Riccardo Vicente, GertâJan van Rooyen, Louzanne Bam
Cryptocurrency mining has been proposed to supplement conventional electricity exporting as a revenue stream with a view to improving the financial performance of renewable energy projects. To analyse this proposal, this paper presents the development of a model which is used as a decision-support tool to inform managerial decisions regarding renewable energy investments. This tool can be used to determine the feasibility of cryptocurrency mining as a hedge for a specific renewable energy project, as well as to inform various decisions that relate to the structuring of such a project. The model is implemented in both a spreadsheet-based environment and a simulation environment and is applied to a number of illustrative scenarios. The results indicate that using cryptocurrency mining to hedge renewable energy investments has potential. Furthermore, results improve for cooler climates and when a flexible approach is employed that entails switching between electricity exporting and cryptocurrency mining as revenue streams.
Buildings can become a significant contributor to an energy systemâs resilience if they are operated in a coordinated manner to exploit their flexibility in multi-carrier energy networks. However, research and innovation activities are focused on single-carrier optimization (i.e., electricity), aiming to achieve Zero Energy Buildings, and miss the significant flexibility that buildings may offer through multi-energy coupling. In this paper, we propose to use blockchain technology and ERC-1155 tokens to digitize the heat and electrical energy flexibility of buildings, transforming them into active flexibility assets within integrated multi-energy grids, allowing them to trade both heat and electricity within community-level marketplaces. The solution increases the level of interoperability and integration of the buildings with community multi-energy grids and brings advantages from a transactive perspective. It permits digitizing multi-carrier energy using the same token and a single transaction to transfer both types of energy, processing transaction batches between the sender and receiver addresses, and holding both fungible and non-fungible tokens in smart contracts to support energy marketsâ financial payments and energy transactionsâ settlement. The results show the potential of our solution to support buildings in trading heat and electricity flexibility in the same market session, increasing their interoperability with energy markets while decreasing the transactional overhead and gas consumption.
Abstract Combined heat and power (CHP) systems, an effective way of meeting high energy demand with high efficiency, were adapted to existing large service buildings in most studies. Because of the large daily and seasonal fluctuations in energy and electricity demands of the buildings, optimization problems have come into view and have been studied. This study propounds a holistic design solution for the CHP systems' inadequacy to meet varying consumer energy demands in residential and the excessive electricity demand created by cryptocurrency mining. In addition, the study defines the possible high efficiency and sustainability for residentials producing and consuming heat and electricity by themselves. An energyâconservative threeâblock residential and a CHP system were projected together by a holistic view balancing the residencies' peak thermal demand to the thermal output capacity of the CHP system. The investment return rate of the CHP system was maximized by optimizing the thermodynamic efficiencies and maximizing the electric generation for cryptocurrency mining. The energetic efficiency increased from 40% to an energy utilization factor of 83%, and exergetic efficiency increased from 39% to 42%. The wasteâexergy ratio decreased from 61% to 58%. The engine's environmental effect factor was 1.56 and reduced to 1.38 with the CHP system. The exergetic sustainability index was improved from 0.64 to 0.72. The benefitâcost ratio was estimated as 1.6, with an internal return rate of 79%. Holistic designs considering common values should be considered to improve sustainability.
Price-responsive demand and dynamic electricity price contracts can play a vital role in balancing renewable energy production and alleviating energy shortages such as those experienced in the European energy crisis. This study focuses on the implicit demand flexibility of residential consumers during extraordinarily high electricity prices in winter 2021/22 in Norway where most households have electric heating and spot price contracts. An econometric model is developed that compares the demand with pre-crisis levels, adjusts for factors influencing electricity consumption, such as outdoor temperature, and utilises a comprehensive dataset including hourly electricity demand data. The results reveal a quick response since the price signal was passed immediately to the customers and substantial energy savings of 11.4 % during winter. While the average household showed no significant short-term price response to daily or hourly price variations, several subgroups did. Particularly, households actively monitoring hourly prices via real-time information channels and those with automatic smart charging of electric cars showed higher load reductions in peak price hours and load shifting to low-price hours. Thus, the study concludes that households are able to respond to variable hourly electricity prices and suggests the promotion of spot price contracts to incentivise residential demand response.
Marco Galici, Emilio Ghiani, Mario Mureddu, Fabrizio Pilo
This paper presents an innovative methodology for managing a local electric market based on artificial intelligence techniques, integrated with a distributed ledger technology platform. The methodology allows an aggregate of users, for example constituting a local energy community, to optimize its energy costs by adopting a local energy market that manages its controllable energy resources in real-time. To achieve this result, the electricity market is managed by means of a distributed ledger platform used for both the certified recording of market operators' bids and for the sharing of a market-solving deep neural network algorithm. This market-solving platform is continuously adapted to the external changes in energy production, consumption and prices. By sharing the state of the system by means of the distributed ledger, the proposed platform allows every operator to locally define its optimal production/consumption and adapting its status according to the community energy needs. The proposed platform has been implemented with a computer-based simulation software and successfully tested for a day-long, 1-minute timestep. The results presented in the paper shown the usefulness of the tool developed in a renewable energy community real case scenario.
Joanna Gusc, Peter Bosma, SĆawomir Jarka, Agnieszka Biernat-Jarka
The current energy prices do not include the environmental, social, and economic short and long-term external effects. There is a gap in the literature on the decision-making model for the energy transition. True Cost Accounting (TCA) is an accounting management model supporting the decision-making process. This study investigates the challenges and explores how big data, AI, or blockchain could ease the TCA calculation and indirectly contribute to the transition towards more sustainable energy production. The research question addressed is: How can IT help TCA applications in the energy sector in Europe? The study uses qualitative interpretive methodology and is performed in the Netherlands, Germany, and Poland. The findings indicate the technical feasibilities of a big data infrastructure to cope with TCA challenges. The study contributes to the literature by identifying the challenges in TCA application for energy production, showing the readiness potential for big data, AI, and blockchain to tackle them, revealing the need for cooperation between accounting and technical disciplines to enable the energy transition.
Typically, residential buildings neither allow flexibility in the individual contract power capacity nor considers buildings as unique electricity consumers. In this work, a smart building is designed that each electricity customer has flexible contract power and the whole collective residential building has a single contract power. A management entity is considered to manage all energy resources of the building such as the photovoltaic generation, electric vehicles, and battery energy storage system, taking into consideration the consumption from apartments and common services, to minimize the electricity bill. Hence, the best/optimal contract power capacity will contribute to minimizing electricity costs. Therefore, finding the optimal decision of the contract power value has received a significant role from the energy management in smart buildings. In this paper, a mixed binary optimization problem is formulated in which not only the optimal value of contract power is yield but the optimal schedule of the electric vehicle/battery storage charge and discharge are found, taking into consideration the photovoltaic generation and load consumption profiles. The proposed model is implemented for three scenarios, and the obtained results show that the model efficiency has a high performance with a significant electricity cost reduction, around 47%. The results pointed that using an optimal value of single contract power and intelligent management system, the building electricity costs decrease remarkably.
Smart homes, connected through a network, can optimize the energy consumption and general load shape of their area. In this work, a blockchain-based smart solution is presented for demand-side management of residential buildings in a neighborhood to improve Peaks to Average Ratios (PAR) of power load, reduce energy consumption, and increase the thermal comfort of occupants by modeling heating, illumination, and appliance systems. For real-time power and temperature monitoring of the neighborhood, a transient numerical physical model has been developed. The simulator has been validated with data measured from a building in Northern Italy. Then, a neighborhood with 2,000 households has been modeled for different occupancy patterns, initial values, and boundary conditions. Two different control scenarios, namely basic and smart, have been considered. In the basic scenario, everything is managed by occupants except the boiler, which is controlled by the indoor temperature of the home. Instead, in the smart scenario, a blockchain-based network has been introduced for buildings to exchange a parameter called the Probability of the Next Hour (PNH). Ethereum Solidity has been deployed for smart contract development in the blockchain. The results show that using blockchain-connected smart controllers aimed at demand-side management can improve PAR, comfort level, and energy efficiency of buildings, which can bring about CO2 reduction on an urban and even global scale.
Shengnan Zhang, Jiaxing Xuan, Zitong Lyu, Yuchen Fu
Disadvantages like cumbersome verification and data centralization are involved in the application and transaction process of Renewable Energy Certificates in China. We realize that blockchain technology has been successfully applied in many fields with its features of decentralization, immutability, and traceability. As a result, we in this article aim to introduce blockchain into the current Renewable Energy Certificates trading system to solve the above problems. Firstly, this article gives an overview of blockchain technology, including its architecture and technical advantages. Secondly, it describes China's Renewable Energy Certificates transaction process and analyzes the potential challenges faced by it. Finally, it proposes a Renewable Energy Certificates trading system based on blockchain technology and analyzes its operation mode, advantages, and potential problems.
Junghoon Woo, Charles J. Kibert, Richard E. Newman, Alireza Shojaei Kol Kachi · 6 authors
The widespread and massive effects of climate are now inevitable, and action must be taken by all sectors to mitigate their contributions to its impacts. The building sector accounts for about 40% of global energy consumption and 30% of GHG emissions. This sector must reduce its energy consumption by at least 50% by shifting to hyper-efficient systems and renewable energy to meet the climate change mitigation goal. Certified green buildings are responsible for about 40% of the office markets in the U. S. and utilize the types of strategies that should be implemented by all new construction and major renovations. Certified green buildings, although highly effective in reducing greenhouse gas emissions, are generally considered to be an expensive solution to this problem. There is excellent potential for the construction sector to employ a blockchain framework of measurement, report, and verification (MRV) towards building energy performance (BEP) to enable certified green buildings to earn carbon credits based on their exceptional energy performance. Blockchain technology eliminates the need for intermediaries to validate the data and builds up a reliable, immutable, traceable energy monitoring system. The goal of this paper is to present a new blockchain digital MRV architecture for existing BEP and a prototype of its application.
Yuta Susowake, Hasan Masrur, Tetsuya Yabiku, Tomonobu Senjyu · 7 authors
In Japan, residents of apartments are generally contracted to receive low voltage electricity from electric utilities. In recent years, there has been an increasing number of high voltage batch power receiving contracts for condominiums. In this research, a high voltage batch receiving contractor introduces a demandâresponse in a low voltage power receiving contract, which maximizes the profit of a high voltage batch receiving contractor and minimizes the electricity charge of residents by utilizing battery storage, electric vehicles (EV), and heat pumps. A multi-objective optimization algorithm calculates a Pareto solution for the relationship between two objective trade-offs in the MATLAB Âź environment.
Den europeiska energisektorn genomgĂ„r numera en viktig övergĂ„ng frĂ„n en centraliserad elkraftförsörjning till distribuerad elproduktion frĂ„n förnybara kĂ€llor. Dessutom leder utfasningen av fossila brĂ€nslen till en ökning av antalet elfordon (hĂ€r EV). Höga penetrationsnivĂ„er för bĂ„de EV och förnybara energin pĂ„ distributionsnivĂ„n kan orsaka ytterligare belastning pĂ„ elnĂ€tet, vilket kan leda till avbrott i strömförsörjningen och försĂ€mring av strömkvaliteten. I detta examensarbete undersöktes möjligheterna att lösa detta problem i Tyskland. Den föreslagna lösningen Ă€r ett förvaltningssystem för EV-laddning och lokal förnybar elproduktion/-koppling i realtid. Tre anvĂ€ndningsfall utvecklades för att analysera denna lösning. Det första anvĂ€ndningsfallet âhyresgĂ€sternas elâ Ă€r baserat pĂ„ den nya tyska förordningen som infördes 2017 och frĂ€mjar att anvĂ€nda solenergi âbakomâ elmĂ€taren i flerbostadshyrehus. I detta fall, genom att erbjuda en EV-laddningstjĂ€nst, kan hyresvĂ€rden uppnĂ„ en högre konsumtionsnivĂ„ under solskenstimmarna nĂ€r hyresgĂ€sterna Ă€r pĂ„ jobbet, och dĂ€rmed fĂ„ en bĂ€ttre ersĂ€ttning. Betalningsperioden för en 11 kW laddsstation, som skulle anvĂ€ndas tillsammans med en PV av 26 kWp, berĂ€knades vara cirka 5 Ă„r om laddstationen Ă€r upptagen 30-40 % av den möjliga dagsljustiden. Om laddstationenen har installerats pĂ„ grund av andra Ă€ndamĂ„l kan âhyresgĂ€sternas elâ-modellen bli en extra inkomstkĂ€lla. De andra tvĂ„ anvĂ€ndningsfallen beror pĂ„ möiligheten att införa en âminskad elnĂ€tavgiftâ. HĂ€r mĂ„ste man nĂ€mna att insatser att föra EV-laddningen pĂ„ tid och plats för förnybar elproduktion mĂ„ste motiveras. Numera Ă€r elpriset fast i Tyskland för smĂ„förbrukare som betyder att det inte finns nĂ„gon orsak för en beteendeförĂ€ndring av EV-förare. En minskad elnĂ€tsavgift kunde bli en Ă„tgĂ€rd för att frĂ€mja âEV-laddning + lokal förnybar elproduktionâ-kopplingen; den kan beviljas av en distributionssystemoperatör (DSO) ifall denna EV-laddning skulle hjĂ€lpa att undvika stockningar och avkortning i elnĂ€tet. Det andra anvĂ€ndningsfallet innebĂ€r att införa en sĂ„dan minskad elnĂ€tavgift för EV-laddning med lokal sol- (PV) eller vindel, som inför dynamisk prissĂ€ttning. I det hĂ€r fallet ska lokala elproducenter behöva sĂ€jla el till lokala laddstationer pĂ„ ett peer-to-peer (P2P) sĂ€tt. Enligt gĂ€llande regelverk Ă€r ren P2P-handel inte möjlig; den skulle behöva inrĂ€ttning av lokala energimarknader och ytterligare balansering. Vad man kan göra kallas direktmarknadsföring, vilket Ă€r en elmarknadsmodell som utförs av en aggregator. AnvĂ€ndningen av blockchain som ett verktyg skulle bli vĂ€lgörande för bĂ„da fallen eftersom det skulle tilllĂ„ta realtids - frĂ€mja âEV-laddning + lokal förnybar elproduktionâ-kopplingen med dynamisk prissĂ€ttning. Ifall man gör P2P-handel möjligt, skulle blockchain ocksĂ„ bli anvĂ€ndbar för betalningar, medan införandet av blockchainbaserade betalningar konstaterades att inte vara genomförbart under den direktmarknadsföringsmodell som existerar idag. Det tredje anvĂ€ndningsfallet innebĂ€r âsjĂ€lvkonsumptionâ/âframmeâ-elmĂ€taren, nĂ€r PV / (vindkraftverk)-Ă€garen och EV-Ă€geren Ă€r samma person; sĂ„ nĂ€r hen laddar sin bil samtidigt med elploduktionen, skulle hen inte behöva betala för kilowattimmar och, beroende pĂ„ distansen mellan de tvĂ„ elanslutningspunkterna, skulle hen dĂ€rmed kunna fĂ„ rabatt pĂ„ elnĂ€tavgiften. För det hĂ€r fallet konstaterades det att enligt den nuvarande direktmarknadsföringsmodellen, dĂ€r aggregatorn och laddstationsleverantören tillhör samma företag, skulle ett sĂ„dant anvĂ€ndningsfall tveklöst kunna genomföras pĂ„ grund av gemensam bokföring. Ett sĂ„dant fall kan bli ett attraktivt erbjudande, sĂ€rskilt för PV-Ă€gare som inte fĂ„r inmatningsavgiften. P2P-handelns slutsatser liknar det tidigare anvĂ€ndningsfallet. För det andra och tredje anvĂ€ndningsfĂ€llet upptĂ€cktes det att i den situationen dĂ„ P2P-handel Ă€r möjlig, skulle EV-laddningen inte uppfylla "försĂ€ljningsbehovet" för producenter eftersom den inte Ă€r fullt förutsĂ€gbar. DĂ€rför mĂ„ste urvalet av P2P-köpare utvidgas till stationĂ€ra konsumenter; d.v.s. att bredda det föreslagna systemets funktionaliteter frĂ„n bara EV-laddning till fullstĂ€ndig P2P-handel. Eftersom EV-laddningen skulle behöva göras i realtid, vara flexibel för laddningsförhĂ„llanden, uppfylls behov av flera andelsĂ€gare och att vara manipulationssĂ€kert, föreslĂ„s distribuerad ledgerteknik (DLT) som implementeringsverktyg. Av tvĂ„ olika DLT, Ethereum och IOTA, drogs slutsatsen att teknikurvalet för att implementera det föreslagna systemet beror pĂ„ implementeringstiden. FrĂ„n och med idag ligger Ethereum i ett högre stadium i utvecklingen , vilket prioriterar Ethereum för omedelbar implementering. Samtidigt Ă€r IOTA en mycket lovande teknik i ett lĂ€gre löptidstillstĂ„nd. NĂ€r de löser ett antal kontroversiella problem blir IOTA ett vĂ€rdefullt verktyg.
Vasiljevska Julija, Jochem Douw, Anna Mengolini, Igor NikoliÄ
EU Regulation / /EC concerning common rules for internal market in electricity calls upon % of EU electricity consumers to be equipped with smart metering systems by , provided that a positive economic assessment of all long-term costs and benefits to the market and the individual consumer is guaranteed. Understanding the impact that smart metering systems may have on the electricity stakeholders (consumers, distribution system operators, energy suppliers and the society at large) is important for faster and e ective deployment of such systems and of the innovative services they o er. For this purpose, in this paper an agentbased model is developed, where the electricity consumer behaviour due to di erent smart metering policies is simulated. Consumers are modelled as household agents having dynamic preferences on types of electricity contracts o ered by the supplier. Development of preferences depends on personal values, memory and attitudes, as well as the degree of interaction in a social network structure. We are interested in exploring possible di usion rates of smart metering enabled services under di erent policy interventions and the impact of this technological di usion on individual and societal performance indicators. In four simulation experiments and three intervention policies we observe the di usion of energy services and individual and societal performance indicators (electricity savings, CO 2 emissions savings, social welfare, consumers' comfort change), as well as consumers' satisfaction. From these results and based on expert validation, we conclude that providing the consumer with more options does not necessarily lead to higher consumer's satisfaction, or better societal performance. A good policy should be centred on e ective ways to tackle consumers concerns.
Installation of smart meters is increasing world-wide, opening the possibility to implement time-of-use (TOU) tariffs to moderate peak loads. This study is focused on the design of an optimal opt-in residential TOU tariff. Residential consumers are assumed to act in their private interests and maximize utility in response to tariffs. The regulated utility has a broader interest in maximizing societal welfare. However, the regulated utility cannot impose household behavior and cannot directly observe household type. Instead, the regulated utility must offer contract options including both a TOU tariff and current pricing to allow households to self-select the plan best suited to their interests. This paper proposes a simple flexible household utility function that can be calibrated with minimal data to describe diverse household behaviors and reveal household responses to different prices. An optimal pricing model is designed for the regulated utility, taking account of asymmetric information and potential household opportunistic behavior. Using economic constructs from principal-agent theory, the pricing model ensures participation among households most aligned with the regulated utility's desire. The pricing model can also be extended for competitive markets. A case study is performed to demonstrate the benefit the optional TOU tariff can realize.
In the smart grid, large consumers can procure electricity energy from various power sources to meet their load demands. To maximize its profit, each large consumer needs to decide their energy procurement strategy under risks such as price fluctuations from the spot market and power quality issues. In this paper, an electric energy procurement decision-making model is studied for large consumers who can obtain their electric energy from the spot market, generation companies under bilateral contracts, the options market and self-production facilities in the smart grid. Considering the effect of unqualified electric energy, the profit model of large consumers is formulated. In order to measure the risks from the price fluctuations and power quality, the expected utility and entropy is employed. Consequently, the expected utility and entropy decision-making model is presented, which helps large consumers to minimize their expected profit of electricity procurement while properly limiting the volatility of this cost. Finally, a case study verifies the feasibility and effectiveness of the proposed model.
Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC) and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS) flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.