Multi-objective coordinated optimization of low-carbon building energy systems based on high renewable energy penetration

The increasing penetration of inverter-based renewable energy sources has fundamentally altered the dynamic behavior of modern power systems by displacing conventional synchronous generation. Reduced system inertia, higher rates of change of frequency, modified fault responses, and complex voltage regulation have emerged as critical stability challenges in low-inertia grids. This paper presents a comprehensive study of power system stability under high renewable energy penetration through a structured literature review, a unified methodological framework, and a realistic transmission-level case study. The proposed framework integrates grid characterization, component and control modeling, multi-domain stability assessment, contingency analysis, and coordinated mitigation strategies using both phasor-domain and electromagnetic transient simulations. A three-zone network with varying levels of renewable integration is analyzed to quantify impacts on frequency, voltage, and small-signal stability following severe contingencies. Results demonstrate that stability degradation increases nonlinearly with renewable share in baseline grid-following configurations. The deployment of grid-forming inverter controls, synthetic inertia, and fast frequency response from battery energy storage significantly improves system performance by reducing RoCoF, restoring frequency nadir, and enhancing voltage recovery. Eigenvalue analysis further confirms improved damping of critical interaction modes. The findings highlight the necessity of hybrid control architectures and coordinated mitigation strategies to ensure reliable operation of future power systems with high renewable penetration.

The majority of published loss evaluation methods reflect on vertically-integrated systems where the generation, transmission and distribution facilities had been owned either by private regulated utilities or by public companies/ government agencies. Particular attention should be given where these vertically-integrated systems are “dis-integrated” into multiple businesses. Given the new era of low carbon electricity markets, it is imperative to address the concept of loss evaluation in a disintegrated market environment with high renewable energy penetration. Therefore, the paper contemplates the main available transformer loss evaluation methods, both, in vertically integrated and decentralized energy systems. In addition, it summarizes and benchmarks the current efforts to address the concept of loss evaluation in energy systems that are experiencing a high penetration of renewable energy sources.

Benefits of transmission switching and energy storage in power systems with high renewable energy penetration

Large‐scale renewable energy (RE) integration in the power systems is displacing conventional sources of generation, thus reducing the system's inherent inertia and primary frequency response (PFR) capabilities. This reduced response may decline the system's ability to stabilise frequency after inevitable events such as loss of generation or load and thus requires additional PFR. To meet the PFR requirements, fast‐acting resources like energy storage systems (ESS) and demand response (DR) (transferrable and interruptible loads) need to be integrated within the system. In this regard, a novel stochastic security‐constrained unit commitment framework is proposed to assess the potential of ESS and DR to ensure additional PFR requirements and handle post contingency frequency dynamics. Moreover, the proposed methodology analyses the impact of uncertain RE integration on system frequency dynamics using Bayesian inference statistics. Case studies are carried out on 39 bus New England and 118 bus IEEE test systems, incorporating post fault frequency security parameters. Simulation results analyse the PFR contribution of ESS and DR and indicate a substantial reduction in system operating cost and RE curtailment with their integration. The proposed analysis would help system operators to maintain required PFR under high RE penetration, and handle unavoidable contingencies.

Achieving high renewable energy penetrated power systems requires considerable operational flexibility to hedge the variability and uncertainty of variable renewable energy (VRE) generation. Compared with VRE sources, concentrating solar power (CSP) is an emerging controllable renewable generation technique that utilizes solar thermal power to generate electricity. The operational dispatchability of CSP would contribute to the power system transition toward high renewable penetration. In this paper, we explore how the generation portfolio will change toward high renewable energy penetrations, how much cost is involved, and what role CSP will play in realizing a high renewable energy penetrated power system. This study relies on a stochastic two-stage generation and transmission expansion planning model with CSP plants. The model captures the uncertainty and variability of renewable generation and the flexibility limits of thermal plants. With the target of achieving a renewable-dominated minimum-cost system with an expected renewable energy penetration level, the investments of both generation and transmission facilities are optimized. A case study on IEEE test systems with renewable technology cost data in 2050 is performed to analyze the value of CSP toward high renewable energy penetrated power systems.

With the rapid increase of renewable energy integration into power systems, its inherent volatility and intermittency pose significant challenges to frequency stability. Traditional Automatic Generation Control (AGC) units struggle to meet the frequency regulation demands of power systems with high renewable energy penetration, necessitating the coordinated participation of diverse resources in frequency regulation. This paper proposes a coordinated frequency control strategy for generation-grid-Ioad-storage systems. By leveraging minute-level power prediction and an opportunity-constrained optimization model, the strategy coordinates the output of thermal power, hydropower, energy storage, and adjustable loads to reduce frequency regulation costs while enhancing system stability. Case studies demonstrate that, under typical scenarios such as anti-peak regulation of wind power and load or in-phase fluctuations, the proposed strategy reduces frequency regulation costs by over 15% compared to conventional methods while meeting the CPS performance requirements. The study reveals the impact of energy storage dynamic efficiency on economic dispatch and provides insights for future research on multi-timescale coordinated control and intelligent algorithm optimization. This strategy offers an effective solution to the frequency stability challenges in power systems with high renewable energy penetration.

Increasing the share of intermittent renewable energy (RE) will challenge the capability of existing power systems to cope with increased variability in net load. This may result in frequent RE and load curtailment in the absence of adequate flexibility. To maximize RE utilization and maintain supply reliability, system flexibility must be enhanced. However, the capability of various flexibility resources to facilitate RE penetration needs to be assessed for optimal system planning. Further, to capture the impact of RE's seasonal variability, a longterm assessment of chronological short-term system operations is required. In this context, this paper proposes a computational framework of the yearly unit commitment model. An attempt has been made to maximize RE penetration at different integration levels by increasing operational flexibility and energy storage integration. Results from various cases examined on the IEEE RTS 24-bus system show that although enhanced operational flexibility is a viable solution for smooth RE integration, a high RE share would require alternative capital-intensive solutions.

As the adoption of renewable energy continues to grow in the building sector, the energy flexibility of air conditioning systems has become a key factor in achieving energy optimization and load shifting. This study systematically compares the performance of radiant and convective cooling systems in both continuous and intermittent operation modes, with a focus on their load shifting capabilities. A dynamic heat transfer model based on the state-space method was established to calculate load transfer indices and node temperature values for both systems under various operating conditions. The results indicate that, under intermittent cooling mode, the radiant cooling system exhibits superior load-shifting capability owing to the high thermal inertia of its radiant terminal and its distinct heat transfer pathway. It enables temporary cooling shutdowns while maintaining indoor thermal comfort for up to one hour, and effectively reshapes the cooling load profile by adjusting the chilled water supply schedule. This study offers a comprehensive comparison between radiant and convective systems, providing practical guidance for improving the adaptability of building cooling systems in future scenarios with high renewable energy penetration.

Facing ever-growing fossil energy crises and climatic and environmental issues, China pledges to the international community to peaking its carbon emissions by 2030 and achieving carbon neutrality by 2060. Hence, building a new power system with high renewable penetration is inevitable to decarbonizing China’s energy sector and achieving its great targets of carbon peaking and neutrality. Nevertheless, high renewable penetration into the grid will fundamentally alter the characteristics of the power system, featuring burgeoning uncertainty, diversified system operation, and complex stability control. On the foundation of this prospect, from the perspectives of safe and reliable system operation, economic operation, and system planning, this paper teases out potential challenges raised by high renewable penetration into the new power system, and explores the key sci-tech issues arising from high renewable penetration, such as power forecast, and system stability control, as well as market mechanism design and spatial-temporal energy balancing, with a view to providing method thoughts and theory support for future research.

With the rapid development of renewable energy, especially wind and solar power, the integration of high proportions of these resources into the power grid presents both opportunities and challenges for the electricity market. This paper focuses on optimizing the electricity spot market trading mechanism and peak-shaving compensation in the context of high renewable energy penetration. The variability and intermittency of renewable energy generation necessitate the development of a robust market design that ensures system stability, economic efficiency, and fair compensation for flexible resources. We propose a comprehensive optimization framework that incorporates the dynamic balancing of renewable generation and load demand, with particular emphasis on peak-shaving compensation for conventional thermal power plants. By using a hybrid model that combines market-based mechanisms with technical constraints such as storage and demand response, we aim to enhance the integration of renewable energy while maintaining grid reliability and minimizing costs. The study also examines the role of peak-shaving in mitigating the intermittency of renewable generation, ensuring balanced grid operation. Through theoretical analysis and simulation results, this paper demonstrates how the proposed market mechanism can improve the efficiency of renewable energy integration, reduce operational costs, and provide fair incentives for peak-shaving services, offering valuable insights for policymakers and market participants in designing future electricity market structures that are both sustainable and economically viable under high renewable energy penetration.

Renewable generations are one of the most significant measures to achieve the goal of carbon emission peak and carbon neutrality. However, high penetration renewable energy results in massive scenarios and pressures heavily on the operation of power systems, due to its randomness and intermittence. This paper proposes a data-driven scenario screening (DDSS) method to figure out crucial scenarios which may lead to insufficiency of peaking shaving and reserve contribution of power systems and release the heavy burden of massive scenarios. First of all, massive long-term operation scenarios including loads, network topologies, and outputs of conventional units and renewable generations are provided from the control centers of power grids or generated by Monte Carlo method. Three types of scenario screening rules are then summarized into Types A, B, and C. Types A, B, and C are all considered leading to insufficiency of peaking shaving and reserve contribution. Types A and B present scenarios with demand peak and demand valley respectively, while Type C presents scenarios with rapid rise/decline in demand. Each type consists of four detailed screening rules. Predetermined number of crucial scenarios can be obtained in descending order by each rule. Furthermore, a flow is illustrated for subtle scenario screening. The number of crucial scenarios will be double, once potential operating risks such as wind/solar power limitation and load shedding are found. The scenario screening comes to an end if and only if no more potential operating risk exists. Finally, crucial scenarios are verified by calculating a series of evaluation indexes such as renewable energy penetration, unit ramp rate, and wind/solar power limitation. Case studies are implemented on a provincial power grid of the China Southern Power Grid to validate the efficiency of scenario screening method.

The high-quality development of the Yellow River Basin and the strategies of peaking carbon dioxide emissions and achieving carbon neutrality are of great significance to the great rejuvenation of the Chinese nation and the sustainable development, and are major strategic decisions made by the Central Committee of the Communist Party of China after careful consideration. Gansu Province deeply implements Xi Jinping's ecological civilization ideology, adheres to the organic integration of the goals of peaking carbon dioxide emissions and achieving carbon neutrality with the strategy of high-quality development of the Yellow River Basin, in order to ensure that the Gansu section of the Yellow River Basin achieves the "dual carbon" goals as scheduled. Based on data from the "Statistical Yearbook of Gansu Province", this article analyzes the economic development, carbon emissions, and high-quality development of the Yellow River Basin in Gansu Province. It is concluded that from 2009 to 2021, the gross domestic product, total carbon emissions, and per capita carbon emissions in Gansu Province showed an overall fluctuating upward trend, while the carbon emission intensity showed a downward trend year by year. In combination with the actual situation in Gansu Province, achieving the "dual carbon" goals in the Gansu section of the Yellow River Basin will help promote the process of ecological civilization construction, build a clean, low-carbon, safe, and efficient energy system, promote energy consumption revolution, facilitate the upgrading and transformation of traditional industries, drive the construction of beautiful rural areas, and achieve the six aspects of significance for the people to live a better life.

Carbon-peaking pilots are instrumental in achieving China’s goal of peaking carbon dioxide (CO2) emissions before 2030, and they can serve as a model for different regions that are trying to explore effective ways to reach carbon peak and carbon neutrality (the “dual carbon” goals). This paper reviews the history of China’s low-carbon pilots, studies and analyzes the status of the first batch of pilot cities and industrial parks, launched in 2023, and identifies four challenges facing the execution: (i) limited local resources in some regions for promoting zero- or low-carbon energy; (ii) difficulties faced by some regions in accessing external resources for promoting zero- or low-carbon energy; (iii) the need for breakthroughs in pilot system and mechanism reforms; (iv) the need for better data and stronger capability. Finally, this paper puts forward several suggestions for how pilot administrators can improve performance: (i) keeping abreast with the national reform and the latest policy trends; (ii) enhancing energy conservation and improving energy efficiency; (iii) creating new business models for developing and utilizing renewable energy; (iv) optimizing integration with market instruments such as green finance; (v) building basic capabilities using digital and intelligent tools.

To establish a pathway consistent with future development of a green, low-carbon, and environmentally friendly economy in Shaoxing, from the perspective of the synergistic effect of carbon-pollutant, this study evaluates the current performances of pollution reduction and carbon mitigation in Shaoxing based on carbon-pollution synergy and also analyzes the synergy effects and the driving factors of carbon and pollutant emissions, aiming to provide a reference for carbon peaking and synergistic carbon-pollutant emission reductions. The results indicated that during the 13th Five-Year Plan period, Shaoxing demonstrated strong synergy in carbon and pollution reduction efforts. The city has enhanced its energy-related carbon emission efficiency and gradually increased the decoupling level between carbon emissions and economic growth. The driving factors and their contributions to both carbon and atmospheric pollutant emissions were largely similar: Economic growth and population size contributed to emission increase, while carbon-pollutant emission efficiency and energy intensity effects contributed to emission reductions. Based on this and considering the current development model and future plans of the city, different carbon emission scenarios were set using the LEAP model. Under the baseline scenario, Shaoxing is expected to reach its carbon peak by 2030, while under a high-energy scenario, peaking may be delayed until 2035. However, with the implementation of more stringent carbon reduction policies, it is possible to achieve an earlier peak. The promotion of strong low-carbon policies, accelerated adjustments to energy and industrial structures, increased investment in low-carbon and renewable energy technologies, and improvements in energy efficiency can effectively facilitate the pursuit of synergistic carbon and pollution reduction in Shaoxing, thus accelerating the implementation of its dual-carbon strategy.

Due to its reduced communication overhead and robustness to failures,\ndistributed energy management is of paramount importance in smart grids,\nespecially in microgrids, which feature distributed generation (DG) and\ndistributed storage (DS). Distributed economic dispatch for a microgrid with\nhigh renewable energy penetration and demand-side management operating in\ngrid-connected mode is considered in this paper. To address the intrinsically\nstochastic availability of renewable energy sources (RES), a novel power\nscheduling approach is introduced. The approach involves the actual renewable\nenergy as well as the energy traded with the main grid, so that the\nsupply-demand balance is maintained. The optimal scheduling strategy minimizes\nthe microgrid net cost, which includes DG and DS costs, utility of dispatchable\nloads, and worst-case transaction cost stemming from the uncertainty in RES.\nLeveraging the dual decomposition, the optimization problem formulated is\nsolved in a distributed fashion by the local controllers of DG, DS, and\ndispatchable loads. Numerical results are reported to corroborate the\neffectiveness of the novel approach.\n