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Operational flexibility is required in power systems to mitigate load-generation imbalances. Inflexibility either results in infeasible scheduling or shift resources from their economic operating point. System operators must estimate flexibility requirement, assess its availability from committed resources, and take corrective measures to handle upcoming inflexibility events. Various metrics are integrated with economic dispatch to quantify different facets of flexibility — ramp, power, and energy. Consideration of all three facets is essential for its adequate assessment, but is often neglected in literature and requires an in-depth investigation. Further, existing literature hardly consider resources' day-ahead scheduling decisions while evaluating flexibility for real-time operations. This results in erratic assessment of available flexibility. In this context, the paper proposes a comprehensive metric to quantify flexibility in terms of ramp, power, and energy insufficiency by simultaneously considering their system-wide requirement and availability. A Resource Flexibility Index based on operating range and ramping capability of resources is proposed for accurate indication of available flexibility. The proposed metric is integrated with real-time stochastic multi-interval scheduling framework that considers day-ahead operational constraints. Netload forecast and associated uncertainty are characterized using Long Short-Term Memory and Markov Chain Monte Carlo techniques. Results highlight that the flexibility index is proportional to system's netload variability handling capability and average inflexibility can be reduced up to 97% with the utilization of emerging resources and ramp products. The proposed tools are of value to power system planners and operators to manage netload intermittency. • Flexibility quantification considering system-wide requirement and its availability. • Resource Flexibility Index based on operating range and ramping. • Machine-learning based methods to forecast netload and generate scenarios. • Multi-interval scheduling to dispatch resources and integrate flexibility metric. • Integrating flexible resources and ramp products reduce inflexibility. [ABSTRACT FROM AUTHOR]

To reach the "30·60" decarbonization target (where carbon emissions start declining in 2030 and reach net zero in 2060), China is restructuring its power system to a new energy-based one. Given this new situation, this paper reviews previous studies on the power market and highlights key issues for future research as we seek to adapt to the new power system (NPS). Based on a systematic literature review, papers on the operational efficiency of the power market, participants' bidding strategies and market supervision were identified. In a further step, papers with high relevance were analyzed in more detail. Then, key studies that focused on market trading under China's new power system were picked out for further discussion. New studies were searched for that pertained to new energy mechanisms and bidding, the transition from coal-fired power, flexible resources and the technical applications of simulations. The quantitative analysis supports the construction of a basic paradigm for the study of power markets that is suitable for the new power system. Finally, the theoretical basis and application suggestions for power market simulations are introduced. This study summarized the existing research on the power market and further explored the key issues relating to the power market as it adapts to the NPS, hoping to inspire better research into China's power sector, and promote safe, low-carbon, and sustainable development in China's power industry. [ABSTRACT FROM AUTHOR]

• Introducing a new linear mathematical programming model for IPPSS problem. • Presenting a novel mixed uncertainty solution approach for IPPSS problem. • Proposing IPPSS problem by regarding flexible resources within activities scheduling. • Considering project activities in multi-modes with different resource requirements. • Offering flexible delivery time for project portfolio selection and scheduling. Resource management plays a pivotal role in project implementation success. The profitability of project-based companies not only relies on the right selection of project portfolio but also depends on accurate scheduling and resource management. This issue is addressed by optimal project portfolio selection and scheduling using flexible resource availability and projects' due date. The motivation of flexible resources is to maximize cash flow by resource management and adding more projects to a portfolio by reinvesting the gain to increase resource availability during planning horizon. Flexible due date leads to perform more projects besides increasing the robustness of multiple projects. This study proposes a new linear structure of mixed-integer programming (MIP) model of project portfolio selection and scheduling considering the resource management, cash flow, tardiness cost, and robustness of multiple projects. Moreover, to a better description of real-life project situations, a new solution approach is introduced based on triangular interval-valued fuzzy random variables to incorporate both fuzziness and randomness uncertainties into mathematical programming models. To solve the proposed interval-valued fuzzy random model, a generalized credibility-based chance constraint measure is applied. The application and performance of proposed model are evaluated through different small to large-sized test problems and a real case study to tackle uncertainties and complexities explicitly. [ABSTRACT FROM AUTHOR]

Using Electric Vehicles (EV) as Flexible Resources (FR) to increase surplus Photovoltaic (PV) power utilisation is a well-researched topic. Our previous study showed that EVs are viable as supplementary FRs in large capacity PV power systems, where EVs are likely to gather (i.e., workplaces). However, that study assumed all EVs to have identical arrival and departure times (availability), and battery capacities. As these characteristics may vary between EVs and affect their performance as FRs, this study expands the modelling of EVs to consider a variety of availabilities and battery capacities. To effectively utilise a variety of EVs as FRs, an Optimisation Electric-load Dispatching model is used to formulate priority schemes for charging and discharging the EVs based on their potential to contribute to the power system. The priority schemes are evaluated by simulating the annual operation of the power system both with and without the priority schemes, and comparing results. The power system is simulated using a Unit-Scheduling and Time-series Electric-load Dispatching model. The priority schemes reduced annual CO2 emissions by nearly 1%, compared to the case without the priority schemes. The performances of different EVs as FRs when the priority schemes are used and not used are also analysed. [ABSTRACT FROM AUTHOR]

• A robust optimization model is proposed to handle economic dispatch problems with uncertainties. • An improved distributed approach with self-adaptive step-size and a polynomial filter is proposed. • It has faster convergence performances and robustness to random communication failures. Power systems are confronted with prodigious challenges of scheduling and operation incurred by the high penetration of distributed renewable energy with intermittency and uncertainty. Therefore, this paper proposes an improved distributed robust optimization approach with self-adaptive step-sizes based on the line search method and a polynomial filter, to minimize the overall costs of flexible resources including conventional generators, energy storage systems, renewable energy curtailments, deferrable loads and tie-line power exchanges, while considering various constraints, such as supply-demand power balance, line congestion constraints and power output limits. Numerical case studies conducted in a modified IEEE 14-bus system and a modified IEEE 118-bus system demonstrate the reliability, robustness and extensibility of the proposed approach. In addition, the effectiveness and accuracy of the proposed distributed robust optimization approach are validated through comparisons with the traditional centralized gradient method and the convergence performance is better in contrast to other distributed optimization algorithm. [ABSTRACT FROM AUTHOR]

• Recent developments have led to an increase in power system flexible resources. • The use of such resources can meaningfully improve power systems voltage stability. • A novel distributed area-based voltage stability index is proposed. • Development of a direct perspective for flexible resources dispatch. • Prevention of early saturation in the improvement of voltage stability margin. Voltage stability margins of modernbulk power systems are significantly affected by renewable energy sources (RESs). The intermittency of these units can constantly move the critical location driving the system to voltage collapse along different coherence regions. Traditional approaches were not designed to deal with this scenario, typically providing a centralized actuation based on a system-wide perspective. In this sense, this paper proposes a novel area-based outlook to take advantage of the new possibilities enabled by power systems distributed controllable resources, e.g. flexible resources, to tackle this critical operational challenge. For this sake, a novel area-based sensitivity index, exploring both the network-wide sensitivity and the local characteristics of voltage collapse is proposed to determine the most effective buses for voltage support and their respective capability of increasing the system's load margin. Comparative case studies indicate the superior capability of the proposed direct method to deal with the new perspectives of modern power systems. [ABSTRACT FROM AUTHOR]

The volatility and uncertainty of high-penetration renewable energy (RE) challenge the stability of the power system. To tackle this challenge, an optimal dispatch of high-penetration RE based on flexible resources (FRs) is proposed to enhance the ability of the power system to cope with uncertain disturbances. Firstly, the flexibility of a high-penetration RE integrated power system is analyzed. The flexibility margin of power supply and flexible adaptability of RE are then introduced as the evaluation indices for optimal operation. Finally, a multi-objective optimal dispatch model for power system flexibility enhancement based on FRs under the constraint of flexibility indices is proposed. The simulation results show that the proposed optimal dispatch can effectively enhance the flexibility of the power system and the penetration of RE and reduce pollutant emissions. Compared with the conventional method, the daily average emissions of CO2, SO2, and NOx with the proposed method are reduced by about 83,600 kg, 870 kg, and 370 kg, respectively, the maximum allowable volatility of net load is increased by 7.63%, and the average volatility of net load is reduced by 2.67%. [ABSTRACT FROM AUTHOR]

The serious problem of climate change has led the energy sector to modify its generation resources from fuel-based power plants to environmentally friendly renewable resources. However, these green resources are highly intermittent due to weather dependency and they produce increased risks of stability issues in power systems. The deployment of different flexible resources can help the system to become more resilient and secure against uncertainties caused by renewables. Flexible resources can be located at different levels in power systems like, for example, at the transmission-level (TSO), distribution-level (DSO) and customer-level. Each of these levels may have different structures of flexibility trading as well. This paper conducts a comprehensive review from the recent research related to flexible resources at various system levels in smart grids and assesses the trading structures of these resources. Finally, it analyzes the application of a newly emerged ICT technology, blockchain, in the context of flexibility trading. [ABSTRACT FROM AUTHOR]

In recent years, the ever-increasing charging demand of electric vehicles (EVs) imposes challenges on both power supply security and reliability in the distribution system. In this paper, an EV accommodation capability evaluation model of a distribution system, with high penetrations of flexible resources, is established. Firstly, according to the actual classifications of EVs and transportation rules, a Monte Carlo simulation is used to simulate the charging behaviors of EVs so as to obtain the relevant parameters of EV charging. Then, a coordinated charging optimization model for various types of EVs is proposed based on the charging characteristics of EVs. The presented model comprises a mixed-integer linear programming problem and a constrained optimization problem which are respectively solved by CPLEX (the Simplex method implemented in the °C programming language) and the particle swarm optimization (PSO) algorithm. Last of all, a real-life distribution system in the coastal areas of China is served for demonstrating the feasibility and efficiency of the proposed approach. Moreover, the impacts of flexible resources, distribution network zoning rules, and EV growth on the EV accommodation capability of a distribution system are also discussed. [ABSTRACT FROM AUTHOR]

A transition to a sustainable energy system is essential. In this context, smart grids represent the future of power systems for efficiently integrating renewable energy sources and active consumer participation. Recently, different studies were performed that defined the conceptual architecture of power systems and their agents. However, these conceptual architectures do not overcome all issues for the development of new electricity markets. Thus, a novel conceptual architecture is proposed. The transactions of energy, operation services, and economic flows among the agents proposed are carefully analysed. In this regard, the results allow setting their activities' boundaries and state their relationships with electricity markets. The suitability of implementing local electricity markets is studied to enforce competition among distributed energy resources by unlocking all the potential that active consumers have. The proposed architecture is designed to offer flexibility and efficiency to the system thanks to a clearly defined way for the exploitation of flexible resources and distributed generation. This upgraded architecture hereby proposed establishes the characteristics of each agent in the forthcoming markets and studies to overcome the barriers to the large deployment of renewable energy sources. [ABSTRACT FROM AUTHOR]