Tri-level Framework Research Articles

A novel strong duality-based reformulation for trilevel infrastructure models in energy systems development

We explore the class of trilevel equilibrium problems with a focus on energy-environmental applications and present a novel single-level reformulation for such problems, based on strong duality. To the best of our knowledge, only one alternative single-level reformulation for trilevel problems exists. This reformulation uses a representation of the bottom-level solution set, whereas we propose a reformulation based on strong duality. Our novel reformulation is compared to this existing formulation, discussing both model sizes and computational performance. In particular, we apply this trilevel framework to a power market model, exploring the possibilities of an international policymaker in reducing emissions of the system. Using the proposed approach, we are able to obtain globally optimal solutions for a five-node case study representing the Nordic countries and assess the impact of a carbon tax on the electricity production portfolio.

“You're only a receptionist, what do you want to know for?”: Street-level bureaucracy on the front line of primary care in the United Kingdom

IntroductionIn care settings across the globe non-clinical staff are involved in filtering patients to the most appropriate source of care. This includes primary care where general practice receptionists are key in facilitating access to individual surgeries and the wider National Health Service. Despite the complexity and significance of their role little is known of how the decision-making behaviors of receptionists impact policy implementation and service delivery. By combining the agent-based implementation theory of street-level bureaucracy with a tri-level analytical framework this work acknowledges the impact of the decisions made by receptionists as street-level bureaucrats and demonstrates the benefits of using the novel framework to provide practical insight of the factors influencing those decisions. MethodsA secondary analysis of qualitative data gathered from a series of semi-structured interviews conducted with 19 receptionists in the United Kingdom in 2019 was used to populate a tri-level framework: the micro-level relates to influences on decision making acting at an individual level, the meso-level influences at group and organizational levels, and the macro–level influences at a societal or policy level. ResultsAt the micro-level we determined how receptionists are influenced by the level of rapport developed with patients and would use common sense to interpret urgency. At the meso-level, influences included their position at the forefront of premises, the culture of the workplace, and the processes and protocols used by their practice. At the macro-level, participants described the impact of limited health service capacity, the lack of mandatory training, and the growth in the use of digital technologies. ConclusionsStreet-level bureaucracy, complemented with a tri-level contextual analysis, is a useful theoretical framework to understand how health workers, such as receptionists, attempt to provide universality without sufficient resource, and could potentially be applied to other kinds of public service workers in this way. This theoretical framework also benefits from being an accessible foundation on which to base practice and policy changes.

A tri-level framework for distribution-level market clearing considering strategic participation of electrical vehicles and interactions with wholesale market

With the increasing penetration of distributed renewable energy sources in distribution networks, a large number of independent market entities such as load serving entities will participate in the distribution-level market, which provides a platform for transparent energy transactions among them. This paper proposes a novel tri-level optimization model for distribution system operator market clearing, fully considering the strategic participation of electrical vehicles and the interactions with the transmission system operator in the market environment. The upper-level model addresses the bidding strategy problem of charging stations and the randomness of renewable energy sources, the middle-level model performs the distribution-level market clearing, and the lower-level model focuses on the joint optimization of power and reserve for transmission network. Furthermore, the Stackelberg game model between distribution system operator and each charging station is converted into a mathematical program with equilibrium constraints formulation, and a decentralized approach based on analytical target cascading algorithm is developed to realize the decoupling of distribution and transmission network. The simulation results show that the proposed distribution-level market clearing method can alleviate the congestion in transmission network and enhance the economic benefits of load serving entities in distribution network.

Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

Identification of in situ concrete characteristic strength (CCS) of deteriorating RC structures directly affects their rehabilitation. Contemporary practices lack the ability to yield CCS or at most produce an unrealistic estimate, because: (i) core tests are few due to technical and economic constraints and their positioning is random, inducing bias in the strength estimate, (ii) non-destructive tests (NDT) are themselves not good estimators of project specific strength, (iii) tests are only local indicators and most practising engineers are unaware of how to process the spatial variability. This paper overcomes these limitations with a novel and implementable framework, for an asset manager to make scientific estimates of CCS. This is a tri-level framework: (1) NDT are performed to capture the spatial variability of the investigated concrete; (2) core extractions are guided by the prior NDT information, to avoid bias in test location selection; (3) NDT and coring results are fused via Bayesian NDT test calibration and updating of the probability distribution of the concrete strength. The proposed framework is successfully implemented for the assessment and rehabilitation of a critical hospital complex in India.

Enhancement of loadability and voltage stability in grid-connected microgrid network

– The implementation of demand response programs in microgrid network applications enables end-consumers to participate in active load shaping, peak shaving, and supply-demand balancing activities. However, the impact of demand response programs on microgrid performance subjected to renewable energy intermittency, network flow constraints, loadability, and voltage stability is not acknowledged to the full extent. To cover this research gap, a tri-level stochastic framework is proposed to enhance the grid-connected microgrid performance in terms of loadability, voltage stability, and optimal scheduling. At the first level, a stochastic scenario-based approach deals with the intermittency of renewable sources. The interdependency of loading level on voltage profile is investigated in level two, implementing utility-oriented and customer-oriented demand-side management schemes. Unlike most previous research, flexible price elasticity-based incentive-driven and price-driven demand response programs are implemented to shape the load demand. Moreover, four distinct seasonal load profiles were considered: summer, winter, spring, and fall. Finally, the recently reported nature-inspired Harris Hawk Optimizer is incorporated in level three to optimize the costs and enhancement of microgrid loadability. The enhanced version of the IEEE 69 bus radial distribution network has been implemented and analyzed to demonstrate the effectiveness of the proposed tri-level framework. The obtained simulation results show that the voltage profile is enhanced by 6.58%, and microgrid loadability is improved by 34.64%. The significance of the proposed work to attain sustainable development goals and various practical insights for the benefit of multi-stakeholder is also discussed.

Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework

This paper addresses the dilemma of coordination among three kinds of stakeholders, namely, the smart distribution networks, microgrids, and customers with demand response resources under a comprehensive trilevel framework. The interaction among these stakeholders, which are regarded as subjects of individual interest, leads to a complex energy generation, storage, transaction, and consumption problem. Based on the assumption that the customers always provide the best response to the signals of leaders, the trilevel problem is transformed into a bilevel problem by replacing the lowest level problem with its optimality conditions. Next, two coordination schemes are formulated to analyze the interactions between the smart distribution network and microgrids with demand response resources. The first scheme is a full cooperative coordination framework, in which the smart distribution network and microgrids jointly activate the resources located under the distribution networks. The second scheme is an ancillary service framework in the sense that the smart distribution network acts as a service subject to balance the supply and demand of the networks, and charges the management fee for transmission service. This scheme can achieve rapid convergence in a distributed manner, expose little information, and protect the privacy of the selfish participants. For each coordination scheme, a detailed mathematical model and solution method are formed. Illustrative examples highlight the feasibility and applicability of the schemes and provide references for the government in making decision with respect to the problems of coordination among the smart distribution networks, microgrids, and customers.

Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data

Considering the volatility and synergies of renewable energy sources, sufficient resource assessment is of great significance for investors and planners to reduce power fluctuations, increase integration capacity, and improve economic and social benefits. This paper proposes a tri-level framework to evaluate and visualize the spatiotemporal characteristics of regional wind and solar energy resources from the perspective of data mining. Furthermore, a free, open-source software package named Quantitative Synergy Assessment Toolbox for renewable energy sources (QSAT V1.0) has been developed with Python and hosted on GitHub, which is a useful tool for the resources assessment and preliminary regional synergetic planning. In the first level, the long-term reanalysis meteorological data of wind speed, solar irradiation and ambient temperature are acquired from MERRA, processed via virtual generation systems, and corrected by in-situ measured data. For the progressive two levels of single-site and wide-area data assessments, the data mining methods incorporating attribute construction, principal components analysis and k-means clustering are used to reduce the dimensionality and capture the temporal and spatial synergy patterns. According to the extracted patterns, the rational combinations of sub-regions can be selected as candidates to make full use of the synergies. Shandong province in China is taken as a demonstration to quantify and analyze the complementarities of solar and wind resources. The proposed method and tools can help enhance the planning of renewable energy sources.

Reliability-Constrained Robust Power System Expansion Planning

This paper presents a tri-level reliability-constrained robust power system expansion planning (SEP) framework modeling the uncertainty of electricity demand, wind power generation, and availability of units and lines. In the proposed tri-level SEP model, electricity demand and wind power generation being continuous uncertain variables are modeled by bounded intervals and availability of units and lines being discrete uncertain variables are modeled by probability distributions. Simulation results on the Garver 6-bus, the IEEE 24-bus, and the IEEE 73-bus test systems confirm the effectiveness of the proposed tri-level framework to cope with multi-fold planning uncertainties.

Interpersonal Relationships, Motivation, Engagement, and Achievement: Yields for Theory, Current Issues, and Educational Practice

In this review, we scope the role of interpersonal relationships in students’ academic motivation, engagement, and achievement. We argue that achievement motivation theory, current issues, and educational practice can be conceptualized in relational terms. Influential theorizing, including attribution theory, expectancy-value theory, goal theory, self-determination theory, self-efficacy theory, and self-worth motivation theory, is reviewed in the context of the role of significant others in young people’s academic lives. Implications for educational practice are examined in the light of these theoretical perspectives and their component constructs and mechanisms. A trilevel framework is proposed as an integrative and relationally based response to enhance students’ motivation, engagement, and achievement. This framework encompasses student-level action (universal programs and intervention, targeted programs for at-risk populations, extracurricular activity, cooperative learning, and mentoring), teacher- and classroom-level action (connective instruction, professional development, teacher retention, teacher training, and classroom composition), and school-level action (school as community and effective leadership).