Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators

Goudarzi, Arman; Swanson, Andrew; Coller, John van; Siano, Pierluigi

doi:10.1016/j.apenergy.2016.12.068

Cited by 16 publications

(6 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We randomly generate the quadratic cost parameters (which is consistent with the approach in Goudarzi et al (2017); Ruiz et al (2012); Oliveira et al (2013)). For the emission intensity, our parameters are consistent with Farhat and Ugursal (2010).…”

Section: Datamentioning

confidence: 99%

Contracts in Electricity Markets under EU ETS: A Stochastic Programming Approach

Abate,

Riccardi,

Ruiz

2021

Preprint

View full text Add to dashboard Cite

The European Union Emission Trading Scheme (EU ETS) is a cornerstone of the EU's strategy to fight climate change and an important device for plummeting greenhouse gas (GHG) emissions in an economically efficient manner. The power industry has switched to an auction-based allocation system at the onset of Phase III of the EU ETS to bring economic efficiency by negating windfall profits that have been resulted from grandfathered allocation of allowances in the previous phases. In this work, we analyze and simulate the interaction of oligopolistic generators in an electricity market with a gametheoretical framework where the electricity and the emissions markets interact in a twostage electricity market. For analytical simplicity, we assume a single futures market where the electricity is committed at the futures price, and the emissions allowance is contracted in advance, prior to a spot market where the energy and allowances delivery takes place. Moreover, a coherent risk measure is applied (Conditional Value at Risk) to model both risk averse and risk neutral generators and a two-stage stochastic optimization setting is introduced to deal with the uncertainty of renewable capacity, demand, generation, and emission costs. The performance of the proposed equilibrium model and its main properties are examined through realistic numerical simulations. Our results show that renewable generators are surging and substituting conventional generators without compromising social welfare. Hence, both renewable deployment and emission allowance auctioning are effectively reducing GHG emissions and promoting low-carbon economic path.

show abstract

Section: Datamentioning

confidence: 99%

Contracts in Electricity Markets under EU ETS: A Stochastic Programming Approach

Abate,

Riccardi,

Ruiz

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…RTP in Stackelberg game. Most of existing works on RTP consider only one electricity supplier [2,9,13,19,29], however, the current retail electricity market is gradually going through the change from one or two monopoly electricity retailers into the coexistence state of multiple electricity retailers [18]. As a result of competition among different electricity retailers, the electricity users enjoy better service and more flexible electricity access by using smart meters and other equipments.…”

Section: (Communicated By Jun Fu)mentioning

confidence: 99%

A real-time pricing scheme considering load uncertainty and price competition in smart grid market

Dai¹,

Gao²,

Gao³

et al. 2020

Journal of Industrial &Amp; Management Optimization

View full text Add to dashboard Cite

As a powerful tool of Demand Response (DR) techniques in smart grid market, Real-time Pricing (RTP) may optimize the electricity consumption pattern of users and improve the efficiency of electricity market. In this paper, a multi-leader-follower Stackelberg Game (SG) based on RTP is established to model the strategic interaction behavior between multiple electricity retailers and multiple users while simultaneously considering the power load uncertainty of users and the price competition among electricity retailers. In the game model, electricity retailers aim to seek their revenue maximization while the optimal power consumption competition among the users is taken into account. Lagrange multiplier method is utilized to solve the Nash Equilibriums (NE) of two non-cooperative games, and the closed-form optimal solution is obtained, then the Stackelberg Equilibrium (SE) consisting of the optimal real-time prices of electricity retailers and the power consumption of users is given. Finally, the numerical analysis results verify that the proposed scheme can reduce the real-time electricity price and increase the users satisfaction under feasible constraint, which shows the effectiveness and better performance of proposed RTP scheme.

show abstract

“…When considering a methodology for the analysis of energy generation systems both at the continental level [24][25][26] and the island level, [9,22,27,28], and particularly in the Canary Islands [1,3,4], several authors have opted for the Hybrid Optimization of Multiple Energy Resources (HOMER) model. This software, which was developed by the National Renewable Energy Laboratory (NREL) [1,8], estimates the best energy system, economic investment, and levelized cost of energy (LCE), among others, and contemplates different energy sources.…”

Section: Introductionmentioning

confidence: 99%

Alternatives for the Optimization and Reduction in the Carbon Footprint in Island Electricity Systems (IESs)

Lozano Medina,

Perez-Baez,

Leon-Zerpa

et al. 2024

Sustainability

View full text Add to dashboard Cite

The penetration of renewable energies in island electricity systems (IESs) poses a series of challenges, which include, among others, grid stability, the response to demand, and the security of the supply. Based on the current characteristics of electricity demand on the islands of the Canary Archipelago (Spain) and their electricity production systems, this study presents a series of alternative scenarios to reduce greenhouse gas (GHG) emissions and increase the penetration of renewable energies. The goal is to optimize combustion-based (nonrenewable) energy production and combine it with renewable-based production that meets the requirements of dynamic response, safety, scaling, and integration with nonrenewable systems in terms of efficiency and power. As verified in the research background, the combination of power producing equipment that is generally employed on the islands is not the best combination to reduce pollution. The aim of this work is to find other possible combinations with better results. A methodology is developed and followed to obtain the lowest GHG production and to determine the measures to be applied based on: (a) changing the fuel type by switching to natural gas in the equipment that allows it; (b) using optimal combinations of the least polluting energy production equipment; (c) integrating, to the extent that it is possible, the Chira-Soria pumped hydroelectric energy storage plant into the Gran Canaria electricity system. A series of alternative scenarios are generated with different operating conditions which show the possibility of increasing the renewable installed capacity in the Canary Islands by up to 36.78% (70% in Gran Canaria), with a 65.13% reduction in GHG emissions and a 71.45% reduction in fuel consumption. The results of this study contribute, through the different measures determined through our research, to the mitigation of GHG emissions.

show abstract

Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators

Cited by 16 publications

References 47 publications

Contracts in Electricity Markets under EU ETS: A Stochastic Programming Approach

Contracts in Electricity Markets under EU ETS: A Stochastic Programming Approach

A real-time pricing scheme considering load uncertainty and price competition in smart grid market

Alternatives for the Optimization and Reduction in the Carbon Footprint in Island Electricity Systems (IESs)

Contact Info

Product

Resources

About