Blockchain Papers

Javier Contreras, Yeny E. Rodríguez

No abstract is available for this record.

Gerry Braun, Stan Hazelroth

Transitioning to clean, climate-friendly and smarter electricity systems means bringing innovative, capital-intensive, and increasingly decentralized power sector infrastructure on stream. National, state, and local policy should recognize and address the implications for finance , particularly the need for investments that capture and optimize local economic benefits.

Hiroyuki Mori, Hajime Fujita

This paper proposes an efficient method for designing a contract model of the weather derivatives between energy utilities in Smart Grid. It is well-known that the weather conditions bring a profit decline or the increase of expenses to do damage to sound management. Weather derivatives are useful for solving such a problem. One of the ideas is to use the complementary relationship between electric power and gas companies in a sense that electric power companies are apt to make profits in hot summer while gas companies are inclined to reduce revenue. This paper focuses on how to create a reasonable contract model of the weather derivative. In this paper, EPSO (Evolutionary Particle Swarm Optimization) of meta-heuristics is applied to designing a contract model of the weather derivative. The proposed method aims at equalizing the mean and the variance of the payoffs between the power and gas companies. To enhance the model accuracy, DA clustering of global clustering is used to classify the historical data into clusters. The effectiveness of the proposed method is demonstrated for the real data in Tokyo, Japan.

Nele Friedrichsen, Marian Klobasa, Martin Pudlik

Decentralized generation on the owners premises can be used on-site which we call auto-consumption. In a system with energy based (volumetric) network charges this reduces network income and in turn causes higher network charges on remaining usage with redistributional effects among customers. We estimate the effect from PV auto-consumption in Germany to be small in many network areas but significant in others leading to significant regional unequality. The effect may be self-enforcing and could increase strongly with pronounced shares of PV and auto-consumption. Further analysis should address the causal links to inform modifications to network charging for higher cost causality in power systems with high shares of (renewable) decentralized generation. Meanwhile a higher fixed component in network charges could be a pragmatic way to mitigate effects and serve a more equal participation of auto-consumers in network financing.

Markus Bestehorn, Theodor Borsche

Particularly with the rise of intermittent renewable energy sources, balancing electricity consumption and production is the core challenge of smart grids. The most important drawback of existing approaches is that controlling loads or producers is typically heavily regulated by contracts or laws. These real-world constraints significantly increase the complexity associated with achieving the aforementioned balance. In this paper, we propose a planning algorithm for smart grids that respects contractual or legal constraints while balancing power consumption and production. Additionally, our planning approach manages energy producers as well as consumers. Thus, it achieves the balance in the grid by controlling a combination of producers and consumers.

Masood Parvania, Mahmud Fotuhi‐Firuzabad, Mohammad Shahidehpour

Advancements in smart grid technologies have made it possible to apply various options and strategies for the optimization of demand response (DR) in electricity markets. DR aggregation would accumulate potential DR schedules and constraints offered by small- and medium-sized customers for the participation in wholesale electricity markets. Despite various advantages offered by the hourly DR in electricity markets, practical market tools that can optimize the economic options available to DR aggregators and market participants are not readily attainable. In this context, this paper presents an optimization framework for the DR aggregation in wholesale electricity markets. The proposed study focuses on the modeling strategies for energy markets. In the proposed model, DR aggregators offer customers various contracts for load curtailment, load shifting, utilization of onsite generation, and energy storage systems as possible strategies for hourly load reductions. The aggregation of DR contracts is considered in the proposed price-based self-scheduling optimization model to determine optimal DR schedules for participants in day-ahead energy markets. The proposed model is examined on a sample DR aggregator and the numerical results are discussed in the paper.

Per J. Agrell, Peter Bogetoft, Misja Mikkers

No abstract is available for this record.

Matías Negrete-Pincetic, Sean Meyn

Many electricity markets around the world treat electricity as a commodity - without qualitative distinctions. This view does not recognize the many different attributes and services that different generation technologies can provide. The Smart Grid platform will provide the technological conditions for even more service differentiation. In this paper, we discuss elements of an alternative view for organizing the markets in a Smart Grid scenario. The key element is the consideration of electricity as a multi-attribute product. The specification of these attributes will first require a clear understanding of the Social Planner's Problem (SPP), as defined in standard economics. Such understanding will facilitate the valuation of the resource attributes with respect to the fulfillment of societal objectives. The emphasis of the paper is investigating the SPP for resource allocation, getting resources appropriately sized in advance. The solution of this problem offers insight, and provides sensible guidelines for how many resources, and of which type, are required. Our viewpoints are illustrated via a detailed investigation of the system-wide value of operational flexibility, along with the market implications. A general discussion about the role of contracts to support multi-attribute products is also included.

Qun Zhou, Wei Guan, Wei Sun

Load forecasting is highly important for power system operation and planning. Demand response, as a valuable feature in smart grid, is growing dramatically as an effective demand management method. However, traditional load forecasting tools have limitations to reflect demand response customer behaviors into load predictions. The energy consumption by demand response customers is mostly guided by their signed contracts. Therefore, existing demand response contracts are reviewed in this study for both wholesale and retail markets. An illustrative example is provided to explore the impact of these contracts on load forecasting. A concept of proactive load forecasting considering contract types is then proposed and discussed for forecasting loads in a smart grid environment.

Paul L. Joskow

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.

Pedro Oliveira, Zita Vale, Hugo Morais, Tiago Pinto · 5 authors

No abstract is available for this record.

Christine Brandstätt, Gert Brunekreeft, Nele Friedrichsen

No abstract is available for this record.

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.

Dionysios Aliprantis, Scott Penick, Leigh Tesfatsion, Huan Zhao

Our research team is developing an agent-based test bed for the integrated study of retail and wholesale power markets operating over transmission and distribution networks with smart-grid functionality. This test bed seams together two existing test beds, the AMES Wholesale Power Market Test Bed and the GridLAB-D distribution platform. As a first step, we have designed an integrated retail/wholesale market module specifically based on the ERCOT (Texas) energy region, and we are using simplified versions of this module to study potential retail consumer response to real-time-pricing contracts supported by advanced metering. This study reports on the latter work.

Chaehwan Won

No abstract is available for this record.

Güzay Pasaoglu Kilanç, İlhan Or

No abstract is available for this record.

Ross Baldick

In this paper, a property rights model for electric transmission is proposed and its properties analyzed. The proposed rights, called "border flow rights," support financial hedging of transmission risk and merchant transmission expansion through associated financial rights, called "contracts for differences of differences." These financial rights allow for forward trading of both energy and transmission by a unified exchange, avoiding the bifurcation in current markets between decentralized long-term energy trading and centralized long-term transmission trading. Such long-term trading can help to support the financing of both generation and transmission assets. We consider incentive properties of such a right in the absence of lumpiness, economies of scale, and market power.

Zhihong Liang, Kun Yang, Yaowei Sun, Jiahai Yuan · 6 authors

No abstract is available for this record.

Silvia Rezessy, Konstantin Dimitrov, Diána Ürge-Vorsatz, Seth Baruch

No abstract is available for this record.

Franz Hubert

No abstract is available for this record.