Review of Research on System Thermal Inertia Modelling and Optimal Scheduling from the Perspective of Flexible Resources

The thermal inertia of the existing heating system is often considered an adverse factor, which will affect the operation of the system. However, under the perspective of resource flexibility, the thermal inertia of the system can effectively increase the flexibility of the system operation, significantly reduce the energy consumption and enhance the ability of energy supply and demand balance, and enhance the new energy integration, such as the wind power. Based on the flexible resources, it focuses on the study of the thermal inertia of the “network side” heating pipe network of the system and the optimal scheduling of the heating system. Combined with the thermal inertia of the pipe network, the operation characteristics of the power/heat output of the gas-steam combined cycle unit were analysed theoretically. On this basis, the optimal scheduling model of the system was established. Taking the energy supply system of an industrial park as an example, the model was verified to achieve a more stable power output effect of the unit.

Key Issues and Technical Applications in the Study of Power Markets as the System Adapts to the New Power System in China

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.

Proposal of Priority Schemes for Controlling Electric Vehicle Charging and Discharging in a Workplace Power System with High Penetration of Photovoltaic Systems

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.

Wheel of Wellbeing (WoW) health promotion program: Australian participants report on their experiences and impacts

Background Community-based mental health promotion programs focus on improving individual and community wellbeing by strengthening resilience and building capacity to support positive health outcomes. The Wheel of Wellbeing (WoW) is an example of such a program, promoting activities that support social engagement and positive emotions within a holistic framework underpinned by positive psychology. WoW is intended to be flexibly implemented in each community, training community members who implement behaviour change activities in their local community, workplace and educational settings. Method This study aimed to understand the opinions and experiences of a sample of individuals who had participated in a range of WoW training programs; documenting the impact on participant behaviours and professional practices, and how the WoW framework was subsequently employed within their communities. Using Ripple Effects Mapping evaluation processes to guide a focus group, nine WoW training participants collectively reflected on the program impacts, generating consensus themes and a mind map. Mind map qualitative data were entered into XMIND mapping software and reviewed with the focus group transcription and field notes. Results Thematic analysis identified three themes: increased community involvement and engagement (strengthening community connections); improved health, emotions and behaviour (motivating change to health behaviours); and flexible resources which could be utilised in a range of settings (easily incorporated in the existing organisational cultures). Conclusions The results of this study support the premise that the WoW framework can be an effective framework for guiding wellbeing promotion activities, with participants championing a ‘ripple effect’ across individual, family, friendship, professional and community networks.

Multi-Level Cooperative Scheduling Based on Robust Optimization Considering Flexibilities and Uncertainties of ADN and MG

This paper develops the coordination structure and method for utilizing flexibilities in a Micro-Grid (MG), an Active Distribution Network (ADN) and a Transmission Grid (TG), which can play an essential role in addressing the uncertainties caused by renewable energy power generation (REPG). For cooperative dispatching, both flexibilities and uncertainties on the interface of MG–ADN and ADN–TG are portrayed in unified forms utilizing robust optimization (RO), based on the modified equipment-level model of flexible resources. The Constraint-and-Column Generation method is adopted to solve the RO control problems. Simulations on the modified IEEE case-6 and case-33 systems are carried out. The results suggest that the proposed algorithm can exploit flexible resources in both an MG and an ADN, improving the economy and promoting REPG consumption within each level (MG, ADN and TG) while reducing uncertainties and providing flexibilities for superior operators.

A Probabilistic and Value-Based Planning Approach to Assess the Competitiveness between Gas-Fired and Renewables in Hydro-Dominated Systems: A Brazilian Case Study

The main challenge with the penetration of variable renewable energy (VRE) in thermal-dominated systems has been the increase in the need for operating reserves, relying on dispatchable and flexible resources. In the case of hydro-dominated systems, the cost-effective flexibility provided by hydro-plants facilitates the penetration of VRE, but the compounded production variability of these resources challenges the integration of baseload gas-fired plants. The Brazilian power system illustrates this situation, in which the development of large associated gas fields economically depends on the operation of gas-fired plants. Given the current competitiveness of VRE, a natural question is the economic value and tradeoffs for expanding the system opting between baseload gas-fired generation and VRE in an already flexible hydropower system. This paper presents a methodology based on a multi-stage and stochastic capacity expansion model to estimate the optimal mix of baseload thermal power plants and VRE additions considering their contributions for security of supply, which includes peak, energy, and operating reserves, which are endogenously defined in a time-varying and sized in a dynamic way as well as adequacy constraints. The presented model calculates the optimal decision plan, allowing for the estimation of the economical tradeoffs between baseload gas and VRE supply considering their value for the required services to the system. This allows for a comparison between the integration costs of these technologies on the same basis, thus helping policymakers and system planners to better decide on the best way to integrate the gas resources in an electricity industry increasingly renewable. A case study based on a real industrial application is presented for the Brazilian power system.

A Renewable Energy Community of DC Nanogrids for Providing Balancing Services

The massive expansion of Distributed Energy Resources and schedulable loads have forced a variation of generation, transmission, and final usage of electricity towards the paradigm of Smart Communities microgrids and of Renewable Energy Communities. In the paper, the use of multiple DC microgrids for residential applications, i.e., the nanogrids, in order to compose and create a renewable energy community, is hypothesized. The DC Bus Signaling distributed control strategy for the power management of each individual nanogrid is applied to satisfy the power flow requests sent from an aggregator. It is important to underline that this is an adaptive control strategy, i.e., it is used when the nanogrid provides a service to the aggregator and when not. In addition, the value of the DC bus voltage of each nanogrid is communicated to the aggregator. In this way, the aggregator is aware of the regulation capacity that each nanogrid can provide and which flexible resources are used to provide this capacity. The effectiveness of the proposed control strategy is demonstrated via numerical experiments. The energy community considered in the paper consists of five nanogrids, interfaced to a common ML-LV substation. The nanogrids, equipped with a photovoltaic plant and a set of lithium-ion batteries, participate in the balancing service depending on its local generation and storage capacity.