Jun 1, 2017·2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Eleonora Riva Sanseverino, Maria Luisa Di Silvestre, Pierluigi Gallo, Gaetano Zizzo · 5 authors
In recent years novel models for energy distribution appeared and islanded microgrids quest for new ways to exchange energy between consumers and producers without the need of central authorities. The blockchain mechanism has emerged as a distributed solution for recording energy transactions in power systems. The blockchain has been used to permit users bartering and selling energy and to keep track of such exchanges without exposing them to tampering. In this work, we consider a novel application of the blockchain in islanded microgrids that includes also annotating energy losses caused by energy transactions, in order to have a more realistic matching between the physical status of the energy grid and the consequent costs attributed to users. To validate our novel use of the blockchain, we carried out simulated experiments for an exemplary islanded microgrid, in which 3 main generators supply 6 load nodes. This validates the compatibility of this new cost attribution model with the supporting physical infrastructure. Preliminary results demonstrate that the superposition of energy transactions in a microgrid changes the distribution of losses in all paths, eventually due to the large reactive flows created by PV systems.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy Resources (DERs). The strategy that maximizes the revenue for each individual DER is the one in which the DER operates at capacity, injecting all available power into the grid. However, when the DER penetration is high and the consumption low, this strategy may lead to power surplus that causes voltage increase over recommended limits. In order to create incentives for the DER to operate below capacity, we propose a proportional-fairness control strategy in which (i) a subset of DERs decrease their own power output, sacrificing the individual revenue, and (ii) the DERs in the subset are dynamically selected based on the record of their control history. The trustworthy implementation of the scheme is carried out through a custom-designed blockchain mechanism that maintains a distributed database trusted by all DERs. In particular, the blockchain is used to stipulate and store a smart contract that enforces proportional fairness. The simulation results verify the potential of the proposed framework.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy\nResources (DERs). The strategy that maximizes the revenue for each individual\nDER is the one in which the DER operates at capacity, injecting all available\npower into the grid. However, when the DER penetration is high and the\nconsumption low, this strategy may lead to power surplus that causes voltage\nincrease over recommended limits. In order to create incentives for the DER to\noperate below capacity, we propose a proportional-fairness control strategy in\nwhich (i) a subset of DERs decrease their own power output, sacrificing the\nindividual revenue, and (ii) the DERs in the subset are dynamically selected\nbased on the record of their control history. The trustworthy implementation of\nthe scheme is carried out through a custom-designed blockchain mechanism that\nmaintains a distributed database trusted by all DERs. In particular, the\nblockchain is used to stipulate and store a smart contract that enforces\nproportional fairness. The simulation results verify the potential of the\nproposed framework.\n
A coordinated trading process is proposed as a design for an electricity market with significant uncertainty, perhaps from renewables. In this process, groups of agents propose to the system operator (SO) a contingent buy and sell trade that is balanced, i.e. the sum of demand bids and the sum of supply bids are equal. The SO accepts the proposed trade if no network constraint is violated or curtails it until no violation occurs. Each proposed trade is accepted or curtailed as it is presented. The SO also provides guidance to help future proposed trades meet network constraints. The SO does not set prices, and there is no requirement that different trades occur simultaneously or clear at uniform prices. Indeed, there is no price-setting mechanism. However, if participants exploit opportunities for gain, the trading process will lead to an efficient allocation of energy and to the discovery of locational marginal prices (LMPs). The great flexibility in the proposed trading process and the low communication and control burden on the SO may make the process suitable for coordinating producers and consumers in the distribution system.
Vasiljevska Julija, Jochem Douw, Anna Mengolini, Igor Nikolić
EU Regulation / /EC concerning common rules for internal market in electricity calls upon % of EU electricity consumers to be equipped with smart metering systems by , provided that a positive economic assessment of all long-term costs and benefits to the market and the individual consumer is guaranteed. Understanding the impact that smart metering systems may have on the electricity stakeholders (consumers, distribution system operators, energy suppliers and the society at large) is important for faster and e ective deployment of such systems and of the innovative services they o er. For this purpose, in this paper an agentbased model is developed, where the electricity consumer behaviour due to di erent smart metering policies is simulated. Consumers are modelled as household agents having dynamic preferences on types of electricity contracts o ered by the supplier. Development of preferences depends on personal values, memory and attitudes, as well as the degree of interaction in a social network structure. We are interested in exploring possible di usion rates of smart metering enabled services under di erent policy interventions and the impact of this technological di usion on individual and societal performance indicators. In four simulation experiments and three intervention policies we observe the di usion of energy services and individual and societal performance indicators (electricity savings, CO 2 emissions savings, social welfare, consumers' comfort change), as well as consumers' satisfaction. From these results and based on expert validation, we conclude that providing the consumer with more options does not necessarily lead to higher consumer's satisfaction, or better societal performance. A good policy should be centred on e ective ways to tackle consumers concerns.
Cherrelle Eid, Paul Codani, Yannick Pérez, Javier Reneses · 5 authors
In many electric systems worldwide the penetration of Distributed Energy Resources (DER) at the distribution levels is increasing. This penetration brings in different challenges for electricity system management; however if the flexibility of those DER is well managed opportunities arise for coordination. At high voltage levels under responsibility of the system operator, trading mechanisms like contracts for ancillary services and balancing markets provide opportunities for economic efficient supply of system flexibility services. In a situation with smart metering and real-time management of distribution networks, similar arrangements could be enabled for medium- and low-voltage levels. This paper presents a review and classification of existing DER as flexibility providers and a breakdown of trading platforms for DER flexibility in electricity markets.
Nicolas Gensollen, Vincent Gauthier, Monique Becker, Michel Marot
In the context of the smart grid, we propose in this paper an algorithm that forms coalitions of agents, called prosumers, that both produce and consume. It is designed to be used by aggregators that aim at selling aggregated surplus of production of the prosumers they control. We rely on real weather data sampled across stations of a given territory in order to simulate realistic production and consumption patterns for each prosumer. This enables us to capture geographical correlations among the agents while preserving the diversity due to different behaviors. As aggregators are bound to the market operator by a contract, they seek to maximize their offer while minimizing their risk. The proposed graph-based algorithm takes the underlying correlation structure of the agents into account and outputs coalitions with both high productivity and low variability. We show that the resulting diversified coalitions are able to generate higher benefits on a constrained energy market, and are more resilient to random failures of the agents.
This paper analyses the heterogeneity of household consumer preferences for electricity service contracts in a smart grid context. Platform pricing strategies that could incentivise consumers to participate in a two-sided electricity platform market are discussed. The research is based on original data from a discrete choice experiment on electricity service contracts that was conducted with 1,892 electricity consumers in Great Britain in 2015. We estimate a flexible mixed logit model in willingness to pay space and exploit the results in posterior analysis. The findings suggest that while consumers are willing to pay for technical support services, they are likely to demand significant compensation to share their usage and personally identifying data and to participate in automated demand response programs involving remote monitoring and control of electricity usage. Cross-subsidisation of consumers combining appropriate participation payments with sharing of bill savings could incentivise participation of the number of consumers required to provide the optimal level of demand response. We also examine the preference heterogeneity to suggest how, by targeting customers with specific characteristics, smart electricity service providers could significantly reduce their customer acquisition costs.
This paper presents a comprehensive framework for the assessment of reliability and risk implications of post-fault Demand Response (DR) to provide capacity release in smart distribution networks. A direct load control (DLC) scheme is presented to efficiently disconnect DR customers with differentiated reliability levels. The cost of interrupted load is used as a proxy for the value of the differentiated reliability contracts for different customers to prioritize the disconnections. The framework tackles current distribution system operator (DSO)’s corrective actions such as network reconfiguration, emergency ratings and load shedding, also considering the physical payback effects from the DR customers’ reconnection. Sequential Monte Carlo simulation (SMCS) is used to quantify the risk borne by the DSO if contracting fewer DR customers than required by deterministic security standards. Numerical results demonstrate the benefits of the proposed DR scheme, when compared to the current DLC scheme applied from the local DSO. In addition, as a key point to boost the commercial implementation of such DR schemes, the results show how the required DR volume could be much lower than initially estimated when properly accounting for the actual risk of interruptions and for the possibility of deploying the asset emergency ratings. The findings of this work support the rationale of moving from the current prescriptive deterministic security standards to a probabilistic reliability assessment and planning approach applied to smart distribution networks, which also involves distributed energy resources such as post-contingency DR for network support.
Large-scale deployment of reliable smart electricity metering networks has been considered as the first step towards a smart, integrated and efficient grid. On the consumer’s side, however, the real impact is still uncertain and limited. This paper evaluates the consumer’s perspective in the city of Västerås, Sweden, where full implementation of smart meters has been reached. New services, such as consumption feedback and the possibility to choose dynamic electricity pricing contracts, have been available from the adoption of this infrastructure. A web-based survey evaluating customers’ perception of these new services was carried out. The survey included consumers’ personal information, preferences about the type of information and the frequency of delivery and the preference for electricity pricing contracts. The results showed that the electricity consumption information offered by distribution system operators (DSOs) today is not detailed enough for customers to react accordingly. Additionally, while variable pricing contracts are becoming more popular, the available pricing schemes do not encourage customers to increase their consumption flexibility. Therefore, more detailed information from the smart meters should be made available, including disaggregated electricity consumption per appliance that would allow consumers to have more control over their energy consumption activities.
The smart grid is widely considered as an efficient and intelligent power system. With the aid of communication technologies, the smart grid can enhance the efficiency and reliability of the grid system through intelligent energy management. However, with the development of new energy sources, storage and transmission technologies together with the heterogeneous architecture of the grid network, several new features have been incorporated into the smart grid. These features make the energy trading more complex and pose a significant challenge on designing efficient trading schemes. Based on this motivation, in this paper, we present a comprehensive review of several typical economic incentive approaches adopted in the energy-trading control mechanisms. We focus on the technologies that address the challenges specific to the new features of the smart grid. Furthermore, we investigate the energy trading in a new cloud-based vehicle-to-vehicle energy exchange scenario. We propose an optimal contract-based electricity trading scheme, which efficiently increases the generated profit.
Although researchers have acknowledged the issue of commercial viability previously, it is only recently that they have laid emphasis on addressing the relative importance of commercial viability to catalyze the dissemination of decentralized sustainable energy systems to rural consumers in developing countries. A business enterprise is said to be commercially viable if its revenues are > costs. Here in this thesis these business enterprises or promoters of efforts are called as renewable energy companies (REC’s). Moreover researchers have failed to acknowledge or address the role of revenues even after acknowledging the merits of a market driven approach as opposed to donor driven approach. Given such a high relevance of revenues in a market approach to operate successfully and a lack of focus on the same by researchers, in this thesis we will analyze the practical issue of commercial viability of Indian REC’s through the lens of revenue model, while also addressing the literature gap on revenue drivers or revenue model components by exploring various relevant revenue drivers of commercially viable REC’s. This study takes an exploratory case study approach to enlist all the relevant revenue driver or revenue model components that are relevant for REC’s to attain commercial viability. This thesis primarily consists of three subsequent phases: first phase: theoretical gap identification. Second phase: identification of types and components of a revenue model and third phase: building a revenue driver – commercial viability framework. The aim of the first phase was to narrow in on the literate gap and also present relevant background literature. The first phase yielded the literature gap on revenue model components in addressing the practical issue of commercial viability. The aim of the second phase was to identify revenue model types and components. The result of which was that two types of revenue models namely: ownership and service revenue models was discovered. Most importantly six potential revenue drivers were also discovered. They are: consumer trust, pricing strategy, willingness to pay, flexibility of payments, number of users and revenue sharing. These six revenue drivers were derived on the premise that they would increase revenues such that REC’s attain commercial viability. This made up our initial conceptual model. Next, the aim of the third phase was to build a framework on revenue drivers or revenue model components – commercial viability of Indian REC’s. In order to do so firstly we analyzed cases where the initial conceptual model is leveraged into a more relevant context of Indian REC’s. The case studies were based on SIMPA Networks, Onergy, Rural Spark and MeraGao Power (MGP). All of these cases primarily are Indian companies exclusively catering to the Indian rural market otherwise also known as REC’s or Indian REC’s. The results of this section yielded us a relevant set of 12 revenue drivers i.e. six more in comparison to the initial set of 6 revenue drivers. They are consumer trust, supplier trust, pricing strategies, willingness to pay, flexibility of payments, number of users, revenue sharing, consumer financing, size of payments, service customization, after sales service/maintenance and discounts. Secondly, a cross case analysis was performed wherein findings from each case are pitched against each other to find the similarities and differences. The result of this section was firstly that, any sort of generalizations based on the type of revenue models was hard to come by and most importantly the type of revenue model only signified its affect on the source of financing and could play no role in explaining how and why commercial viability was being achieved. Moreover it also led to an inference that service revenue model poses more risk than ownership revenue model but however commercial viability was achieved by adopting both types of revenue model, which was quite the contrary to the outcome of literature survey. Secondly, list of revenue drivers was further narrowed to 10 from the previous list of 12. Basically willingness to pay was eliminated because it was already being considered in pricing strategies and number of users was also removed because it affected the commercial viability of REC’s in terms of both costs and revenues whereas the others only impacted only revenues. The final set of relevant revenue drivers are: consumer trust, supplier trust, pricing strategies, flexibility of payments, size of payments, revenue sharing, consumer financing, service customization, after sales service/maintenance and discounts. Lastly, a set of three factors was identified that actually contributed to the increase in revenues such that revenues were > costs. Or in other words served as a link between revenue drivers and commercial viability. They are namely: rate of adoption, recoupment of costs (regular payments) and retention. It is these afore mentioned revenue drivers that impact the three factors, which subsequently drive or increase revenues such that commercial viability can be attained. The ownership revenue model primarily derives its revenues from only the adoption factor, which subsequently brings in revenues to attain commercial viability. That said the adoption of DSE’s by the rural consumers is contingent or dependent on revenue drivers like consumer financing and size of payments among others. The revenues of REC’s employing service revenue model primarily depended on all the three factors like rate of adoption, recoupment of costs and retention. More specifically the revenue drivers should be conducive to rural customers such that they firstly adopt the product and/or service and most importantly make regular payments, which translates to revenues while retaining the existing customers. Moreover the retention factor only applies to REC’s that adopt a service revenue model with only a service platform like MGP unlike other REC’s, which adopt a only a product platform like Onergy or both product and service platform like in the case of SIMPA and Rural spark. In the backdrop of afore mentioned scientific implications several managerial implications can also be derived. Among many the key take away for incumbent managers and future potential entrants will be to look at each of the revenue drivers and adopt them carefully such that commercial viability can be attained contingent on the his/her appetite for risk and most of all focus less on the type of revenue model because that is not going to help achieve commercial viability. Future research should be aimed at firstly developing a more elaborate revenue driver- commercial viability framework. After which each of the revenue driver’s true affects on each of the factors should be quantitatively determined. This further helps to gain greater generalizability. That said the key limitation of this thesis is that it focuses only on one country i.e. India among other developing countries.
In the smart grid, large consumers can procure electricity energy from various power sources to meet their load demands. To maximize its profit, each large consumer needs to decide their energy procurement strategy under risks such as price fluctuations from the spot market and power quality issues. In this paper, an electric energy procurement decision-making model is studied for large consumers who can obtain their electric energy from the spot market, generation companies under bilateral contracts, the options market and self-production facilities in the smart grid. Considering the effect of unqualified electric energy, the profit model of large consumers is formulated. In order to measure the risks from the price fluctuations and power quality, the expected utility and entropy is employed. Consequently, the expected utility and entropy decision-making model is presented, which helps large consumers to minimize their expected profit of electricity procurement while properly limiting the volatility of this cost. Finally, a case study verifies the feasibility and effectiveness of the proposed model.
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India today needs to have around 2,OO,OOO MW of power to meet its current energy needs, but it is able to provide only about two third of it. Additional finances are difficult to come by and the infrastructure is often not available to make it reach the remote areas. Heavy roistering in city areas has been a perpetual feature in some states. Many of the dwellers of small cities have come to depend on what is called an 'inverter' and its associated battery based storage system to cope up with the frequent power outages. Seen from another perspective these systems only lack the solar panels to become completely self contained power systems. Thus addition of solar panels to these will be only an incremental cost. By encouraging this approach several problems can be solved all the same time. First of all this additional investment will be from the users themselves. Next the power generated will be environmentally friendly and the regular power supply and the grid may need to be used sparingly. These storage based systems may become parts of Smart Grids for the future as they may be further evolved to feed power into the grid.Evaluation of the performance of these systems has been studied through simulation and the economics of the system has been investigated under various conditions for typical users. The proposed system has been compared with the early telecom systems in India that were based on land lines and could not be expanded fast enough. Later the privatized and decentralized wireless based approach provided the desirable solutions.
Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC) and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS) flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.
Decentralized or distributed small renewable power facilities are usually installed in local communities for households and small business companies. These facilities include solar PV, concentrated solar power, and wind power, etc. In order to promote installations of such facilities, governments in many countries have developed a number of policies and business models. For example, in Germany and Canada, electricity feed-in tariff policy and business model were developed; in the USA, tax rebate policies and relevant business models were promoted. These policies and models have in some but not in large scale promoted decentralized small renewable power in local communities. The key issue is that these policies and business models do not provide sufficient incentives to local distribution companies (LDC), nor to renewable power installers and users. This paper’s research covers the creation of a business and communication model, named as LDC model, to incentivize both renewable power installers/users and LDCs. This LDC model can play a key role in promoting decentralized small-scale generation (DSG) with renewable energy in local communities. The core element of the LDC model is a revenue model which serves as an instrument to finance renewable installations for households and small commercial businesses. A case study is undertaken with real data of a power distribution company in Toronto, Canada. This paper concludes that with appropriate government policy and with the development of customized information systems for accessing households and small business via internet, an LDC will be able to take leadership in investing and installing small renewable power, and consequently enlarge the share of renewable energy supply in its local power distribution network.
The important energy requirements for the desalination process impose especially in autonomous and decentralized plants supplied by Renewable Energy Sources (RES). In this paper, five alternative energy generation topologies of Reverse Osmosis desalination process are evaluated. The proposed topologies assessed in terms of economic, environmental, technological and societal indices are compared using multi-criteria analysis, namely the Analytic Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). Ranking of topologies resulted in the selection of direct connection and hybrid configuration as optimum solutions. In case economic priorities prevail diesel generation should also be considered.
This paper focuses on efforts to build what policymakers call the “smart grid,” involving 1) improved remote monitoring and automatic and remote control of facilities in high-voltage electricity transmission networks; 2) improved remote monitoring, two-way communications, and automatic and remote control of local distribution networks; and 3) installation of “smart” metering and associated communications capabilities on customer premises so that customers can receive real-time price information and/or take advantage of opportunities to contract with their retail supplier to manage the consumer's electricity demands remotely in response to wholesale prices and network congestion. I examine the opportunities, challenges, and uncertainties associated with investments in “smart grid” technologies. I discuss some basic electricity supply and demand, pricing, and physical network attributes that are critical for understanding the opportunities and challenges associated with expanding deployment of smart grid technologies. Then I cover issues associated with the deployment of these technologies at the high voltage transmission, local distribution, and end-use metering levels.
Christine Brandstätt, Gert Brunekreeft, Nele Friedrichsen
Smart contracts based on voluntary participation and optionality can be a low transaction cost solution to implement locational signals in distribution networks and thereby avoid network investment. This paper examines the efficiency properties of smart contracts. Based on a three-node example network we show that cases exist in which smart contracts can achieve a pareto-improvement compared to the status-quo even with voluntary participation. With the pareto improvement at least one party is better of under a smart contract without worsening the situation for anyone else. We note that this requirement is very restrictive and leaves significant potential for efficiency improvements by smart contracts untapped. We then discuss the implementation of smart contracts with incentive regulation. There are two main tasks for the regulator: allowing network operators flexibility to offer such contracts and incentivizing network operators to do so.
The availability of abundant renewable resources, lack of fossil fuels and difficult geographical terrain for grid line extensions contribute to the advantages of renewable based decentralized rural electrification in Ne-pal. Solar home system (SHS) and micro-hydro are the most commonly adopted off-grid renewable energy technologies in the country. This dis-sertation examines the market of renewable energy based rural electrifi-cation within prevailing policy and programmes framework. The study verifies whether the market has been able to serve the poor in Nepal. It also captures the perception of various stakeholders (e.g. private sup-ply/installation companies, NGOs, financial institutions and the donor‘s programme) regarding the business, financing issues and the role of gov-ernment policy on the market development. In addition, the study dis-cusses and analyses renewable based rural electrification supply models, the economics behind rural electrification, market drivers and market distribution in the rural areas of Nepal. The financial mix in the off-grid rural electrification is generally charac-terized by subsidy, equity and credit. The study shows that awareness about renewable energy technologies and willingness to pay for electricity access has increased considerably. However, there is a huge financial gap between the cost of electrification and affordability among the poor. The distribution analysis shows there is significant increment in the extensive growth but decrease in the intensive growth rate of rural electrification thus indicating market expansion with uneven penetration among the ru-ral people. Solar PV technology is still not in the reach of the economic poor. Access to credit and cumbersome subsidy delivery mechanisms have been perceived as the major factors affecting the expansion of rural electrification by the stakeholders, requiring innovation in the credit and subsidy delivery system so that a larger rural population can be given ac-cess to electrification.