Light robust co-optimization of energy and reserves in the day-ahead electricity market

Article Energy & Fuels

A multi-stage stochastic programming model for the unit commitment of conventional and virtual power plants bidding in the day-ahead and ancillary services markets

Andrea Fusco et al.

APPLIED ENERGY (2023)

添加到收藏夹

Article Energy & Fuels

Stochastic programming approach for optimal day-ahead market bidding curves of a microgrid

Robert Herding et al.

APPLIED ENERGY (2023)

添加到收藏夹

Article Energy & Fuels

A novel stochastic model for flexible unit commitment of off-grid microgrids

Simone Polimeni et al.

Summary: This work proposes a new two-stage stochastic optimization approach for the Energy Management System (EMS) of MicroGrids (MG). It integrates scenario-based uncertainty characterization with piecewise affine correction rules, improving service reliability and fuel efficiency. The proposed EMS outperforms state-of-the-art methods in a real-world case study and laboratory-scale microgrid, achieving significant cost savings and secure operations.

APPLIED ENERGY (2023)

添加到收藏夹

Article Energy & Fuels

Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach

Adam F. Abdin et al.

Summary: This paper proposes a multistage robust generation expansion planning model that can effectively address uncertainties and generate appropriate power generation investment decisions. By using decision rules to transform the model, the proposed solution method is shown to efficiently solve the problem. The results demonstrate the effectiveness of the proposed approach in dealing with multiple operational uncertainties.

APPLIED ENERGY (2022)

添加到收藏夹

Article Engineering, Electrical & Electronic

Stochastic short-term scheduling of a wind-solar-hydro complementary system considering both the day-ahead market bidding and bilateral contracts decomposition

Qian Cheng et al.

Summary: The complementary operation of hydropower, wind, and photovoltaic power is a cost-efficient solution for integrating intermittent wind and PV power. This study establishes a stochastic scheduling model to optimize the day-ahead market bids and the decomposition of daily contracts, aiming to maximize the profits and resource utilization efficiency of a wind-solar-hydro complementary system. The results show that the proposed model effectively decomposes the total energy of the daily contracts and achieves larger benefits, less power curtailment, and higher water resources utilization efficiency.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)

添加到收藏夹

Article Green & Sustainable Science & Technology

Acknowledgments This work was partially supported by the National Science Founda- tion under Grant CBET-1643244.

Ning Zhao et al.

Summary: This paper proposes a novel robust unit commitment framework for integrating variable renewable energy into sustainable power systems. The framework incorporates uncertain intermittent power outputs using data-driven disjunctive uncertainty sets and machine learning. The approach identifies uncertainty space based on renewable power forecast error data and constructs disjunctive uncertainty sets using various techniques. The problem is formulated into a two-stage adaptive robust unit commitment model and solved using a tailored decomposition-based optimization algorithm. Case studies demonstrate that the proposed framework improves economic performance with reduced computational time compared to conventional methods.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

添加到收藏夹

Review Green & Sustainable Science & Technology

Short term wholesale electricity market designs: A review of identified challenges and promising solutions

Lina Silva-Rodriguez et al.

Summary: This paper provides a comprehensive investigation and detailed assessment of modifications proposed in the literature for the European electricity markets in the short-term timescale. It identifies the barriers hindering market performance and explores various market solutions proposed in the literature. The analysis shows that no single proposal can address all the barriers simultaneously, highlighting the need for a future-proof market design that combines different elements of proposed solutions to overcome implementation challenges and mitigate market barriers.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

添加到收藏夹

Article Construction & Building Technology

Two-stage stochastic programming for risk-aware scheduling of energy hubs participating in day-ahead and real-time electricity markets

A. Rezaee Jordehi

Summary: Energy hubs play a crucial role in sustainable cities by coupling different energy carriers to enhance efficiency and decrease costs. This research proposes a stochastic model for operating energy hubs in conjunction with electricity markets, considering uncertainties. Results show that considering value-at-risk improves worst-case operation costs but may worsen costs in other scenarios. Increasing the weight factor increases expected costs and decreases value-at-risk, while increasing the confidence level increases value-at-risk.

SUSTAINABLE CITIES AND SOCIETY (2022)

添加到收藏夹

Article Energy & Fuels

Two-Stage stochastic optimization for operating a Renewable-Based Microgrid

Hamza Abunima et al.

Summary: Carbon emissions resulting from urbanization and population growth worldwide are leading to climate change and global warming. To address the challenges posed by the intermittent behavior of renewable energy sources (RES), microgrid (MG) technology is introduced and studied. This paper proposes a two-stage stochastic optimization method integrated with a novel artificial neural network (ANN)-based prediction model to solve the scheduling issue of MG in islanded mode.

APPLIED ENERGY (2022)

添加到收藏夹

Article Engineering, Electrical & Electronic

A light robust optimization approach for uncertainty-based day-ahead electricity markets

Lina Silva-Rodriguez et al.

Summary: This paper proposes a light robust mechanism for day-ahead market clearing to find a balance between robustness and economic efficiency, encouraging participation of stochastic producers.

ELECTRIC POWER SYSTEMS RESEARCH (2022)

添加到收藏夹

Article Thermodynamics

A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets

Ana R. Silva et al.

Summary: This paper proposes a multistage stochastic decision-aid algorithm based on linear programming to optimize the bidding strategy of market agents in three different electricity markets. The results show that participating in all three markets increases the profit achieved by the market agent while decreasing the incurred imbalances.

ENERGY (2022)

添加到收藏夹

Review Energy & Fuels

A review of co-optimization approaches for operational and planning problems in the energy sector

Geremi Gilson Dranka et al.

Summary: This paper presents a comprehensive overview of the application of co-optimization in the energy sector based on a systematic literature review of 211 related studies, tracking frontiers, trends, and potential research gaps. The findings suggest technical challenges and the necessity of data-intensive procedures in co-optimization approaches. Future challenges include addressing uncertainties and balancing model fidelity, spatial granularity, and geographical coverage.

APPLIED ENERGY (2021)

添加到收藏夹

Article Energy & Fuels

An incentive-compatible distributed integrated energy market mechanism design with adaptive robust approach

Yunting Yao et al.

Summary: Research shows that sharing energy may lead to profit loss for some participants and diminish the incentive to join the coalition. To address this issue, an optimization model is proposed in this paper to allocate the cooperative surplus based on market contributions, ensuring fair shares for market participants.

APPLIED ENERGY (2021)

添加到收藏夹

Article Energy & Fuels

Two-stage stochastic optimization frameworks to aid in decision-making under uncertainty for variable resource generators participating in a sequential energy market

Razan A. H. Al-Lawati et al.

Summary: This study proposes two decision-making frameworks for a wind energy generator participating in different energy markets, showing better performance in simulation experiments. These frameworks help in making better decisions while maximizing return on investment.

APPLIED ENERGY (2021)

添加到收藏夹

Article Energy & Fuels