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25 pages, 2288 KiB

Open AccessArticle

Virtual Power Plant Optimization Process Under the Electricity–Carbon–Certificate Multi-Market: A Case Study in Southern China

by Yanbin Xu, Yi Liao, Shifang Kuang, Jiaxin Ma and Ting Wen

Processes 2025, 13(7), 2148; https://doi.org/10.3390/pr13072148 - 6 Jul 2025

Viewed by 347

Abstract

Over the past decade, China has vigorously supported the development of renewable energy and has initially established the electricity–carbon–certificate multi-market. As a typical market-oriented demand-side management model, studying the optimization process and cases of virtual power plants (VPPs) under the multi-market has significant importance for enhancing the operation level of VPPs, as well as promoting corresponding experiences. Based on the mechanisms and impacts of the electricity–carbon–certificate multi-market, this manuscript takes a VPP project in southern China as a case, constructs a sequential decision-making optimization model for the VPP under a diversified market, and solves it using reinforcement learning and Markov decision theory. The case analysis shows that, compared to energy supply income, although the proportion of income from certificate trading and carbon trading in the multi-market is relatively limited, participating in the electricity–carbon–certificate multi-market can significantly enhance VPPs’ willingness to accommodate the uncertainties of renewable energy and can significantly improve the economic and environmental performances of VPPs, which is of great significance for improving the energy structure and accelerating the process of low-carbon energy transformation. Full article

(This article belongs to the Special Issue Evaluation, Decision–Making and Market Simulation of a New Type of Power System)

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21 pages, 574 KiB

Open AccessArticle

What Incentives Are Required for Renewables to Provide Redispatch Services? A Simulation in a Multi-Market Setting

by Regina Hemm, Ksenia Poplavskaya, Stefan Strömer, Miriam Schwebler, Bernadette Fina and Fabian Leimgruber

Energies 2022, 15(15), 5676; https://doi.org/10.3390/en15155676 - 4 Aug 2022

Cited by 2 | Viewed by 2503

Abstract

Renewable energy sources (RES) can provide valuable flexibility potential for multiple markets and grid services in the future. In this paper, the focus lies on the development of algorithms for an optimal dispatch and bidding of a RES-based virtual power plant (VPP) by considering current short-term and balancing market conditions in Austria, as well as a proposed redispatch market. Specifically, different pricing and bidding strategies for a redispatch market are compared and their feasibility is analyzed. The attractiveness of different pricing models and remuneration mechanisms for redispatch, as well as the influence of the redispatch call probability on the bidding behavior of the VPP, is investigated. The simulation of the bidding behavior is carried out using linear optimization techniques. The paper describes the algorithms as well as the assumptions for market rules in redispatch, balancing and short-term electricity markets. The results show that the probability to be activated for redispatch and thus the required incentives depend highly on the location of the plant. Pre-curtailment of the plant to offer positive redispatch is not recommended as the prices would need to be set at up to 200–300% of the day-ahead price. Full article

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10 pages, 1159 KiB

Open AccessArticle

Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants

by Rakkyung Ko and Sung-Kwan Joo

Energies 2020, 13(1), 67; https://doi.org/10.3390/en13010067 - 21 Dec 2019

Cited by 9 | Viewed by 2605

Abstract

Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Machine Learning and Optimization with Applications of Power System II)

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14 pages, 790 KiB

Open AccessArticle

Implementation Schemes for Electric Bus Fleets at Depots with Optimized Energy Procurements in Virtual Power Plant Operations

by Andreas F. Raab, Enrico Lauth, Kai Strunz and Dietmar Göhlich

World Electr. Veh. J. 2019, 10(1), 5; https://doi.org/10.3390/wevj10010005 - 17 Jan 2019

Cited by 30 | Viewed by 8083

Abstract

For the purpose of utilizing electric bus fleets in metropolitan areas and with regard to providing active energy management at depots, a profound understanding of the transactions between the market entities involved in the charging process is given. The paper examines sophisticated charging strategies with energy procurements in joint market operation. Here, operation procedures and characteristics of a depot including the physical layout and utilization of appropriate charging infrastructure are investigated. A comprehensive model framework for a virtual power plant (VPP) is formulated and developed to integrate electric bus fleets in the power plant portfolio, enabling the provision of power system services. The proposed methodology is verified in numerical analysis by providing optimized dispatch schedules in day-ahead and intraday market operations. Full article

(This article belongs to the Special Issue Selected Papers from The 30th International Electric Vehicles Symposium and Exhibition (Stuttgart, Germany))

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12 pages, 1086 KiB

Open AccessArticle

The Optimal Configuration Scheme of the Virtual Power Plant Considering Benefits and Risks of Investors

by Jingmin Wang, Wenhai Yang, Huaxin Cheng, Lingyu Huang and Yajing Gao

Energies 2017, 10(7), 968; https://doi.org/10.3390/en10070968 - 11 Jul 2017

Cited by 17 | Viewed by 3852

Abstract

A virtual power plant (VPP) is a special virtual unit that integrates various distributed energy resources (DERs) distributed in the generation and consumption sides. The optimal configuration scheme of the VPP needs to break the geographical restrictions to make full use of DERs, considering the uncertainties. First, the components of the DERs and the structure of the VPP are briefly introduced. Next, the cubic exponential smoothing method is adopted to predict the VPP load requirement. Finally, the optimal configuration of the DER capacities inside the VPP is calculated by using portfolio theory and genetic algorithms (GA). The results show that the configuration scheme can optimize the DER capacities considering uncertainties, guaranteeing economic benefits of investors, and fully utilizing the DERs. Therefore, this paper provides a feasible reference for the optimal configuration scheme of the VPP from the perspective of investors. Full article

(This article belongs to the Section F: Electrical Engineering)

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19 pages, 1763 KiB

Open AccessArticle

Two-Stage Coordinated Operational Strategy for Distributed Energy Resources Considering Wind Power Curtailment Penalty Cost

by Jing Qiu, Junhua Zhao, Dongxiao Wang and Yu Zheng

Energies 2017, 10(7), 965; https://doi.org/10.3390/en10070965 - 10 Jul 2017

Cited by 16 | Viewed by 4514

Abstract

The concept of virtual power plant (VPP) has been proposed to facilitate the integration of distributed renewable energy. VPP behaves similar to a single entity that aggregates a collection of distributed energy resources (DERs) such as distributed generators, storage devices, flexible loads, etc., so that the aggregated power outputs can be flexibly dispatched and traded in electricity markets. This paper presents an optimal scheduling model for VPP participating in day-ahead (DA) and real-time (RT) markets. In the DA market, VPP aims to maximize the expected profit and reduce the risk in relation to uncertainties. The risk is measured by a risk factor based on the mean-variance Markowitz theory. In the RT market, VPP aims to minimize the imbalance cost and wind power curtailment by adjusting the scheduling of DERs in its portfolio. In case studies, the benefits (e.g., surplus profit and reduced wind power curtailment) of aggregated VPP operation are assessed. Moreover, we have investigated how these benefits are affected by different risk-aversion levels and uncertainty levels. According to the simulation results, the aggregated VPP scheduling approach can effectively help the integration of wind power, mitigate the impact of uncertainties, and reduce the cost of risk-aversion. Full article

(This article belongs to the Section F: Electrical Engineering)

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