Business models for distributed energy resources: A review and empirical analysis

Burger, Scott P.; Luke, Max

doi:10.1016/j.enpol.2017.07.007

Cited by 190 publications

(126 citation statements)

References 47 publications

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“…The utility price is usually determined by the utility company in the form of a ToU pricing or a real-time pricing [24]. In the ToU pricing, the utility prices are just offered in a table with a few levels of prices according to time zone.…”

Section: Overall System Structurementioning

confidence: 99%

Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

2018

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A smart grid facilitates more effective energy management of an electrical grid system. Because both energy consumption and associated building operation costs are increasing rapidly around the world, the need for flexible and cost-effective management of the energy used by buildings in a smart grid environment is increasing. In this paper, we consider an energy management system for a smart energy building connected to an external grid (utility) as well as distributed energy resources including a renewable energy source, energy storage system, and vehicle-to-grid station. First, the energy management system is modeled using a Markov decision process that completely describes the state, action, transition probability, and rewards of the system. Subsequently, a reinforcement-learning-based energy management algorithm is proposed to reduce the operation energy costs of the target smart energy building under unknown future information. The results of numerical simulation based on the data measured in real environments show that the proposed energy management algorithm gradually reduces energy costs via learning processes compared to other random and non-learning-based algorithms.

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Section: Overall System Structurementioning

confidence: 99%

Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

2018

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“…11 For a business model analysis (out of the scope of this paper) see [1]. 12 We do not address any particular forecasting mechanism/technology.…”

Section: Households Problem Definitionmentioning

confidence: 99%

Novel market approach for locally balancing renewable energy production and flexible demand

Horta

Kofman

Menga

et al. 2017

2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)

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Future electricity distribution grids will host a considerable share of variable renewable energy sources and local storage resources. Moreover, they will face new load structures due for example to the growth of the electric vehicle market. These trends raise the need for new paradigms for distribution grids operation, in which Distribution System Operators will increasingly rely on demand side flexibility and households will progressively become prosumers playing an active role on smart grid energy management. However, in present energy management architectures, the lack of coordination among actors limits the capability of the grid to enable the mentioned trends. In this paper we tackle this problem by proposing an architecture that enables households to autonomously exchange energy blocks and flexibility services with neighbors, operators and market actors. The solution is based on a blockchain transactive platform. We focus on a market application, where households can trade energy with their neighbors, aimed to locally balancing renewable energy production. We propose a market mechanism and dynamic transport prices that provide an incentive for households to locally manage energy resources in a way that responds to both prosumer and operator needs. We evaluate the impact of such markets through comprehensive simulations using power flow analysis and realistic load profiles, providing valuable insight for the design of appropriate mechanisms and incentives.

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“…While distributed energy systems and technologies to support new economic models of electricity generation and consumption are being investigated (William et al ., ; Burger & Luke, ; Green & Newman, ), exactly how blockchain could be applied to carbon markets has only just begun to be explored. Carbon markets are premised on the theory that reducing emissions can be more economically and environmentally effectively achieved through trading (Bumpus & Liverman, ; Schmalensee & Stavins, ).…”

Section: Introductionmentioning

confidence: 99%

Applying Blockchain to the Australian Carbon Market

Hartmann

Schierl

2019

J of App Econs and Policy

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Blockchain is a distributed digital ledger system that establishes transparent contract processes and facilitates secure but trusted business transactions. Policy-makers around the world are intrigued by the potential of this emerging technology to solve policy problems, including the challenges of the transition away from centralised, linear models of energy generation and consumption towards decentralised and distributed energy systems. Blockchain has also been promoted as a mechanism to transform carbon markets, yet the focus in this area to date has been on using blockchain to create new carbon market schemes. This paper addresses an important research gap by asking how blockchain could be applied to an existing carbon market. To answer this question, the study uses an established design process to develop an Australian carbon market blockchain design. The paper finds that this design could improve the efficiency, equity and effectiveness of the Australian carbon market. This paper makes an important research contribution to carbon market policy development by developing a blockchain design that could improve how an existing carbon market functions, and the findings presented here are relevant to government and industry stakeholders globally.

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Business models for distributed energy resources: A review and empirical analysis

Cited by 190 publications

References 47 publications

Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

Novel market approach for locally balancing renewable energy production and flexible demand

Applying Blockchain to the Australian Carbon Market

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