Carbon-Aware and AI-Empowered Operating Processes of Virtual Power Plants in Renewable Energy Grids

Dear Colleagues,

The transition toward renewable-dominant power systems is reshaping how distributed resources are planned, aggregated, traded, and operated. Virtual power plants (VPPs) are evolving from conventional demand-response aggregators into multi-functional operating entities that integrate distributed photovoltaics, wind power, battery energy storage, electric vehicles, industrial flexible loads, data centers, zero-carbon parks, and multi-energy facilities. They provide an operational bridge between fragmented edge-side resources and system-level requirements for flexibility, reliability, market participation, and low-carbon transition.

The necessity of this Special Issue arises from three intertwined challenges. First, high shares of variable renewables require dispatchable flexibility that can be verified, monetized, and coordinated across distribution and transmission networks. Second, electricity markets, ancillary-service markets, green power trading, demand-response mechanisms, carbon markets, and carbon-footprint accounting are developing at different speeds. In such incomplete market environments, VPP operators must make decisions under imperfect price signals, asymmetric information, uncertain settlement rules, and multiple revenue streams. Third, the shift from energy-consumption control to carbon-intensity and total-carbon-emission dual control creates new operational and planning requirements for parks, campuses, and industrial clusters.

Against this background, electricity–carbon interaction technologies are becoming central to the next generation of VPPs. VPPs should no longer be evaluated only by energy cost or peak shaving, but also by their capability to coordinate power flows, carbon flows, flexibility values, green certificates, carbon allowances, carbon footprints, and marginal carbon signals. Carbon-aware VPP operation can support renewable energy accommodation, low-carbon dispatch, carbon quota management, product-level carbon accounting, and transparent allocation of emission responsibilities among heterogeneous participants.

Artificial intelligence further expands the feasible scope of VPP operation. AI-enabled source-to-edge coordination can connect source-side renewable forecasting, grid-side security constraints, storage-side degradation management, load-side behavioral response, and edge-side device control. Promising methods include physics-informed machine learning, digital twins, reinforcement learning, federated learning, graph neural networks, large energy models, distributed optimization, and explainable AI. These techniques can improve forecasting, bidding, dispatch, fault diagnosis, carbon-emission monitoring, and real-time control while respecting privacy, cybersecurity, and operational constraints.

This Special Issue aims to collect original research, methodological advances, and practical demonstrations on carbon-aware and AI-empowered VPP operating processes in renewable energy grids. Particular attention will be given to VPP business strategies in incomplete electricity–carbon markets, electricity–carbon coupled optimization, source–grid–load–storage and source–edge collaborative control, and zero-carbon park operation and planning under dual constraints on carbon intensity and total emissions.

Topics of interest include, but are not limited to, the following:

• Carbon-aware operation, planning, and control of VPPs in renewable-rich power systems;
• Electricity–carbon interaction mechanisms, carbon-flow tracking, marginal carbon-emission signals, and carbon responsibility allocation for VPPs;
• VPP operating strategies under incomplete market environments, including multi-market bidding, contract design, risk hedging, benefit allocation, and policy uncertainty;
• Joint participation of VPPs in energy, ancillary-service, demand-response, green power, green certificate, and carbon-related markets;
• AI-enabled source–grid–load–storage coordination, source-to-edge collaborative control, and edge intelligence for VPPs;
• Forecasting, scheduling, and real-time dispatch using machine learning, reinforcement learning, digital twins, federated learning, graph learning, and explainable AI;
• Zero-carbon industrial parks, campuses, data centers, and eco-industrial clusters operated through VPP platforms;
• Carbon intensity and total emission dual-control models for zero-carbon park planning, equipment sizing, energy management, and product carbon-footprint accounting;
• Multi-energy VPPs integrating electricity, heat, cooling, gas, hydrogen, energy storage, flexible manufacturing, electric vehicles, and CCUS-related resources;
• Robust, stochastic, distributionally robust, and risk-aware optimization for renewable uncertainty, market uncertainty, and carbon-policy uncertainty;
• Grid-support functions of VPPs, including congestion management, resilience enhancement, frequency response, voltage support, and grid-forming resource coordination;

We sincerely invite academics, system operators, aggregators, industrial practitioners, and policy researchers to submit original research articles, review papers, case studies, and technical reports that advance the theory, methods, and practical implementation of VPPs in the era of renewable energy, artificial intelligence, and electricity–carbon coordinated transition.

Dr. Zelong Lu
Dr. Shuai Fan
Dr. Chenjia Gu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• virtual power plants (VPPs)
• distributed energy resources (DERs)
• electricity–carbon coupling
• carbon-aware operation
• AI-enabled source–grid–load–storage coordination
• incomplete electricity markets
• demand response
• green power and carbon markets
• zero-carbon industrial parks
• multi-energy systems