The Role of Blockchain-Secured Digital Twins in Promoting Smart Energy Performance-Based Contracts for Buildings

Abstract

Energy performance-based contracts (EPCs) offer a promising solution for enhancing the energy performance of buildings, which is an overarching step towards achieving Net Zero Carbon Buildings, addressing climate change and improving occupants’ comfort. Despite their potential, their execution is constrained by difficulties that hinder their diffusion in the architecture, engineering, construction, and operation industry. Notably, the Measurement and Verification process is considered a significant impediment due to data sharing, storage, and security challenges. Nevertheless, there have been minimal efforts to analyze research conducted in this field systematically. A systematic analysis of 113 identified journal articles was conducted to fill this gap. A paucity of research tackling the utilization of digital technologies to enhance the implementation of EPCs was found. Consequently, this article proposes a framework integrating Digital Twin and Blockchain technologies to provide an enhanced EPC execution environment. Digital Twin technology leverages the system by monitoring and evaluating energy performance in real-time, predicting future performance, and facilitating informed decisions. Blockchain technology ensures the integrity, transparency, and accountability of information. Moreover, a private Blockchain infrastructure was originally introduced in the framework to eliminate high transaction costs related to on-chain storage and potential concerns regarding the confidentiality of information in open distributed ledgers.

1. Introduction

Efforts are being made to mitigate environmental impacts and promote sustainability in the architecture, engineering, construction, and operation (AECO) industry. Buildings represent around 40% of the European Union’s (EU) total energy consumption and generate approximately 36% of Europe’s greenhouse gases (GHGs), making the AECO industry one of the most polluting sectors [1]. Net Zero Carbon Buildings (NZCBs) have gained global recognition as a pioneering sustainable development approach to achieve the net zero goal for built environments by 2050 [2]. NZCBs are energy-efficient buildings utilizing on-site or off-site renewable energy sources and verified offsets to achieve equilibrium between energy demand and renewable energy supply, or neutralize carbon emissions linked to annual energy usage and provision [2,3]. Operational carbon is considered one of the primary metrics provided by the EN15978:2011 standard for the zero-carbon assessment, also called the whole-life carbon assessment (WLCA) [4]. Lowering operational carbon emissions can be accomplished by implementing solutions typically offered for Zero Energy Buildings (ZEBs) and Nearly Zero Energy Buildings (nZEBs), such as integrated designs, minimized plug loads, and energy-efficient retrofits [5]. In the same context, in the last decade, the European Union (EU) has developed policies to accelerate the cost-effective retrofitting of existing buildings, with the vision of a decarbonized building stock by 2050 [6]. Even though it is possible to construct new energy-efficient structures, most energy consumption is still attributed to current buildings, emphasizing the critical need to enhance their energy efficiency [7]. This situation makes investors, owners, and users face an immense challenge. It is necessary to invest in saving measures to improve the energy performance of buildings, which entails a considerable short-term financial commitment with relatively long payback periods. Furthermore, increasing and accelerating the extent of building renovation is crucial in post-COVID-19 economic recovery [8]. Energy Performance-based Contracting (EPC) is among the potential strategies to achieve this goal and improve the energy efficiency of buildings [9].

EPC, as defined by the Energy Efficiency Directive 2012/27/EU, is a type of ”creative financing” for capital improvement that allows the funding of energy upgrades from cost reductions [10]. EPC has the potential to accelerate the pace of energy renovation for current buildings and encourage the application of energy-efficient measures in upcoming constructions [11]. These agreements are established between the client and a private entity that serves as a service provider, often known as an “Energy Service Company” (ESCO) [12]. This contract model offers a mutually beneficial outcome where owners can reduce energy expenses while providers profit from continuous incentives and a new service offering. EPCs are set to become more widespread as awareness of their benefits and cost savings increases.

The utilization of EPCs has not been extensively embraced in the built environment. Academics have identified challenges with accountability, the absence of standardized performance assessments, novel and unfamiliar financial concepts, and the added burden of upfront communication between parties [13]. Nevertheless, the continuous digitalization of the AECO industry and advancements in technologies such as Digital Twins (DTs) and Blockchain present a novel prospect for implementing performance-based building better [10]. DTs can facilitate performance-based contracting by establishing performance expectations via simulation, continuously monitoring and updating actual performance, and furnishing recommendations for maintenance and operation via analytics. In general, DTs can assist in accurately and equitably forecasting and evaluating performance, thereby surmounting a known obstacle to EPC implementation in the built environment [13].

Moreover, Blockchain can provide an immutable and transparent digital record of transactions. Although CO₂ emissions are generated due to the computational power required, the energy savings facilitated by EPC significantly outweigh these emissions. These savings are achieved by leveraging advanced predictive models and data management techniques that ensure substantial energy efficiency improvements [14]. By integrating Blockchain technology in EPC, the efficiency and reliability of energy savings verification are enhanced, and greater transparency and trust in the energy savings process are ensured, thus contributing to the overall goal of achieving NZCBs. The net effect is a substantial reduction in CO₂ emissions, affirming that the benefits of energy savings far exceed the carbon footprint of the Blockchain system itself [15].

Certain Blockchains (i.e., Ethereum) also allow for the implementation of smart contracts, which utilize scripts to establish tamper-proof transaction logic. Smart contracts are automated computer programs operating within a Blockchain protocol, enabled by the general-purpose computation capabilities of Blockchains. They encompass contractual arrangements, contract execution, and governance of preconditions for contractual obligations. Ethereum introduced the first Turing-complete scripting language with smart contract support, making it a prominent and highly utilized Blockchain platform for smart contracts [16]. Thus, the development of performance-based smart contracts has the potential to be deployed within the Blockchain framework to establish protocols for automating real-world processes. A fundamental challenge for performance-based buildings is accountability, an issue that Blockchain can address by ensuring protection mechanisms that help avoid the risks and costs of opportunistic behavior in construction supply chain collaboration [17]. However, few attempts have been made to study or implement performance-based smart contracts.

To address this issue, the article aims to propose a framework for integrating Digital Twin and Blockchain technologies and demonstrate how the interdependency of these technologies can facilitate the diffusion of EPCs in the AECO industry.

2. Background

2.1. Energy Performance-Based Contracts (EPCs)

EPCs emerged after the first oil crisis in North America in the 1970s. They have evolved as a cutting-edge finance strategy to lower energy use by recouping the expenses of providing energy-saving technologies [18,19]. In 2008, Europe faced a severe financial crisis that affected national economies and caused market uncertainties, especially in Mediterranean countries. Despite limited financial resources, the EU’s energy policy has become more rigorous, with the vision of a decarbonized building stock by 2050 [20]. As a means of conserving energy to meet the EU energy policy objectives and to improve energy efficiency in buildings, EPC is considered a potential approach and has been used by many EU countries [9].

An EPC is a contract agreement between an ESCO and an energy user. The contract sets a specific energy-saving target, and the ESCO provides energy-efficient technologies, financing, installation, and maintenance through an appropriate business model. If executed successfully, the ESCO can recover its investment and earn a reasonable profit, which benefits both parties involved [21]. The EPC concept is illustrated in Figure 1. The EPC’s business model outlines the obligations of both building owners and ESCOs when executing EPC projects and provides a means of distributing risk in such projects [22].

EPC projects are perceived as investments with high levels of risk [23], thus affecting their diffusion in the AECO industry. Despite working on providing accurate initial predictions, various risks and barriers hinder the successful implementation of EPCs. Inadequate financing options resulting from conservative lending practices, insufficient familiarity with performance-based project financing, and alterations in economic and market circumstances are considered financial challenges facing EPC projects [22]. In addition, a lack of performance savings standardized Measurement and Verification procedures, a lack of reliable data to optimize performance, alack of knowledge of the technology and its benefits, potential changes in governmental policies, climate change, and unanticipated or inappropriate building usage may influence the energy-conservation benefits of EPCs [24,25]. Ultimately, there is an overall lack of awareness about EPCs among AECO industry stakeholders.

2.2. Energy Service Companies (ESCOs)

As aforementioned, EPCs are agreements established between clients and service providers. The clients can be either public or private organizations, while the service providers are usually private companies known as Energy Service Companies [12]. Experts and scholars have identified the services provided by ESCOs as promising opportunities to fulfill consumers’ energy requirements more sustainably [26]. The definition of ESCOs differs from country to country. However, an ESCO is typically responsible for implementing energy efficiency measures and ensuring their effectiveness. They are also responsible for monitoring the contract and may not receive a payment if they fail to meet the energy savings agreed upon in the contract [20]. Thus, their remuneration is associated with project performance.

ESCOs may differ in their operational methods in EPC projects, but the primary distinction lies in whether they offer funding for the project they are implementing or not [22]. ESCOs can obtain the necessary investment from their funds or through financing options offered by a third-party financial institution. The success of ESCOs is influenced by several crucial factors, such as the size and flexibility of the banking system involved in energy-performance contracting, the structure of the energy-efficiency market, the local institutional environment, the technical, financial, and business expertise of ESCO personnel, as well as potential clients and funders, and most notably, access to financing [27].

2.3. Measurement and Verification in EPC

The energy savings achieved through EPC projects are commonly disputed because they serve as the foundation for contract payments and adherence [28]. Disputes are one of the major risks that hinder the diffusion of EPCs in the AECO industry due to a lack of trust and intention to cooperate between stakeholders in EPC projects. In an ideal situation, disputes regarding energy savings in EPC projects are resolved through the Measurement and Verification (M&V) process [29]. M&V is intended to confirm the enhancements provided through energy conservation measures (ECMs) by evaluating the actual performance of buildings once the installation and construction work on the system is finished and a consistent level of operation has been achieved [30,31]. The evaluation and communication of the effectiveness of the installed ECMs according to an M&V plan is typically the responsibility of ESCOs [32]. A quality M&V is the means by which actual savings are quantified and could be considered an insurance policy [28].

Conventionally, M&V calculations have been carried out utilizing techniques chosen on a per-case basis, considering the ECM’s characteristics, the projected savings, and the available site data [33]. However, a number of M&V protocols have been created to enhance uniformity and minimize ambiguity in gauging the energy savings derived from retrofitting existing buildings [30]. Two approaches that are commonly acknowledged are the International Performance Measurement and Verification Protocol (IPMVP) provided by the Efficiency Valuation Organization (EVO^®) [34] and ASHRAE Guideline 14 [35]. M&V protocols prioritize quantitative requirements and may not cover all issues in a building’s performance gap. On-site investigations may only uncover some technical issues and may not reflect all key causes [36].

Recent technological advancements, such as “smart” meters and energy management and information systems (EMISs), have enabled more rapid and cost-effective M&V processes. Utilizing more sophisticated data analytics techniques on more detailed datasets with shorter time intervals, which could be automated and conducted regularly, would offer viable solutions [37]. These technologies assist in conserving energy and provide functionalities that exceed conventional M&V approaches. Evolving M&V techniques towards responsive, dynamic, and precise approaches are commonly known as Measurement and Verification 2.0 (M&V 2.0) [38]. M&V 2.0 leverages metered data to improve real-time performance evaluation, tenant participation, and resource management through the use of analysis tools and algorithms. Additionally, hardware and software advancements have enhanced the precision of M&V functions, such as baseline modeling, detecting anomalous events, and establishing energy consumption benchmarks [30]. However, M&V requirements need to be more strictly prescribed in EPCs.

2.4. Role of Digital Technologies for Energy Performance in AECO

The incorporation of innovative technologies like Digital Twins, Internet of Things (IoT), and Artificial Intelligence (AI) is deemed as a very auspicious solution to tackle the issues confronted by the AECO industry [39], which include inadequate compliance with regulations, poor performance, ineffective communication, fragmentation of information flow, and a lack of trust among different stakeholders [40].

The utilization of DT technology enables an improvement in evaluating buildings’ real-life performance by duplicating their actions and behavior in various situations, ensuring that all involved stakeholders remain informed and up-to-date. The process involves amalgamating data collected from multiple sources, including sensors (IoT), Building Information Modelling (BIM) models, and simulations, enabling the examination of the building’s energy efficiency and indoor environmental quality. It also facilitates the evaluation of the impact of different design and operational tactics [41] that affect decision-making for smart asset management [13]. Thus, DTs have the potential to evaluate the energy performance of buildings, paving the way for solutions to the risks associated with EPC.

In all DT applications, IoT is regarded as the fundamental technology. Indeed, a recent study has predicted that over 90 percent of all IoT platforms will have Digital Twinning capability by 2028 [42]. IoT uses sensors to collect data from real-world objects, which can be used to create a digital duplicate of a physical object. The digital replica can be scrutinized, optimized, and manipulated. With the assistance of IoT, which continuously updates data, DT applications can produce a virtual, real-time model of a physical object. In the same context, AI can support DTs as an advanced analytical tool that can automatically scrutinize the collected data, furnish valuable insights, generate predictions about the potential outcomes, and suggest how to avoid potential problems [43]. Thus, IoT and AI technologies could provide granular data using automated data analytics, which is necessary to evaluate EPCs better.

Furthermore, Blockchain, a popular type of Distributed Ledger Technology (DLT), provides trustworthiness, security, quality, and data openness. Decentralized Applications (dApps) are web applications that utilize Blockchain technology to store and manage their interactions [44]. These dApps depend on distributed ledgers and decentralized databases, which will eliminate the reliance on a single trusted source and establish a secure framework for sharing lifecycle information. This is especially crucial in a complicated ecosystem where stakeholders engage with DTs. While ensuring the required integrity, confidentiality, and availability, this approach can address the data exchange challenges [45]. With Blockchain employed, transactions’ legitimacy would be guaranteed, and cryptography and consensus mechanisms can be employed to facilitate the validation and traceability of high-value transactions. Thus, incorporating Blockchain technology in the AECO industry and its fusion with DTs and BIM for managing lifecycle information holds enormous potential to address concerns regarding trust, transparency, and communication [46], tackling trust issues between EPC stakeholders.

To that extent, digital technologies have an important role in advancing the AECO industry. Nonetheless, academics have urged investigating how novel business and financing models of performance contracts can be combined with emerging automation technologies such as DTs and IoT [47], but little research has explored this in detail.

Table 1. The added value of DT and Blockchain technologies for EPC in buildings.

Aspect	Added Value
	Digital Twin	Blockchain
Enhanced Performance Evaluation	Creates high-fidelity virtual models of buildings, allowing real-time monitoring, simulation, and optimization of energy performance, which lead to more accurate performance evaluation and proactive maintenance, which are critical for successful EPC implementation [13].	Ensures data integrity and transparency, facilitating secure and tamper-proof recording of energy performance data, enhancing stakeholder trust, and streamlining the verification process [14].
Improved Data Management	Integrates various data sources into a single platform for comprehensive analysis and better decision-making for energy optimization [48].	Blockchain secures data storage and sharing, addressing data manipulation and unauthorized access concerns that are particularly beneficial for managing large volumes of energy data generated by smart buildings [40].
Automation and Smart Contracts	The combination of DTs and Blockchain enables the automation of EPC processes through smart contracts, which automatically execute and enforce contract terms based on predefined conditions and real-time data [49]. This reduces administrative overhead, minimizes disputes, and ensures timely and accurate performance-based payments, thereby increasing the efficiency and reliability of EPCs [14].

summarizes the added value of using DT and Blockchain technologies for promoting EPC for buildings, highlighting how they address issues not fully resolved by other technologies.

3. EPC in AECO

3.1. Search Methodology

The selection for this review was restricted to published or in-press journal articles and review articles. The review covered articles from three electronic databases: Scopus, Web of Science, and ScienceDirect. It was conducted using the reference management program Mendeley. The retrieved articles were from databases that guarantee the quality and reliability of indexed scientific journals (e.g., Science Citation Index (SCI), Science Citation Index Expanded (SCI-E), or Engineering Index (EI)). The “article title/abstract/keyword” field was used for the search. The terminology used in the literature search was influenced by a preceding search using generic terms. In this search, journals containing the keywords combination ((“performance contract*” OR “performance-based contract*”) AND (“energy savings” OR “energy performance” OR “energy efficiency” OR “energy performance gap” OR ESCO OR “energy service compan*”)) in the title, abstract and keywords were selected. The selection process was based on the following inclusion criteria:

• Publication year: 2013 to 2023;
• Document type: articles and review articles;
• Source type: journals;
• Language: English;
• Others: subject areas limited to engineering, energy, and environmental sciences.

Articles were recorded and tracked for each limitation applied, with records of the initial count of articles and the number excluded by each limitation. Selected studies from the three databases were exported to Mendeley for filtering to eliminate duplicated records. Full-text documents were collected for articles that met the inclusion criteria based on their title and abstract. If the relevance was unclear to the research objectives, the article was still considered relevant, and the full text was collected. A backward-snowballing process was also used to identify older articles that could provide the corresponding information. A flowchart representing the search methodology is shown in Figure 2.

The database search yielded 967 publications, of which 391 were considered for filtering based on the inclusion criteria. After removing duplicates, 188 publications were retrieved, and after excluding non-related topics, 152 articles were left for further analysis. A more in-depth examination of the title, abstract, and keywords was conducted to ensure that only articles related to EPC in the AECO industry were included, resulting in 113 relevant articles for the study.

3.2. Search Results/Analysis

In order to better analyze the selected articles, it was essential to categorize articles that have applications for buildings from conceptual articles. As shown in Figure 3, two main groups were identified. The buildings group includes 81 articles tackling the building sector (e.g., commercial, residential, and generic types of buildings) [12,20,24,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126], while the remaining 32 articles tackled conceptual studies that focus on non-building related EPC applications (e.g., review articles) [22,28,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156]. There are few review articles in this field. Zhang and Yuan (2019) [137] and Shang et al. (2017) [142] are two notable studies addressing challenges related to EPC; however, specific difficulties of EPC implementation in achieving Net Zero Carbon Buildings, particularly the data sharing, storage, and security issues in the M&V process, were not comprehensively addressed, which highlights the importance of developing research work that provides more in-depth and up-to-date insights on these specific challenges. Thus, in the context of the challenges mentioned above, the categorized data were further studied to provide several insights about the current state of EPC diffusion in the AECO industry, highlighting current limitations and future opportunities.

The data presented in Figure 4, regarding the number of EPC-related publications in the AECO industry, demonstrate interesting trends over the past decade. The number of publications in both the buildings and conceptual categories has an upward trend, but it is not clearly a steady increase since 2013, with a peak of 13 publications in the buildings category in 2018 and 9 publications in the conceptual category in 2016. Interestingly, while the number of publications in the buildings category remained relatively consistent in recent years, the conceptual category saw a decline in publications from four in 2019 to one in 2021. Nonetheless, both categories saw a slight increase in 2022, followed by a slight decrease again in 2023. These findings indicate approximately an average of 10 publications per year, which highlights the need for further research to optimize the effectiveness and implementation of EPCs.

From a deeper aspect of the studies included in the building group, the distribution of studies related to EPCs was classified according to the building type, which reveals some interesting insights into the current focus of EPC research, as shown in Figure 5. The data show that most studies have focused on commercial buildings, with 59 papers (63%) dedicated to this building type. In contrast, only 18 studies (19%) have focused on residential buildings, indicating a significant research gap in this area. The remaining 17 studies (18%) are categorized as generic, which may include studies that do not differentiate between building types. The significant disparity in the number of studies between commercial and residential buildings suggests that implementation and optimization of EPCs in commercial buildings has received greater attention than in residential buildings. This distribution highlights the need for more research focused on EPCs in residential buildings, as these buildings represent a significant portion of the overall building stock and can benefit from implementing EPCs in terms of energy savings and environmental impact.

Moreover, mapping EPC publications related to buildings in the AECO industry by country of application in the case studies provides valuable insights into the research trends and priorities in this field. The data in

Table 2. Mapping EPC publications related to buildings in the AECO industry by country.

Country	No. of Publications	Country	No. of Publications
China	17	Poland	1
USA	13	Iran	1
Italy	6	Switzerland	1
France	5	Germany	1
UK	4	Portugal	1
Canada	3	Croatia	1
Malaysia	3	Greece	1
Netherlands	3	Denmark	1
UAE	3	Ukraine	1
Taiwan	2	Slovakia	1
Norway	2	Russia	1
Spain	2	Latvia	1
Australia	2	Turkey	1
Hong Kong	2

reveal that China and the USA lead the number of publications, with 17 and 13, respectively, constituting about 37.5 percent of the publications. Italy, France, and the UK also have a significant number of publications, with six, five, and four, respectively. It is worth noting that some countries, such as Switzerland, Germany, and Portugal, have only one publication each, indicating that EPC research in these countries may still be in the early stages. This mapping provides a valuable starting point for further EPC research analysis and comparison in different countries and regions.

Furthermore, published articles within the building category were classified into four main research topic areas, as shown in Figure 6. The provided data offered valuable insights into the current focus of EPC research within the industry. The data indicate that EPC development has been the most prominent research topic, with almost 36 percent of published articles showing a strong interest in exploring and improving the processes, methodologies, and strategies associated with EPC development [20,157,158]. Following closely behind, EPC execution challenges, legal and contractual constraints, financial mechanisms and business models evaluation analysis, and market studies of EPC and ESCO diffusion have garnered attention, with around 32.5 percent of published articles [12,159,160]. This demonstrates the significance of addressing the practical and contractual aspects of EPC implementation and the financial considerations and market dynamics associated with such contracts. Published articles focusing on understanding the decision-making processes and managing, identifying, and classifying risk and uncertainty factors in EPC projects have also been substantial research topics, with 23 percent of published articles [161,162,163,164].

Lastly, the effective M&V of the energy savings achieved by EPC projects has been largely ignored. However, few studies have acknowledged that M&V is critical for implementing EPC projects. Ke et al. [165] explored the analysis of building energy consumption parameters and M&V of energy savings. The study focused on calibrating a building energy model that facilitates M&V energy savings. The calibrated model was utilized to analyze the impact of changes to energy consumption parameters on the overall energy consumption in the building, providing valuable insights into energy management strategies. Park et al. [166] presented a methodological approach for calibrating building energy-performance simulation models to ensure accurate M&V energy savings. In 2019, Newsham [33] utilized a case study to assess the effectiveness of M&V methods. Specifically, a simple regression-based M&V approach was applied to analyze whole building energy data. Alfaris et al. [167] explored the energy performance of retrofitted buildings undergoing an EPC during the COVID-19 pandemic. The study focused on the approach to be taken and its impact on monitoring the energy profile following the IPMVP. The data collected were then compared with the baseline model to assess the effectiveness of the EPC.

Piccinini et al. [31] and Agenis et al. [168] provided M&V applications for an EPC. The former proposed a novel Reduced Order Model (ROM) framework that facilitates the estimation of energy savings in building retrofits. The ROM was incorporated in the IPMVP to support the M&V of energy savings. The study demonstrated and validated the ROM’s ability to forecast energy consumption in an operating educational building. The latter proposed an automated method for selecting the most relevant baseline model based on the IPMVP, which was generalized to handle cases where contracts involve multiple buildings of various types or consumption ranges. The method identified a common best model using new dimensionless indicators, which was useful in buildings with different energy profiles.

Despite their potential benefits, M&V studies have yet to fully leverage the advantages of integrating digital technologies such as DTs, IoTs, Blockchain, and AI into the M&V plan. By utilizing these technologies, it is possible to adjust the physical project’s real-time behavior according to the virtual model’s performance assessments. This could significantly improve the accuracy and efficiency of M&V, paving the way for the widespread adoption of EPCs in the AECO industry.

3.3. Identifying Research Limitations in EPC

This article clearly shows that the building sector is the focus of many studies. However, only a small percentage of these—8.5%—is dedicated to the vital aspect of Measurement and Verification [31,33,109,165,166,167,168]. Additionally, no studies related to the residential sector have been found to address M&V. Advanced M&V, or M&V 2.0, has only been studied in two research articles [33,109]. Moreover, only a fifth of studies related to the building sector are concerned with the residential sector. Interestingly, although energy performance certificates are frequently mentioned in M&V-related articles, they are only discussed in the abstract in 70%, and no studies have explored the relationship between M&V and EPC contract terms. Only one study has explored the potential of Digital Twin and Blockchain technologies or smart contracts concerning EPCs [13]. However, the study’s use of Digital Twins did not fully utilize their potential to adjust the physical product’s real-time behavior according to the virtual model’s performance assessments.

These research gaps highlight the need for further investigation and exploration of M&V, EPCs, and their relationship with Digital Twin and Blockchain technologies to promote the diffusion of EPC projects in the AECO industry.

4. A Framework for Delivering a Smart EPC Using Digital Twin and Blockchain Technologies

4.1. Overview

In this section, the authors aim to develop a framework that applies to energy performance contracts for building projects. The fundamental idea of this framework is to utilize digitalization by integrating DT and Blockchain technologies to deliver a smart EPC. The framework facilitates a trustworthy M&V environment that encounters trust problems and disputes that arise between stakeholders resulting from poor and inaccurate performance management and evaluation in EPCs, which disincentivizes its diffusion in the AECO industry.

The proposed framework uses multi-layered architecture applicable to EPCs in building projects. The following sections will describe the logical structure of the framework. Section 4.2 provides an overview of the framework’s architecture. Section 4.3 emphasizes the Digital Twin layer of an asset and its sublayers. Section 4.4 explains the Blockchain service layer and its sublayers. Section 4.5 describes what a Virtual Data Room provides for stakeholders.

4.2. Framework Architecture

In the same context of this research, the proposed framework illustrated in Figure 7 consists of three main layers: (1) the Digital Twin of an Asset; (2) the Blockchain Service layer that is characterized by two sublayers, the private Blockchain infrastructure and the Consortium Blockchain; and (3) the Virtual Data Room. The framework’s logic starts with the Digital Twin layer, which provides the base of the M&V environment. The DT layer focuses on integrating static and dynamic building data. The static data of the building is provided through the as-built BIM model (i.e., IFC files). Dynamic data is fed by a real-time data stream captured by sensors attached to physical assets, which is then transmitted to the virtual space in the Digital Twin. This approach to conveying information facilitates swift recognition of underperformance issues, thereby enhancing the ability to take immediate actions and make informed decisions to help optimize a building’s energy efficiency through bi-directional dynamic data communication and analytics.

Choosing an adequate infrastructure for Blockchain application depends on several factors including robustness, information privacy, development and maintenance costs, and speed [169]. The increasing use of AIM and DTs raises concerns about data security and privacy, particularly when the collected data include private information about asset performance and users [170]. These digital models may contain sensitive data, such as occupancy and consumption of water and electricity, which should remain confidential. Additionally, real-time building data, such as indoor air quality, comfort levels, number of occupants, or actual storage levels, can be linked to expected performance and have contractual implications [171]. In this study, since the data from buildings’ energy performance can be sensitive for privacy and legal reasons, a private Blockchain is selected.

To the authors’ knowledge, the Blockchain service layer is the first integration of a private Blockchain infrastructure using BigchainDB software v 2.2.2 [172] and a Consortium Blockchain (e.g., Ethereum) to a building Digital Twin for an energy performance-based smart contract in the AECO industry. The use of BigchainDB software as a private Blockchain infrastructure offers a combination of the perks of a typical Blockchain and a typical distributed database, such as decentralization, immutability, owner-controlled assets, low latency, high transaction rate, no transaction fee, the permission of access for stakeholders, indexing, and querying of structured data [173]. The authors believe that these advantages help mitigate major challenges—hindering the diffusion of using Digital Twin Blockchain-based energy performance-based contracts—posed by data storage due to high transaction costs resulting from the high intensity of sensor data (i.e., in public Blockchains, every transaction of adding sensor data to the network is subjected to a transaction fee that is determined through the computation of the required computing resources (gas amount and the multiplication of this value by the gas price) and possible concerns regarding the confidentiality of information (e.g., energy data) in open distributed ledgers. In addition, the performing complex performance evaluation and optimization is impossible to execute on Consortium (public) Blockchains.

Finally, the Virtual Data Room provides a user interface that allows each stakeholder permission to access their information and to interact with performance data, triggered actions, and contract functions in a user-friendly environment. Overall, the authors believe the proposed framework to be effective for implementation to manage the performance of energy applications in buildings, enabling real-time adjustments, flexibility, and independent decision-making for interventions and operations.

4.3. Digital Twin of an Asset

The Digital Twin layer serves as a dynamic and interconnected platform that enables real-time monitoring, analysis, simulation, and optimization, facilitating enhanced operational efficiency, predictions, informed decision-making, and effective resource utilization of buildings. This layer comprises three sublayers: (1) The physical/built asset that involves the interaction of physical subsystems, such as sensors and actuators, which operate within the system to monitor and control various aspects of the building’s functions through capturing real-time conditions such as temperature, humidity, light intensity, and occupancy. (2) The Asset Information Model (AIM) that contains only required information containers transferred from the as-built BIM model, which are based on the requirements of the building’s energy performance management besides essential sensor information containers to provide a real-time update on energy-related parameters. The process of selectively filtering the information containers from the Project Information Model (PIM) to the AIM prevents the inclusion of unnecessary information that could burden various stakeholders. (3) The data visualization, integration, and analysis sublayer offers comprehensive solutions for processing raw data into actionable information using data analytics techniques rooted in statistical theory, Artificial Intelligence, and Machine Learning algorithms.

Overall, in the DT layer, a baseline model is initially developed, and real-time updated models are subsequently generated by collecting current operational indicators. These models are employed to quantify energy savings and assess the fulfillment of predefined energy performance contract conditions. Moreover, it enables the integration of a dynamic display feature within the Virtual Data Room, which will be further elaborated upon. Once a substantial dataset has been accumulated, the data are integrated into the system’s algorithm to enable automated control and feedback adjustment. Simultaneously, the system can forecast future scenarios and offer recommendations.

In light of the challenges encountered due to the absence of standardized guidelines governing the practical implementation process of DT, the approach used in this proposed framework is based on a previously established standardized DT framework developed by the authors [174]. The standardized DT framework integrates the BIM ISO 19650 standards [175,176,177,178] in the DT processes to facilitate interoperability between the used digital technologies (i.e., Digital Twins and Blockchain).

4.4. Blockchain Service Layer

The key challenge of utilizing Digital Twin technology to enhance the energy performance evaluation and dispute elimination in EPCs is to make the process tamper-proof. Thus, developing secure data sharing and a smart contract is essential for effectively managing a complex system consisting of interconnected Digital Twins and various stakeholders. For this purpose, the Blockchain layer serves as the foundation layer for the Digital Twin that ensures the integrity, transparency, privacy, and accountability of information through the framework. The architecture demonstrates how the Blockchain securely and reliably handles all transactions within the Digital Twin, making the information from the Digital Twin trustworthy. As a result, it can be utilized for smart contract execution and/or payment with confidence.

A core step in evaluating energy performance successfully is to provide accurate and safely exchanged data. IoT provides an accurate and automated data source, which helps eliminate human errors. As mentioned, the collected data are stored in a central repository named “Information containers”, which is presented as a part of the BIM processes defined by the ISO 19650 series. On the other hand, the Blockchain ensures the safety of the data exchanged and stored for smart contract execution. However, storing performance data within the smart contract on public Blockchains always poses major challenges, such as high transaction costs and concerns regarding data privacy [13]. In the same context, if data are stored locally off-chain (centralized), the usefulness of the Blockchain is diminished, or the Blockchain network does not store all the data from IoT or DTs, but only stores and shares data required for evaluation. Thus, a trade-off exists between increased trust at the expense of higher on-chain data storage costs or opting for off-chain data storage with reduced trust.

The core idea of this framework is to add a private Blockchain sublayer, accessed through permission, that works as an intermediate layer between the Digital Twin layer and the smart contract layer. The European Data Protection Supervisor (EDPS) emphasizes the need for managing personal data—such as altering, deleting, and selectively disclosing it—to protect individuals’ privacy [179]. Ideally, to facilitate data deletion, Blockchain participants would need to establish a mutually agreed-upon process for collectively executing lawful requests to erase personal data from decentralized ledgers [180]. From a technological standpoint, research on eliminating Blockchain’s immutability while maintaining security is still in its early stages [181]. More explicitly, the clash between immutability and privacy/data protection rights makes absolute immutability a significant obstacle to the adoption of Blockchain technology when personal data are involved [182]. From this viewpoint, recent progress in incorporating mutability, governed by strict, pre-approved rules, is attractive to both regulators and businesses [183]. Off-chaining techniques are currently viewed as essential in Blockchain-based application development due to their significant advantages, such as lowering Blockchain data storage needs, thereby reducing scalability issues and ensuring compliance with the General Data Protection Regulation (GDPR) [181,184,185]. Moreover, academic research utilizing off-chaining techniques used as a private Blockchain infrastructure for storing actual information [186,187], have been suggested for aligning Blockchains with the GDPR privacy requirements [181].

In this study, the selection of a private Blockchain architecture provides further control over the ledger itself, including decommissioning, as it explicitly enables their right to be forgotten (also known as erasure) [188] when the ledger itself ceases to exist. Although data encryption on a public Blockchain provides a layer of security, which may be sufficient in many use cases, in this study, we explore solutions that allow sensitive information to be deleted once the purpose of the ledger is achieved. The private Blockchain infrastructure utilizes BigchainDB, offering a privileged opportunity for control and privacy over the network. The strength of using BigchainDB is that its properties combine the advantages of Blockchain (e.g., decentralization, Byzantine fault tolerance, immutability, and owner-controlled assets) and typical distributed databases (e.g., low latency, indexing and querying of structured data, and high transaction rates) [173]. Furthermore, in this framework, information containers are stored off-chain to various BigchainDB databases (e.g., information models, documents, and sensor data) to provide confidential information access rights to stakeholders, which maintains data privacy and offers flexibility and scalability, accommodating diverse data formats and volumes. In contrast, based on the EPC evaluation period, only performance indicators essential for contract evaluation and automatic execution are stored on-chain. This selective on-chain storage optimizes Blockchain resources, enhancing transaction throughput and minimizing storage costs. Moreover, guaranteeing traceable storage and data sharing from the sensor to the DT within the Blockchain network ensures that all data transactions within the DT are reliable and trustworthy and guarantees critical updates necessary for prompt decision-making that can be selectively shared within the Blockchain network. In addition, this database can gather data throughout the entire lifecycle of an asset, and by leveraging the inherent benefits of a real Digital Twin, this approach harnesses bi-directional data exchange by establishing a link between algorithmic decisions stored on the Blockchain and their consequential effects on both the models and the corresponding physical asset in the physical realm.

Moreover, since Blockchains cannot connect to real-world data and events on their own, Decentralized Oracle Networks (DONs) will be used to combine on-chain code (smart contract) and off-chain infrastructure (BigchainDB) [189]. Blockchain oracles are “entities that connect Blockchains to external systems, thereby enabling smart contracts to execute based upon inputs and outputs from the real world” [190]. In other words, oracles serve as intermediaries between Blockchain systems and the external world [191]. Oracles serve as valuable tools for reducing the necessity of costly transactions on a Blockchain, such as storing and utilizing data within smart contracts [192]. Furthermore, oracles are foundational in providing environmental data sourced from sensor readings, satellite imagery, and sophisticated ML calculations to smart contracts. These contracts, in turn, enable the distribution of rewards to individuals involved in reforestation efforts or practicing sustainable consumption [190].

To this end, the private Blockchain infrastructure developed will facilitate the use of data on the smart contract published on the Consortium (public) Blockchain by sharing only the required information through semantic path access for energy performance compliance.

4.5. Virtual Data Room

A Virtual Data Room (VDR) is a user interface that facilitates access with permission to information for each stakeholder. It enables stakeholders to interact with performance data, visualize simulations, and initiate actions through the Digital Twin user interface. In addition to an EPC smart contract user interface to track and analyze all data transactions, it utilizes contract functions within a user-friendly environment. This interface enhances collaboration and streamlines communication among stakeholders, enabling them to effectively navigate and leverage the relevant information for their respective roles and responsibilities. The VDR optimizes the overall user experience, fostering efficient decision-making and promoting effective coordination among stakeholders throughout the contract period.

5. Conclusions

This research aimed to promote the use of EPCs in the AECO industry by utilizing advancements in digital technologies. This was achieved by conducting a systematic analysis of 113 published journal articles. The results showed limitations related to M&V and EPCs’ interplay with Digital Twin and Blockchain technologies in the building sector. M&V received minimal attention in studies, with only 8.5% dedicated to this aspect, and none of them addressed M&V in the residential sector. Advanced M&V, or M&V 2.0, was explored in only two research articles. Moreover, although EPCs are frequently mentioned, their relationship with M&V and contract terms remains unexplored. Only a single study investigated the potential of DT and Blockchain technologies for EPCs, but it underutilized the capabilities of DTs and suffered from high real-time transaction costs of data in the Blockchain network.

These research gaps highlight the necessity for further investigation into M&V, EPCs, and their integration with Digital Twin and Blockchain technologies to facilitate the implementation of EPC projects in the AECO industry. In response, the architecture of a framework that combines Digital Twin and Blockchain technologies to create an improved environment for executing EPCs was proposed. The proposed framework consists of three main layers: the Digital Twin of an asset, the Blockchain service layer (including a private Blockchain infrastructure and a Consortium Blockchain), and the Virtual Data Room. The framework shows the potential to enhance Measurement and Verification (M&V) in energy performance-based smart contracts in the AECO industry.

The proposed framework combines the Digital Twin layer with the Blockchain service layer, integrating static and dynamic building data to identify underperformance and facilitate informed decision-making. The Blockchain service layer includes a private Blockchain infrastructure and a Consortium Blockchain, addressing challenges related to data storage, transaction costs, and information confidentiality. The framework incorporates a private Blockchain infrastructure (BigchainDB) as an initial addition, aiming to eliminate the significant transaction costs associated with on-chain storage and address potential concerns about the confidentiality of information in open distributed ledgers. The Virtual Data Room provides stakeholders with a user-friendly interface to access their authorized information and interact with performance data. The framework aims to effectively manage energy applications in buildings, enabling real-time adjustments, flexibility, and autonomous decision-making for interventions and operations.

In future work, the authors recommend formulating a detailed framework for information flow between current framework layers and providing a proof-of-concept that delivers insights into the potential of using the proposed framework for a better EPC digitalized environment.