, extensive research has been conducted on developing different local energy market models that enable energy trading and provide the opportunity to minimize the operational costs of the distributed energy resources by promoting localized market management. Local energy markets provide a stepping stone toward fully transactive energy systems that bring adequate flexibility by reducing users’ demand and reflecting the energy price in the grid. Designing a stable regulatory framework for local electricity markets is one of the major concerns in the electricity market regulation policies for the efficient and reliable delivery of electric power, maximizing social welfare, and decreasing electric infrastructure expenditure. This depends on the changing needs of the power system, objectives, and constraints. Generally, the optimal design of the local market requires both short-term efficiencies in the optimal operation of the distributed energy resources and long-term efficiency investment for high quality. In this paper, a comprehensive literature review of the main layers of microgrids is introduced, highlighting the role of the market layer. Critical aspects of the energy market are systematically presented and discussed, including market design, market mechanism, market player, and pricing mechanism. We also intend to investigate the role and application of distributed ledger technologies in energy trading. In the end, we illuminate the mathematical foundation of objective functions, optimization approaches, and constraints in the energy market, along with a brief overview of the solver tools to formulate and solve the optimization problem.
Bozhi Wang, Jinfei Xu, Ke Jin, C. L. Philip Chen · 9 authors
With the spread of distributed renewable energy, residents are shifting from being mere consumers to being energy producers and consumers. This role shift poses challenges to the electricity trading mechanism that connects distributed renewable energy sources to the grid. In this paper, a new efficient and secure blockchain-based distributed community energy trading mechanism is proposed, called CE-SDT. Our system is proved to be stable and scalable. It can also help shift loads and power peaks and reduce customer costs by 60%. As a result, our proposed blockchain-based trading mechanism, as compared to the centralized trading mechanism, is applied to microgrids formed by distributed renewable energy sources, not only obtaining greater economic benefits but also reducing the carbon footprint of residents, and furthermore, it promotes low or zero-carbon configurations of the power system, thereby achieving certain environmental benefits.
Liaqat Ali, M. Imran Azim, Jan Peters, Vivek Bhandari · 8 authors
This paper presents the application of a community battery energy storage system (CBESS)-integrated microgrid (MG) in a blockchain-enabled local energy market (LEM). The proposed LEM balances the community energy requirement while facilitating frequent peer-to-peer (P2P) energy transactions between several energy users in the presence of both energy supplier and energy operator. The architecture is formulated by taking a number of local market and network constraints, that include residential battery energy storage system (RBESS) constraints; CBESS constraints; P2P traded price constraints; P2P traded power constraints; margin constraints of the stakeholders; power grid export and import constraints; and network energy balance constraints, so as to not only incentivise energy users but also reduce import/export from/to power grid while keeping the margins of energy supplier and energy operator unaffected. Different types of transactions data including energy users’ P2P pricing bids and P2P traded energy volume are also stored in the blockchain database. Further, the developed LEM framework is also validated through a case study executed on an actual Australian power grid network, comprising 260 residential energy users; two energy suppliers; an energy operator; and a CBESS, and the performance of the proposed P2P trading-based LEM strategy is compared with the existing business-as-usual (BAU) that directs energy users to buy/sell energy at the time-of-use (ToU)/ feed-in-tariff (FiT) rate. The extensive and comparative simulation results confirm the superior performance of the proposed LEM mechanism in terms of minimising energy users’ electricity bill; lowering power grid import and export; and retaining margins of energy suppliers and the energy operator; and thus, emphasise its application suitability in the current electricity market.
Godwin C. Okwuibe, Thomas Brenner, Peter Tzscheutschler, Thomas Hamacher
Local energy markets (LEMs) provide opportunity to handle the challenges arising from the lower grid level while using the traditional top-down approach to manage distributed generated renewable energy resources. Blockchain based local energy markets (LEMs) have been introduced in recent years as a way to enable local consumers/prosumers to trade their energy locally in a distributed and highly secured manner in an LEM. However, there are still some challenges regarding the main factors that can drive local consumers/prosumers to participate in a blockchain based LEM, optimal community size and prosumer to consumer ratio for an efficient LEM. Also, there is still no information on how the quantifying factors for participation on a blockchain based LEM can affect the performance of an LEM. This paper presents a survey and simulation based analysis of quantifying factors for participation in a blockchain based LEM. The survey was distributed among local consumers/prosumers and a total of 261 responses were received from the responders. The results from the responders were analyzed using a Python code based statistical analysis model. The simulation based analysis was conducted using a community based LEM model and evaluated using data received from a combination of German household profiles and standard load profiles. The survey results showed that the major drive for local consumers/prosumers to participate on blockchain based LEM is their willingness to support renewable energy integration, transparency and trust offered by a blockchain network. On the other hand, the simulation based analysis showed that small and medium communities with prosumers to consumer ratios between 0.3 to 0.5 create more economic and technical benefits for local consumers/prosumers compared to large communities. The community based simulation results were modelled together with the survey results to determine how the individual quantifying factors for participating in a blockchain based LEM can affect the performance of an LEM.
Interconnected Microgrids (IMGs) are considered a futuristic paradigm of power grids that offer modularity, resilience, and independence with energy exchangeability. In this context, each MG is accountable to its own citizens (i.e., generators or loads) and can participate in a market with its neighbours, if this enhances the benefits of its citizens. Thus, greedy behaviour is assumed to be rational for MGs participating in such a market. In this paper, a novel decentralized platform to facilitate energy trading between IMGs is developed. The platform would allow interested MGs to participate and gain benefits assuming self-benefit-driven (SBD) actions from participating MGs. The proposed platform provides a market-clearing approach based on sequential rounds. In each round, the MG with the cheapest energy price is privileged to export its surplus energy and maximize its own benefits. In order to identify the round champ, a decentralized ranking algorithm is developed to determine the MG with the cheapest energy price. The effectiveness of the proposed platform is validated using various case studies.
Miguel Gayo-Abeleira, Carlos Santos, Francisco J. Rodríguez, Pedro Martı́n · 6 authors
Regulatory changes in different countries regarding self-consumption and growing public concern about the environment are encouraging the establishment of community microgrids. These community microgrids integrate a large number of small-scale distributed energy resources and offers a solution to enhance power system reliability and resilience. This work proposes a geographically-based split of the community microgrids into clusters of members that tend to have similar consumption and generation profiles, mimicking the most typical layout of cities. Assuming a community microgrid divided into clusters, a two-layer architecture is developed to facilitate the greater penetration of distributed energy resources in an efficient way. The first layer, referred as the market layer, is responsible for creating local energy markets with the aim of maximising the economic benefits for community microgrid members. The second layer is responsible for the network reconfiguration, which is based on the energy balance within each cluster. This layer complies with the IEC 61850 communication standard, in order to control commercial sectionalizing and tie switches. This allows the community microgrid network to be reconfigured to minimise energy exchanges with the main grid, without requiring interaction with the distributed system operator. To implement this two-layer energy management strategy, an aperiodic market approach based on Blockchain technology, and the additional functionality offered by Smart Contracts is adopted. This embraces the concept of energy communities since it decentralizes the control and eliminates intermediaries. The use of aperiodic control techniques helps to overcome the challenges of using Blockchain technology in terms of storage, computational requirements and member privacy. The scalability and modularity of the Smart Contract-based system allow each cluster of members to be designed by tailoring the system to their specific needs. The implementation of this strategy is based on low-cost off-the-shelf devices, such as Raspberry Pi 4 Model B boards, which operate as Blockchain nodes of community microgrid members. Finally, the strategy has been validated by emulating two use cases based on the IEEE 123-node system network model highlighting the benefits of the proposal.
This paper presents the PEACEFULNESS software platform (Platform for transvErse evAluation of Control stratEgies For mULti-eNErgy Smart gridS), an open framework dedicated to multi-energy smart-grids, based on a techno-economic model that integrates economic considerations (contracts). As such, it is mainly oriented towards the evaluation of multi-energy grid supervision strategies, that is, energy management, and the corresponding policies and legal organization. The main goal is then to highlight the various possible behaviors and strategies to organize the probable future interconnections between the different energy carriers. In particular, it aims at investigating how to maximize the use of renewable energy sources (RES), using Demand Side Management (DSM) techniques and energy storage, in a shared economy context. The open-source tool PEACEFULNESS, written in Python, is described here in detail. It combines a top-down description of the energy networks and connections between the various agents (energy providers, distribution system operators, aggregators, consumers, producers, prosumers, etc.), together with a techno-economic bottom-up description for all devices. Here, both public databases and users’ data (basic heating demands or based on building modeling) can be used, as well as generic or more specific models (e.g., PV panels with constant or temperature-dependent efficiency). One of its major unique features compared with other tools is that it extends the use of DSM techniques to various energy grids which can also interact together. Furthermore, different economic models can be set for both the aggregators and the customers, and even within these groups. As a last competitive advantage, PEACEFULNESS allows the user to simulate the operation and supervision of tens up to hundreds of thousands of agents. It also provides a reporting system giving access to all the data, with a configurable granularity and frequency for the retained indicators. Finally, several validation cases are presented, followed by a series of test cases with increasing size: a smart home, a smart district (2 000 dwellings) and a smart community (50 000 dwellings).
Abstract Due to the growing number of Distributed Energy Resources and new electrical loads at the sectoral contact points, novel organisational forms such as Local Energy Markets arise to deal with increasing complexity in the energy system. However, these markets are radically different from traditional energy markets, as they often allow individual prosumers to trade with each other via a peer‐to‐peer scheme. To guarantee tamper‐proof settlement, an increasing number of these markets feature a distributed ledger technology. This paper analyses different design variants of peer‐to‐peer markets, focusing specifically on the allocation mechanism under network constraints as these mechanisms constitute the core component of a market design. We assess these designs concerning user acceptance, economic performance, practicability, and their ability to relieve grid congestion. Further key performance indicators also cover communal revenues or welfare distribution. For this purpose, we developed an agent‐based simulation framework, which builds on data from three German reference municipalities derived from a novel clustering approach. Besides a consolidated presentation of the results, we highlight current implementation obstacles and identify promising concepts for further research.
Decarbonisation of energy sector is crucial to deliver the future net zero energy system with promoting and facilitating the large-scale electrification of end-user sectors. It is necessary to provide sustainable, cost-effective, resilient and scalable energy solutions to exploit the power of citizens to contribute to the clean energy transition, increasing the flexibility of the overall energy system. Energy community, as the new actor, create an integrated pan energy market by bringing together the local consumers and energy market players. However, diversity of energy community brings huge challenges in integration of decentralized renewables with regulated framework, interaction of decentralized marketplaces, as well as interoperability of the cross-border energy sectors with privacy, security and incentives. This paper intends to provide an in-depth investigation on the role of microgrid and blockchain, alone and together, in facilitating the energy community as the “enabling framework” to boost the potential solutions of electrification in the transportation, building, and industrial sectors, as well as rural/remote areas and islands towards a networking green ecosystem. This paper serves as a comprehensive reference to understand the modern microgrid on its control and communication technology with integration of blockchain services in promoting the techno-socio-economic innovations for the restructuring of the sustainable energy supply chain.
Sabrina Lee Chartier, Vinod Kumar Venkiteswaran, Shriram S. Rangarajan, E.R. Collins · 5 authors
Microgrids are emerging throughout the world as a means of integrating decentralized, renewable energy power generation. The flexibility of this customer-driven, behind the meter solution allows it to address unique challenges. This variability that drives microgrid adoption is the same thing that keeps them from being categorized and repeatable. This lack of specific modeling leads to a stalling in financing and wide-scale adoption. By analyzing the microgrid system development, evolution, architecture, integration zones, technological advances, and business models, a clearer picture of how these entities are intertwined emerges. Several case studies of deployed microgrids will showcase the cutting-edge solutions they apply. The future implications of this new energy revolution will be highlighted and shown to create an energy generation equilibrium and the significant role played by microgrids in this new energy revolution. Although many compilations of research work on microgrids have been previously presented by various reviewers, most of them are specific to an electrical or power quality-related issue, which addresses a discrete audience. This work only includes within its scope a general outlook of microgrids and the present-day challenges in its use of rural/urban renewable energy production and distribution. The results allowed for the researchers to conclude that microgrids have emerged as a great solution in situations where energy has to be transmitted from a decentralized system to a centralized system. Challenges will arise in the microgrid management and government laws and regulations if rectified microgrids can lead to an equilibrium between decentralized and centralized bulk energy networks.
The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community.
Abstract Since the early beginnings of the electricity system, storage has been of high relevance for balancing supply and demand. Through expanded electricity production by variable renewable technologies such as wind and photovoltaics, the discussion about new options for storage technologies is emerging. In addition, the electricity markets were subject to remarkable alterations. Some developments which describe these changes are increasing electricity generation from variable renewables and the continuing decentralization. These developments have led, among other required transformations, to demands for additional capacities of storage technologies. However, their economics will play a crucial role in their effective market penetration in the following years. The core objective of this work is to conduct a review on the relevance of storage options for electricity and its costs, economics, welfare effects, and on issues of electricity market design. In addition, based on expected Technological Learning prospects for future economics are derived. The major result is that the perspectives of electricity storage systems from an economic viewpoint are highly dependent on the storage's operation time, the nature of the overall system, availability of other flexibility options, and sector coupling. All market‐based storage technologies have to prove their performance in the large electricity markets or if applied decentralized, the (battery) systems compete with the electricity prices at the final customers level when the battery costs are also taken into consideration. Yet, new storage capacities should only be added when it is clear that electricity generation from variable renewables will also be expanded in a way that excess generation is expected. This article is categorized under: Policy and Economics > Green Economics and Financing Energy and Power Systems > Energy Infrastructure Emerging Technologies > Energy Storage
Zhiwei Chen, Wenxin Guo, Ruifeng Zhao, Yang Liu · 5 authors
The purpose is to realize the decentralized microgrid economic dispatch, improve the information transparency and security of microgrid systems, and make the power grid move towards a clean, safe, efficient, and reliable development path. Deep learning optimization of microgrid economic dispatch and wireless power transmission based on blockchain technology are studied. First, the related theories and methods of microgrid systems, wireless power transmission, and deep learning optimization based on blockchain technology are introduced. Next, the microgrid economic dispatch is simulated and analyzed on a large scale. Finally, the comparison results between microgrid economic dispatch and common radio energy transmission technologies are analyzed. The results show that daily planning can better coordinate the state of distributed generation, energy storage system, and public connection. The operation results of the previous day correspond to the long‐term operation economy of the microgrid. The total operation cost of the microgrid is 4668 yuan/day, and the remaining power is maintained between 500 and 600 kW, which helps to prevent excessive battery discharge, prolong battery life, and reduce operation cost. The simulation results show that the total power imbalance of the microgrid can reduce the output fluctuation of controllable load shedding of distributed generation. When the load characteristics are not important, the output fluctuation of controllable distributed generation can be reduced. The proposed economic dispatch model can optimize the data security, information storage, and information release of the microgrid and has a certain guiding role for the development of the national power grid and power industry.
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan · 5 authors
With advancements in renewable energy technologies, consumers are becoming prosumers, and renewable energy resources are being used in distributed networks. In an isolated distributed system, peer-to-peer (P2P) energy trading is one of the most promising energy management solutions. In this paper, we propose a P2P energy trading method for micro-grids using open resources and technology. The proposed setup comprises an Internet of Things (IoT) server to transfer energy amongst the peers without human intervention, and an Ethereum based private blockchain is suggested for money transfer in the form of cryptocurrency. The IoT server enables the peers to control and monitor self-produced energy. Arduino UNO, ACS 712 hall-effect current sensor, and a relay are the main components used in the hardware setup. The current sensor data is sent in real- time to Arduino for onward communication to the IoT server. A user-friendly interface has been developed on the server to perform various energy trading tasks. Peers have the choice to access the server remotely to perform energy trading tasks. The energy trading events can be shared amongst peers through e-mail notifications. For financial transactions, we utilized Ganache graphical user interface (GUI) a private Ethereum blockchain eliminating the need for financial institutions. The proposed peer-to-peer energy trading model has been successfully tested for energy trading between two peers. This paper provides details of the proposed hardware and software setup and explains how low-cost P2P energy trading can be achieved.
To further implement decentralized renewable energy resources, blockchain based peer-to-peer (P2P) energy trading is gaining attention and its architecture has been proposed with virtual demonstrations. In this paper, to further socially implement this concept, a blockchain based peer to peer energy trading system which could coordinate with energy control hardware was constructed, and a demonstration experiment was conducted. Previous work focused on virtually matching energy supply and demand via blockchain P2P energy markets, and our work pushes this forward by demonstrating the possibility of actual energy flow control. In this demonstration, Plug-in Hybrid Electrical Vehicles(PHEVs) and Home Energy Management Systems(HEMS) actually used in daily life were controlled in coordination with the blockchain system. In construction, the need of a multi-tagged continuous market was found and proposed. In the demonstration experiment, the proposed blockchain market and hardware control interface was proven capable of securing and stably transmitting energy within the P2P energy system. Also, by the implementation of multi-tagged energy markets, the number of transactions required to secure the required amount of electricity was reduced.
This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighbouring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.
Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large U.K.-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator's revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated.
Moayad Aloqaily, Ouns Bouachir, Öznur Özkasap, Faizan Safdar Ali
Abstract Growing intelligent cities is witnessing an increasing amount of local energy generation through renewable energy resources. Energy trade among the local energy generators ( aka prosumers) and consumers can reduce the energy consumption cost and also reduce the dependency on conventional energy resources, not to mention the environmental, economic, and societal benefits. However, these local energy sources might not be enough to fulfill energy consumption demands. A hybrid approach, where consumers can buy energy from both prosumers (that generate energy) and also from prosumer of other locations, is essential. A centralized system can be used to manage this energy trading that faces several security issues and increase centralized development cost. In this paper, a hybrid energy trading system coupled with a smart contract named SynergyGrids has been proposed as a solution, that reduces the average cost of energy and load over the utility grids. To the best of our knowledge, this work is the first attempt to create a hybrid energy trading platform over the smart contract for energy demand prediction. An hourly energy data set has been utilized for testing and validation purposes. The trading system shows 17.8% decrease in energy cost for consumers and 76.4% decrease in load over utility grids when compared with its counterparts.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Zita Vale
This paper proposed a Mixed Binary Linear Programming (MBLP) approach to find the optimal size of some components of a Smart Building (SB) attempting to reduce the overall cost. The considered SB is equipped with local resources such as Photovoltaic (PV) panels, Electrical Vehicles (EVs), and the Battery Energy Storage System (BESS). Moreover, the SB is only connected with the grid by an Energy Management System (EMS) in which the whole SB has a single Contract Power (CP) such that EMS manages the power flow among external grid, local resources, apartments, and common services, for the goal of reducing the electricity bill. Hence, the wrong choice of CP and BESS capacity will impose unnecessary charges on the electricity bill. As a results, EMS has played a crucial role in SB in determining the best CP and BESS values. The obtained results of this work show the efficiency of the model in which by finding the optimal capacity of CP and BESS, the electricity bill improves by a 34% reduction.