Crowd Energy Management: New Paradigm for Electricity Market

Mario Gstrein and Stephanie Teufel

Crowd Energy Management: New Paradigm for Electricity Market

Mario Gstrein and Stephanie Teufel

—The traditionally centralized approach of electricity networks is progressively undergoing a shift towards a decentralized, distributed structure. The local and crowd-based principle is transforming the existing supply chain and related activities into a value network (VN). Previous researches on crowd value network concepts focus on the activities of infrastructure and load management and neglect activities that generate collaboration. Collaboration with and within crowds particularly demands a different mindset and management of sharing values, information, benefit, and risks. Furthermore, these concepts must integrate technical, processual, and social aspects. Thus, this article proposes a holistic framework of electricity VN management for crowd energy. It redefines VN activities for infrastructure and load management while appending VN activities for social electricity handling. Additionally, the framework illustrates the interactions among these three elements and concludes with an adaption cycle for the crowd value network.

Index Terms—Crowd energy, decentralized distribution systems, value network, collaboration, electricity management.

1. Introduction

Decentralized or distributed energy systems reflect the current trend in the electricity industry transformation. These systems seek to replace conventional electricity components, e.g., nuclear plants, with smaller units that are closer to the consumer. This delocalization should provide a more efficient distribution[1], as production and consumption of electricity is local. Further benefits of distributed systems include flexibility and electrical load management in local areas[2], energy resources supply diversification, and exploitation of favorable sources of locations[3]. Single buildings can achieve independency from the network by self-supply of electricity[4],[5]. On the other hand, the conventional network would function as a backbone providing a supply of electricity in case of a shortage, maintaining the overall infrastructure, and operating relationships to neighboring networks. This hard swing to a decentralized and island structure creates several problems of increased complexity in automation, short circuit currents, and voltage regulations[3]. Overcoming these deficits, the current distributed scenario calls for attributes like the interconnected and meshed topology, distribution logic, full integration of decentralized storage and production, and multi-directional power and information flows[3],[6]. The potential features of such a decentralized smart grid include efficiency, accommodation, motivation, opportunism, resilience, and greenness[3],[7]. Concepts of smart energy distribution and management systems[6],[8]show this processual integration of decentralized structures in the existing centralized system based on technologies and information. This comprises the consideration of adaptive and dynamic behavior of the multiple production and consumption units and the agility of delivering context-aware services. These scenarios are based on traditional supply chain settings and assume a continuation of the current electricity management approach. Nevertheless, to provide a sustainable supply chain management (SCM) approach, the following points may be considered.

The conventional SCM activities are aligned with a“one-to-many” paradigm; the distribution process is top-down from a supplier to a consumer. Thus, the decentralization is a processual and physical integration of production and storage units. Decentralization, however, also entails structural and organizational alterations pursuing virtual constructs of communities. Reference [9] refers to it as the phenomenon of crowd energy, which is the collective effort of individuals and organizations, profit or non-profit, pooling their resources to build a sustainable supply chain. This concept generates values through a complex and dynamic exchange process among electricity suppliers, service providers, consumers, prosumers, strategic partners, and communities, and creates a sustainable and interactive value network (VN). These networks transact more around goods like electricity and revenue, and networks profit by further intangible currencies[10]. Within this“many-to-many” construct, social structures are centered around production and consumption[11]and introduce a different perspective on electricity sharing. VN management may exhibit the ability to manage collaboration within and among communities while dealing with value perception and enrichment proposed by the communities. Communitycompulsion is also to pursue a sustainable VN, elaborating on the environmental improvement intentions[12]—the“green” concept—to encompass economic and social dimensions[13]. To operationalize the sustainability and benefit from sustainable capitalism, any member may show a minimum performance in all three areas to obtain access the VN[14]. Consequently, a coordination of all supply chain activities and tactics is carried out in a systematic and strategic way to achieve long-term performance for all members following the “with you” rather than the “to you”paradigm[9]. Therefore, a VN becomes “an integrative philosophy to manage the total flow” (cooper) and requires an examination of the VN activities integrated process, collaboration, shared goal, and mutuality in information, risk, and benefit sharing[15],[16].

This paper therefore proposes a holistic framework of electricity value network management for crowd energy[9]that unites aspects of infrastructure, load management, social management, and policy. First, the paper elaborates the important factors of a crowd energy framework by discussing the concept of a distributed energy value network and the relevant activities. In the second section, a short outline of the framework describes the basic mechanics followed by detailed specifications of the essential management principles in each area. An adaption cycle demonstrates the dynamical alteration steps in the value network and completes the framework. The following chapter describes an abstract of a crowd energy model and ends with a conclusion.

2. Value Network Activities

2.1 New Value Network

Understanding the effects of the supply chain reconfiguration is needed to shed light on the changes in traded objects and required business models. The future electricity industry generates value through a complex dynamic value network among several partners—electricity suppliers, service providers, consumers, prosumers, strategic partners, and communities (see Fig. 1). One feature of the value network is that electricity is traded beyond the traditional paths while additional players utilize load management and infrastructure activities. Another outcome in this constellation is that new relationships will become important and intensified as others are minimized to the size needed to support the VN. Within these networks, transactions transcend the currency of goods, services, and revenues and include knowledge and intangible benefits such as loyalty or commitment[10]. These objects serve as a medium for exchange or as currencies that are accepted in transactions[10]. The dynamics of exchange depend on the performance of activities. The performance is a corporate responsibility in an electricity network and refers to proper systematic and strategic management of the new activities. The new electricity management activities deal with the processual, technical, and social integration of the demand side, which entails a novel distribution perspective as electricity availability comes from the traditional top-down as well as decentralized locations. Furthermore, it handles relationships that create value with and for consumer, prosumer, and the virtual construct of a crowd. The concept of a crowd is especially troubling for the electricity industry. Moreover, difficulties exist in electricity management among service provider, consumer, prosumer, and crowd. Not only would a competitive advantage for service providers be available, but mastering these specific VN activities would also support the energy turnaround.

Fig. 1. Value network of crowd energy.

A challenge within this environment is the determination of the value of electricity to satisfy all stakeholders. The collaboration within and among communities has an invasive character on the value due to the scale delay to non-money-based reciprocity exchange objects. These social activities are not currently considered in electricity management. Furthermore, values are created by additional services, and profit is realized by considering a different set of values. This offers new windows of opportunities for information and communication companies as well as for appliances manufacturers. Therefore, a consolidation of all technical, social, and regulative activities under a holistic and generic framework requires an understanding of the modified VN activities.

2.2 Integrated Process

To achieve a sophisticated crowd energy system, integration of demand side management[17]and distributed energy resources[7]is crucial. Today, it represents the technical consolidation of end-consumers but fails to account for the effects on technology and infrastructure activities. In addition, the integrated process influences collaboration and its corresponding electricity management, yet these are hardly discussed.

In recent decades, the steady technological development of small generation units[18], especially the photovoltaic and storage, has localized the production-consumption paradigm. A movement towards individual or micro grids is underway[19]along with the evolution of the consumer into a prosumer[9]. With an advanced and decentralized network and integration among demand-side members, a system of intelligent generation-storage-load cells (iGSL) comprisingthe basic elements of the crowd energy concept can be achieved[9]. Crowd-based structures allow decoupling from the residual electricity network and can form autocracy plans[5]. In this way, integration may go beyond competition in the market of the core product—electricity, and include infrastructure management and/or load management. For example, the locality of production and consumption minimizes transmission losses due to the intrinsic property of electrical resistivity and conductivity[20]. Furthermore, decentralized crowd structures can be sensitive to short-term and extensive dynamic perturbations while decreasing the likelihood of failure of the transmission line[21]. The implication is that a high dispersion of production units requires control rather than anticipation[21]. The optimization potential of decentralized crowd units, e.g., load balancing, may lead to advanced control systems and new business opportunities. This implies that distributed energy resources expect enhanced functionalities for distributed intelligence, visualization, forecasting and predictions, interoperability, and information security[7],[22]. Demand-side integration also entails an integration of new players. New capabilities to fulfil demands are necessary, and they create a window of opportunity. Novel regimes in the socio-technological system[23]intercept the provider-consumer link and force providers to compete on uncertain terrain like data management. Integration efforts are also diversified as the diffusion of decentralization depends on political, economic, social, and technological parameters[5],[18],[24], resulting in a mixed electricity network of centralized and decentralized structures—a consequence of not every customer becoming a prosumer. In other words, the industry may perform traditional load management tasks including new possibilities of distributed balancing while managing loads among crowd networks on a micro-grid level. The eventual challenge will be to manage a range of partially owned technologies and infrastructure components in order to permit and foster collaboration within the value network.

2.3 From Cooperation to Collaboration

Crowd energy infrastructure supports interactions among members and emphasizes the shift from a cooperation- to a collaboration-based philosophy. Cooperative behavior among several production-distribution players[25]already exists and should increase strategic performance[26]through the creation of higher value and profit. It is an essential activity in the value network to provide superior outcome. Cooperation is understood as“two individuals or organizations [reaching] some mutual agreement, but their work together [not progressing] beyond this level”[27]. This reflects a standard business practice of regarding the customer as the end of the value network. Successful VN, however, lies in the collaboration within crowds’ shifting standard business practices[28]. Collaboration is the joint approach to managing, planning, execution, and control of activities by sharing information and risks[16]. The formation of an interlinked network is likewise a voluntary agreement of sharing human, financial, or technical resources[16]to accomplish sustainability along the value network. Each member contributes a certain value to succeed, and VN management integrates the value creation from the demand side.

The novelty of collaboration in the crowd energy concept is in the perception of sharing, which refers to “the act and process of distributing what is ours to others for their use and/or the act or process of receiving or taking something from others for our use”[27]. The collaborative consumption trend follows different economic arrangements where individual ownership is outweighed by collaborative performance and includes activities such as bartering, lending, trading, renting, and gifting[29]. Today, the socio-economic movement of collaboration consumption spills over into more ecology- and sustainability-orientated areas where consumer and prosumer simultaneously decrease wasteful performance.[30]The objectives are achieved by complementary and coordinated activities within a community interacting in a manner that is “… local and face-to-face or internet-connected [groups creating] a peer-to-peer network”[29]. In this way, the perimeter of a community depends on geographical and/or relational dimensions[31]. A spatial boundary often constitutes technological or infrastructural conditions, e.g., the power wiring of a street or village, and any changes in the community are directly linked with changes in the structure. Conversely, the relational dimension develops around common purpose/interest, mutual responsibility, and acceptance of individualism and dependency among members to achieve benefits for oneself as well as for the group[32]. In a distributed regional system, the industry and demand side will be part of the electricity community sharing the same relational factors and awareness will be required in this communities[18]. Any misbehavior leads to penalization (Morgan). Additionally, the mediators of commitment and trust are decisive for collaboration and minimize conflicts or uncertainty[33],[34]. A successful VN relies on both factors and involves the management of social exchange and transactional variables[33],[35]. Elaborated approaches may form positive attitudes towards a collaborative consumption and/or participation in this network to 1) work in preserving relationships through collaboration, 2) reduce risk-seeking behavior, and 3) seek long-term rather than short-term benefits[33],[36]. The challenge for VN management in the context of crowd energy is to create an environment where all members are part of the operation[37]by considering shared goals and mutuality in electricity management.

2.4 Shared Goal and Focus

Successful collaboration assumes shared goals among members of the VN to establish sound formal and informal relationships[38]. The advantage is the ability to solve issues quickly[38]. On the other hand, the decentralized and community-related electricity management extends the perceptions of value propositions and value creation, which, in turn, regulate the crowd energy’s objectives.

To satisfy consumers’ requirements, electricity providers initially integrate a consumer’s value by aligning all activities and required sources to produce it[39]. Still, the value chain view is designed strictly so that every company occupies a position in the chain[40]; providers deliver electricity downstream to the distributor and ultimately to the customer. However, misconceptions of value proposition and creation lead to undesirable outcomes, illustrating that electricity provider acknowledge serious problems. An example of measures in this effort is the initiative to capture values from abstract values like efficiency or optimization[37]. From a company’s perspective, it is logical to approach efficiency in such a way that a higher efficiency ratio positively effects the cost and revenue. This is actively executed on the value chain. By contrast, consumers perceive an improvement of efficiency in a price reduction, which is an indirect benefit at the end of the chain. For consumers, electricity is an enabler to fulfil tasks rather a product, hence no value is directly associated with it. Thus, collaborations should not be tailored exclusively to customer benefits[37].

The understanding of values and their effects on all stakeholders is decisive, as electricity includes additional benefits for individuals, such as comfort and flexibility, as well as for the society through sustainability commitments, for instance[14]. The telecommunication industry has experienced similar dematerialization of traditional products[41],[42]. Sustainability is one factor among many that may be considered in the translation of business models. A sophisticated electricity management must employ general value mapping[43]and normative value management[44]to foster trust and commitment[33]. Furthermore, collaboration requires the management of values on the firm and system levels[45]. Informed by continuous creation of business cases[46], VN management should be capable of understanding players and inherent dynamics—their regime settings[47]—beyond values, e.g., the rapid innovation cycle and procedure of the ICT sector. Finally, though the shared goals and values in a crowd system are a precondition, the fuel to drive collaboration derives from the mutuality of sharing information, benefits, and risks.

2.5 Mutuality

Sustainable collaboration demands strong commitments and trust from all members with a long-term perspective[48]. Such collaborative behavior calls for a relation of mutual dependencies, actions, or influences[15]. An integrated philosophy employs this mutuality to optimize internal operations with partners as well as the demand side. Two types of mutuality in a VN[15],[16]should be established: the mutuality in sharing information to coordinate among members and the mutuality of sharing risks and rewards to remain in the network.

By sharing information, members exhibit willingness to exchange information to improve coordination and reduce uncertainty among players[49]. The information typically encompasses inventory levels, forecasts, sales promotion strategies, and marketing strategies[49]. The electricity management for a crowd, on the other hand, involves decision-making about electricity distribution among and within communities. Data beyond business information for decision-making are necessary and include strategic and operational data such as those for load management, pricing, performance measurement, and administration. The accessibility and availability of data play a crucial role in regulating the degree of members and processes integration. For example, through a decentralized load management, crowds can exclude the leverage of electricity providers. On the other side, the collection of private information provides a competitive advantage for providers. Furthermore, sharing is dramatically changed as information technology fosters the integration of processes and players[49]. Various information systems now support sharing, bringing tech-driven dynamics into play[36]. Together with automation efforts, the frequency of information updates[50]creates enormous amounts of data and has implications for information management. This requires new capabilities and gives a window of opportunity for entrants. The result is a destruction of existing core competencies through new entrants and their abilities to utilize different technologies.

On the other hand, remaining in a crowd value network requires sharing risks and benefits. Any sharing demands equality of the substituted object immediately or in the near future[33]. In a traditional electricity network, the concept is described as the principle of a long-term risk management by securing rewards for investments. However, the crowd energy alters the risk and benefit perspectives in several ways. First, the period under observation is shortened to a decade or less. This is also triggered by the shorter IT lifecycle. Second, a decoupling of risk covered by rewards occurs through the influx of various values from the different stakeholders. This means that covering risks is distributed among the various crowds rather in the investment of enormous sums in a centralized object. Third, risks are prioritized. Communities prioritize the risks of a crowd over the risks related to the entire network. These are still the responsibility of electricity providers. Fourth, the rewards differ from those of the provider and the crowd agenda. Providers use centrally driven mechanisms aligning information and incentives to convince decentralized decision-makers to act in the best interests of the entire system[51]. On the other side, sharing the necessary information for stabilizing the grid is accepted by the crowd but, beyond that, rewards must have a meaning. Finally, the meaning of received benefits varies from rational economic factors to social exchange factors[52]as emotional, fairness-concerned, and social behavior are evoked by the shared approach. Consequently, rewards consist of quantitative and qualitative media as well as their non-negotiable natures[52]. Furthermore, realized exchanges precede a discussion of the social dilemma[53]and the argumentation for self-interest or for social provision. Future electricity management rewards for exchange are a delicate subject to broach, but punishments will improve the collaboration by eliminating selfish behavior or preventing excessive economic exploitation[36],[54].

Eventually, crowd energy management and electricity management through VN activities will foster collaborationby increasing trust and commitment by way of shared goals, risks, and benefits among all members.

3. Crowd Energy Management

The crowd energy management framework addresses the request of a consistent electricity management approach for a sustainable and collaborative VN (see Fig. 2). It regards and links socio-technological aspects of actors, technical systems, and policies and regulations as well as the larger interplay among those elements[23]. In general, the framework is a fusion of the decentralized crowd and the traditional centralized structures. The primary goal is to produce and deliver according the TAL principle, i.e., at the right time, the right amount, to the right location.

Fig. 2. Overview of the crowd energy framework.

To achieve the TAL principle, a synchronization of all four areas is necessary: the technology and infrastructure areas, load management layers for electricity distribution (traditional and crowd), socially focused layers (social electricity management and administration), and finally, the policy and regulation (P&R) area, which interacts with all other layers.

3.1 Crowd Energy Framework

The framework builds on the technology and infrastructure of the existing electricity grid. Both elements encompass all needed hardware and software components for producing, delivering, and consuming electricity. It is the foundation of changing the paradigm from “production follows demand” to the “TAL” principle. The infrastructure layer is distinct from the technology layer in the assembling and interplay of all technologies fulfilling goal-directed actions. Technologies, conversely, are independent single units that can be implemented in other systems. Therefore, the design of the electricity management is strongly related to available and accessibility of technology and the method of integration. At that point, the ownership of technology and infrastructure areas becomes blurred as the system replies to crowd and traditional requirements. Therefore, the crowd structure is not wholly detached from the top-down structure.

This is carried further in the load management area, where the infrastructure distributes electricity on a traditional network and on a crowd level. Activities involve a mixture of traditional load management tasks of the providers, guaranteeing network stability and reliability as well as providing service to distribute electricity within and among the crowd community. To respond to the community needs, the framework extends the basic crowd load management tasks by social electricity management (SEM) and administration (SEA) aspects. The primary goals of the SEM are the social handling of electricity and the understanding of the demand-side behavior. It represents the interface between the technical system—the physical distribution—and the social aspects of the demand. To respond to this new challenge, crowd-based structure requires implemented procedures for managing large data sets and for executing appropriate analysis. The SEA layer summarizes such comprehensive systems and includes organizational structures, methods, skills, and capabilities. Finally, the policy and regulation (P&R) area should govern a win-win-win situation for business, customers, and society[55]. Reference [14] recommended that P&R should intervene in destructive behavior of locusts or caterpillars and support regenerative behavior of honeybees and butterflies. By leaving regulation solely to the government, the crowd electricity management would miss opportunities to drive business. For example, industry standards in smart metering allow for generating a complementary environment and for fostering the integration of technologies to create superior services. Additionally, ethical guidelines could build trust and commitment of the demand side, and certifications of sustainable service would actively help to determine the value of electricity. Whatever the scale of P&R is, each layer should be supported by it.

Within the framework, each area has a specific purpose and tasks for the system including visions, strategies, resources, and participants. Thus, each field constitutes a separate system endeavoring inherent stability, flexibility, and functionality settings. By integrating all fields, the framework complements different views on an approaching task and reaches its full potential of sustainable and beneficial outputs. The intersections lead to interactions and provide boundaries and limitations. The interdependency also forces fields to shape one another mutually without violating inherent settings or the overall goals of a smart grid. For example, to provide community-based exchange of electricity adequate technologies like databases and analysis, certain tools are required along with the ability to organize such jobs in the SEM and SEA. The success of dealing with the crowd framework to generate benefit depends on the handling of changes from each area as well as on the framework’s implementation. At this point, any additional area is a vertical extension of functionalities that are available in the crowd electricity management. This represents different types of functionalities, including different skills and capabilities, and hence the breadth of manageable activities. Horizontal extensions, on the other hand, are the characteristics of a function within a layer and define different options. This corresponds to the scope of functionalities and the depth of manageable activities.

3.2 Technology

The technology area refers to all techniques applied to create a TAL situation. An immense portfolio exists and raises challenges for technology management. In a crowd energy environment, different categories of technology directly or indirectly influence the electricity allocation. The first category defines core technology, which is responsible for production, consumption, and storage of electricity. This also includes basic distribution facilities. On the top of that, technology in a narrow sense refers to electricity processing. Those technologies for electricity management are mostly associated with IT and involve, for instance, smart metering or panels for control devices in a smart home. The last category defines technology for electricity management in a wider sense. This refers to technologies used to change social behavior, e.g., internet platforms for consumption behavior and achievements. Moreover, it contains other energy systems influencing the electricity consumption, e.g., cooling systems where saving electricity is achieved by creating an ice puffer in the night for cooling during the day.

It is needless to say that the technology portfolio is too immense to be managed by a single player and hence players may adapt a technology surveillance behavior. This serves to align resources to the objectives, to find innovation gaps and to keep an eye on niche technology developments that may have an impact on the system[56]. Additionally, technology is the entry point to the demand side, i.e., it provides a strategic position to access the consumer, control the load, and receive data for further processing. Therefore, one dimension of the technology management matrix is the required management attention. The high or low attention derives from the current trends, technological risks, and the player’s objectives. On the second dimension of the matrix, players may consider the distance between current and demanded skills and capabilities to utilize technology for the competitive advantage. A scale of owned, partially owned, or not owned provides insight into smaller and larger adaptation distances. The interceptions of both dimensions allow for creating strategies to implement technologies and develop skills and capabilities or to create partnerships to assimilate further competencies.

3.3 Infrastructure

The extension of the functionalities in electricity VN requires the consolidation of various technologies in a comprehensive infrastructure. The goal is the depiction of decentralized and virtual crowd communities within the centralized infrastructure. Similar configurations are already achieved on the production side through virtual power plants, however, the virtualization of the demand side for crowd energy has implications of potential disparity in ownership rights and management essentials of community-related infrastructure components. For example, individual decision-making behavior can interfere with the need for usage to balance the load by the right to use one’s own resources. These issues may be perceived as a subject of discrimination when an individual decision is overruled. In this way, the line between ownership and management becomes blurred. The infrastructure’s purpose is to model processes beyond the traditional load management, and delicate matters of social behavior should be reflected in the ruling and automation of distribution processes. The increasing machine-to-machine automation for representing crowds enhances the speed and volume of decision-making. These M2M communications are subject to constant alteration through multiple players and through the access of various technologies. A competitive advantage is achieved by the implementation of algorithms that promotes transparency, flexibility, and adaptability.

Nevertheless, the infrastructure management for sophisticated products and services may apply a categorization of technologies according to two dimensions. The first dimension is a separation of technologies based on their purposes. To that end, technology can be classified by core or wider functionalities. Core functionalities refer to functionalities for basic load management and mostly for automation purposes. Wider functionalities are indirect functionalities for load management that serve community or individual interests. The second dimension considers the impact of the purpose on the infrastructure. The impact can be measured either in the importance of goal attainment or in the risk assessment of the integrated functionality. A high impact represents basic transition of the infrastructure and the possibilities of new development directions, whereas low impact refers to incremental changes and can be seen as the refinement of the network. The intersection of the two dimensions enables categorization of technologies and functionalities in the areas of immediate attention, periodic attention, or annual review. Subsequently different rules, guidelines, or policies for implementation can be applied, for example calling for active evaluation and monitoring.

3.4 Traditional Load Management

The traditional load management within a decentralized crowd structure focuses on entire network stability and requires the integration of communities. In general, the major task is the processual integration of the numerous intelligent generation-storage-load cells into the existing power network and dealing with frequency and voltage issues. Those issues are handled with an adaptive and dynamic demand management. Currently, this management is summarized in a demand response (DR) approach, which influences consumption patterns through price alterations. A predefined policy of load priority and considered environmental situations adjusts the load and increases the stability of the network. Such location-based and context-aware services[6]present the one-to-many control mechanism of DR programs[57], assuming that collaboration is based on the exchange of the intangible stability with tangible money values. With a crowd energy structure, traditional load management can have the advantage of layering crowds virtually. The mode and organization of conflicts in the frequency and voltage are handled on a local and regional rather than on an individual level. Measurements are holistic but can also affect specific crowds in the network. A subdivision of the low voltage grid may occur. Additionally, the mindsets of crowds in networks inform collaboration and the mutuality of sharing values forthe same benefit and risk. Stability is no longer individual to the anonymous grid; instead, it becomes a many-to-many or community-to-community approach. Eventually, primary goals of the network outweigh the individual or community based ones.

3.5 Crowd Load Management

In contrast, the crowd load management is concerned with the processual load distribution in micro-grids. It represents the first step in the alignment of electricity infrastructure, distribution, and social behavior. The generators, storage and loads (iGSL) cells are interconnected and able to operate independently from the electrical grid. These local-based systems generate stability from the bottom by assessing potential production capacity, prospected consumption, and the residual storage capacity. By following the TAL principle, electricity is distributed from cells with a surplus to cells with a shortage. Any available surplus is charged in the storage for later references. Whereas the traditional load management looks at statistically standard load profiles, the crowd load management focuses on the refined user patterns related electricity management[6]. In so doing, information related to electricity distribution for basic iGSL devices and for context-aware situations becomes necessary. Thus, decision-making for distribution implies an enrichment of information creating a multi-layered model of data. The refinement of information supports the DR approach and customizes collaboration aspects beyond money-for-stability exchange. Along with it, the division of the demand side into smaller manageable constructs affirms customized electricity and accompanied services offerings. Furthermore, crowd DR creates a more familiar environment where the one-to-many directive can be less intimidating as immediate effects may be anticipated, e.g., through punishments of opportunistic behavior. Although the traditional load management and crowd load management focus on different levels, both strongly depend on each other for a stable network and the line between network- and crowd-based decisions might be blurred. This is also valid for the offered functionalities and requested information.

3.6 Social Electricity Administration (SEA)

The social electricity domain defines the collection of capabilities and skills to handle social aspects in the value network. It illustrates the core of the crowd framework and constitutes the connection between the technical solutions and the demand side. The major goals of the social electricity domain are a) to streamline the crowd load management process and b) to provide possibilities for additional services that surround electricity. It is to be noted that an understanding of consumer, prosumer, or crowd is postulated.

The first area, social electricity administration (SEA), comprises all disciplines for the sophisticated information management. SEA requires a technical, implemented distribution system operator (DSO) allowing for the monitoring and control of electricity flow. Apart from DSO functions, SEAs address major duties of the information design, especially for information creation, processing, analyzing, and yielding the desired results. For example, this includes, among others, a definition of required information types, a map of measure points, collection rhythm, and granularity of information. Furthermore, there is an emphasis on the information processing within this crowd energy system, which includes the data preparation, enrichment, and guaranteed availability through sharing. Along with this, new capabilities and skills for analysis may be learned to furnish new perspectives on service offerings and on the organization of crowds. Such points are crucial for the value network to drive business innovation or to optimize crowd load management, but it reconsiders capabilities in further areas such as IT security and risk management.

Overall, SEA deals with the breadth and depth of the information pool and allocates information to the diverse functionalities of the crowd energy system. By doing so, the layered model of functionality-information builds the bridge of crowd load management and the intrinsic/extrinsic motivations[58]of the demand side.

3.7 Social Electricity Management (SEM)

SEM is the second part of the social electricity domain and provides insight into the social aspect of the crowd system. In this way, it furnishes definitions for the SEA activities and the following load management tasks. The SEM is the entry point for demand side communications, so it is the starting point for service definition, whereas the crowd load management executes the delivery. The objective of SEM is to foster collaboration and to address community and individual aspects by defining mutuality in sharing information, benefits, risks, and goals. Successful SEM involves interaction among these.

The foundation is the management of all generated values in the crowd energy system. Thereby, values from the system, e.g., normative values, and values from stakeholders should be considered in the translation to business outcomes. Such a value mapping outlines the scope of existing values and is the common basis for sharing goals (see Fig. 3). It reveals the pains and gains of partners, communities, prosumers, and consumers. Furthermore, the mapping allows for finding new values, which should be transformed to capture values through best practices. Conversely, it also shows poor performing values that lack processual outcomes (missed) or insufficient technological realization (hibernated). In light of this information, members can take actions to address incomplete, yet promising values.

A further aim of the value mapping is the deduction of shared benefits and risks in collaboration. This provides insight beyond goals of efficiency and sustainability as well as beyond the exchange based on money. Members of the network develop a mutual understanding decreasing uncertainty, which, in turn, increases the willingness of sharing information. Greater information sharing contributes to improved trust and commitment in the communities[33],[35]. Community building and management are essential to crowd energy management, as they allow for a) accessing the demand side and b) managing decision-making byshowing the negative outcomes of opportunistic decisions. The community management also involves establishing rules for punishment[54]. Finally, the SEM provides the possibility of crowd categorization and hence profiling beyond the infrastructural and load management dimensions.

Fig. 3. Value management in a SEM.

3.8 Adaption Cycle of the Crowd Energy System

The crowd energy system streamlines the value network functions of all members to generate a sustainable electricity network (see Fig. 4). By integrating the demand side, the electricity network extends management responsibilities of production and storage infrastructure, load management, and information system. By doing so, the sharing facet becomes important and can divert from the existing understanding. The agreement on shared values, benefits, and risks concentrates on material as well as on social definitions. In this way, it is necessary to address the wider scope for supporting trust and commitment, which foster collaboration. Furthermore, the translation of sharing into sophisticated products and services bears competitive advantages.

Fig. 4. Crowd energy functions and flows.

Such a crowd-focused business should be established beyond simple customer orientation, as it influences value network functions like sales, marketing, or financing. This can result in sustainable business models such as cooperative ownership or inclusive sourcing. Additionally, innovative business models rely on the novel value network flows of information, knowledge, and insights. Availability and accessibility of such flows is decisive in innovation, but is more important in detecting adaptations in the value network triggered by social or by technological impulses. The momentum affects all value network functions and inherent flows.

A dynamic interwovenness is a key characteristic and follows a specific adaption cycle by which members may acquire necessary skills. Crowd value network adaptations commonly follow the stages of invasion, inclusion, integration, and incubation, though these steps may have varying different durations (see Fig. 5, adapted from [14]). The invasion step refers to the natural process of occupying opportunity space by new technological or changed social behaviors. These impulses can provoke different adaptation types, e.g., regular, disruptive, specific shock, or avalanches[47]. The invasion process causes new economic and environmental impacts.

Fig. 5. Adaption cycle of a crowd energy network.

In the subsequent inclusion step, internal and external stakeholders process the occurring effects. It is important to know and define the management priorities for the projected crowd energy system. Depending on the impacts, discussions constitute a single member or a group of members. In the integration phase, the new priorities are consolidated with the existing ones to improve the crowd system and better achieve sustainability. In particular, each crowd energy framework domain adjusts to the new principles and creates or releases interaction links. The last step refers to learning from the changes and acting under the new system priorities. New windows of opportunities evolve, providing space to investigate or even to develop novel priorities for the crowd energy network, e.g., by developing niche markets. Consequential technology or social impulses are the sources for invasion and the start of the next cycle. Eventually, the iterative evolution of a crowd energy system depends on the overall targets of the electricity grid and changes of targets drive it in different directions.

4. Basic Crowd Model

The comprehensive crowd energy concept is a complex adaptive system with many elements and interactions. To understand this dynamic and interactive system in the context of electricity management, a crowd model is required to glean preliminary insights.

The model is a bottom-up orientation based on a cellular structure (see Fig. 6). The structure is multi-layered and consists of iGSL cells, crowd, and the low voltage network. The iGSL cells are the first-line level representing a building on the low voltage layer. The model’s minimum unit is a building and aggregates all inherent structures (e.g., flats). A unit can possess three functionalities: consumption, production, and storage, providing seven possible combinations in which a cell can perform or offer performances to the grid. This implies that each cell has either a specific status of electricity availability (currently and already produced) or a status of electricity demand. Subsequently, it can be classified according to three conditions: positive, negative, and neutral (neutral status is production equals consumption). Such performance-related status consists of many factors that are general in nature, like photovoltaic potential, appliances or individual and changeable considerations like living situation and social behavior. However, the current status depends on the sequence of past conditions, so it is an associated series comprising the formal sum of all negative and positive conditions. Over a period of time, a line diagram of the status can be plotted as an expression of the individual independency from or dependency on the grid. In other words, a cell obtains surplus periods achieving independency from—and shortage periods achieving dependency on—the grid. Furthermore, surplus periods do not depend on common production patterns like photovoltaics do such as on the availability of storage. Thus, storage is very influential on the cell’s behavior, as it temporarily transfers surpluses into shortage periods and works like a bank account. In optimal cases, it covers negative deflections of a cell until production comes up again. So, the storage allows for additional consumption during surplus conditions (charging) and replaces production units when discharging. With this cell dynamic, electricity is available from the production and storage, contributing to the formation of a crowd structure.

Fig. 6. Crowd model.

The next virtual layer of the model, that of the crowd, is an achievement of communities balancing the load through transferring electricity from positive to negative cells. A community-based independency or dependency is contingent on such balance (see Fig. 6). The formation of crowds is based on cellular automata rules and requires the integration of factors of mutuality, cooperation, and prospected values in the crowd energy modelling. This demands an integrative mindset combining different aspects to form a consistent structure. For example, the described technological functionality of storage depends on the willingness to share, which can be understood as risk-averse or risk-seeking behavior of individuals[59]. This means that any sharing with other cells is time-dependent and likely to occur if the current storage level is sufficiently high to exchange electricity. In other words, prosumers do not jeopardize a shortage of electricity supply in the near future[59]. Eventually, such considerations allow for verification of such measures as the threshold of cell numbers. This short outline, however, only provides a glance of the wide spectrum crowd model factors. The ultimate goal is to propel the discussion on the sustainable crowd energy approach.

5. Conclusions

The concept of crowd energy refers to a novel electricity distribution paradigm through a more decentralized structure. Thereby, communities of prosumers and consumers work together to create bottom-up potential for the energy turnaround. Such modifications affect the existing value network and the associated activities for electricity management. An appropriate value network management anticipates the handling of infrastructure and load management, but in order to respond to the emerging crowd structure, social aspects should be reflected in related activities. Thus, the discussed crowd energy framework proposes domains of social electricity management and administration. In so doing, crowds contribute to the stability of the network through elaborated insights into the collaborative behavior surrounding the electricity distribution. In order to integrate social aspects, the crowd energy framework establishes connections to technological and processual domains. It also concludes that future electricity management requires new skills and capabilities for value management and community handling in order to access the value network. Finally, electricity management should proceed cautiously as it is crucial for the development trajectory and quality of crowd energy.

Acknowledgment

We would like to thank Dr. Bernd Teufel for providing insight and expertise that greatly assisted the paper.

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Mario Gstreinstudied business administration and informatics at the Berufsakademie Lörrach (GER) and received the B.Sc. degree in 2001. He received the M.Sc. degree in innovation and technology management at the Science and Policy Research Unit (SPRU), University of Sussex (UK). He is currently pursuing the Ph.D. degree with the International Institute of Management in Technology (iimt), University of Fribourg, Switzerland. His research interests include energy systems, electricity management, innovation management, value network, and simulation of complex systems.

Stephanie Teufelstudied informatics at the Technical University of Berlin and the Swiss Federal Institute of Technology Zurich (ETH Zurich). She received her Doctor’s degree from the University of Zurich in 1991. She was a lecturer at the University of Wollongong, Australia, and a university professor in information systems at the Carl von Ossietzky Universität Oldenburg, Germany. Since 2000 she holds a full professorship in management in information and communication technology at the Faculty of Economics and Social Sciences, University of Fribourg, Switzerland. Furthermore, she is the Director of the International Institute of Management in Technology (iimt). Currently, she is the Dean of the Faculty of Economics and Social Sciences, University of Fribourg, Switzerland. Her research interests include management of information security, energy systems management, project management, innovation, and technology management.

Manuscript received May 9, 2015; revised July 15, 2015.

M. Gstrein is with the International Institute of Management in Technology, University of Fribourg, Fribourg 1700, Switzerland (e-mail: mario.gstrein@unifr.ch).

S. Teufel is with the International Institute of Management in Technology, University of Fribourg, Fribourg 1700, Switzerland. (Corresponding author e-mail: stephanie.teufel@unifr.ch).

Digital Object Identifier: 10.11989/JEST.1674-862X.505091