Search results

Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.

First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientificity and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.

Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.

Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.

The highlights of the paper are as follows:

1. A new seasonal grey buffer operator is constructed.

2. The impact of shock perturbations on seasonal data trends is effectively mitigated.

3. A novel seasonal grey forecasting approach with multi-method fusion is proposed.

4. Seasonal electricity consumption is successfully predicted by the novel approach.

5. The way to adjust China's power system flexibility in the future is analyzed.

A new seasonal grey buffer operator is constructed.

The impact of shock perturbations on seasonal data trends is effectively mitigated.

A novel seasonal grey forecasting approach with multi-method fusion is proposed.

Seasonal electricity consumption is successfully predicted by the novel approach.

The way to adjust China's power system flexibility in the future is analyzed.

This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.

With daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.

The empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.

The MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

The purpose of this paper is to explore the interplay between firm boundary decisions and the management of both efficiency and flexibility and the implications this has for modular design in the provision of advanced services.

A single case study in the defence industry employs semi-structured interviews supplemented by secondary data. Data are analysed using thematic analysis.

The findings provide a process model of boundary negotiations for the design of efficient and flexible modular systems consisting of three phases; boundary ambiguity, boundary defences and boundary alignment.

The study provides a process framework for boundary negotiations to help organisations navigate the management of both-and efficiency and flexibility in the provision of advanced services.

Drawing upon modularity, paradox and systems theory, this article provides novel theoretical insight into the relationship between firm boundary decisions and the management of both-and efficiency vs. flexibility in the provision of product upgrade services.

Automated warehouse equipment is often regarded as being inflexible, and yet its use continues to rise even though markets are becoming increasingly volatile. The purpose of this paper is to explore the reasons for, and nature of, warehouse automation implementations in order to further this understanding.

The research is based on semi‐structured interviews with some of the key stakeholders in automation projects. This is followed by a survey questionnaire to widen the findings.

The research indicates that the main reason for automation is to accommodate growth, with cost reduction and service improvement also being important. The implementation process tends to be complex and lengthy, although most projects are controlled within the planned budget and timescale. There is, however, a real risk of disruption and service level failings during the operational start‐up of these projects, as well as some concerns about ongoing flexibility.

The findings provide a useful insight into these areas but further research is required to explore the key characteristics of successful implementations and to understand how warehouse automation can be designed to provide responsiveness to rapidly changing market conditions.

The findings have important implications as regards the need to incorporate scenario planning into the design process and to plan for the management of the ongoing operation.

There has been relatively little previous research into this important area, which involves a substantial proportion of the capital budget of many supply chains. The above findings are of value to academics and practitioners.

The purpose of this paper is to standardised four-step flexibility assessment methodology for evaluating the available electrical load reduction or increase a building can provide in response to a signal from an aggregator or grid operator.

The four steps in the methodology consist of Step 1: systems, loads, storage and generation identification; Step 2: flexibility characterisation; Step 3: scenario modelling; and Step 4: key performance indicator (KPI) label.

A detailed case study for one building, validated through on-site experiments, verified the feasibility and accuracy of the approach.

The results were benchmarked against available demonstration studies but could benefit from the future development of standardised benchmarks.

The ease of implementation enables building operators to quickly and cost effectively evaluate the flexibility of their building. By clearly defining the flexibility range, the KPI label enables contract negotiation between stakeholders for demand side services. It may also be applicable as a smart readiness indicator.

The novel KPI label has the capability to operationalise the concept of building flexibility to a wider spectrum of society, enabling smart grid demand response roll-out to residential and small commercial customers.

This paper fulfils an identified need for an early stage flexibility assessment which explicitly includes source selection that can be implemented in an offline manner without the need for extensive real-time data acquisition, ICT platforms or additional metre and sensor installations.

The Nature of Business Policy Business policy — or general management — is concerned with the following six major functions:

Business research and development (R&D) is of critical importance for innovation and economic growth. The purpose of this study is to present an application of the analytic hierarchy process (AHP) to select the most appropriate policy measure to support the business expenditure on R&D (BERD).

AHP method adopts a multi-criteria approach that can be used to analyse and prioritize the policy measures based on pairwise comparisons between several attributes that affect the selection of a policy tool. The model formulated in this study is applied to a real case of supporting decision-makers in some high-tech sectors in Iran.

The results highlight the four main financial policy measures implemented in Iran to enhance the BERD; those are, public procurement for R&D, direct subsidies for R&D, grants for R&D and income tax credit for firms have the priority values of 0.280, 0.260, 0.249 and 0.211, respectively.

The findings of this study are based on subjective evaluation of policy measures by experts of designing policy measures. Objective assessment of policy measures is important too because the preferences of policy interventions change during the time. Another significant point is that the priorities of specific policy measures depend on the effectiveness of their implementing arrangement and the previously successful experience of firms in receiving them.

This paper presents an application of the AHP to select the most appropriate policy measure to support the BERD. This method could be used to prioritize the policies and interventions that governments implement to solve different problems, especially at the innovation system level.

Teams focus on a common and valued goal, and effective teams are able to alter their behaviors in pursuit of this goal. When teams are viewed in the context of a dynamic environment, they must adapt to challenges in the environment in order to maintain team effectiveness. In this light, we describe various sources of team variation and how they combine with individual-level, team-level, and dynamical mechanisms for maintaining team effectiveness in a dynamic environment. The combination of these elements produces a systems view of team effectiveness. Our goals are to begin to define, both in words and in operational terms, team effectiveness from this perspective and to evaluate this definition in the context of team training using intelligent tutoring systems (team ITS). In addressing these goals, we present an example of real-time analysis of team effectiveness and some challenges for team ITS training based on a dynamical systems view of team effectiveness.

Those economists who emphasise the short‐run analysis and its effects tend to value distributive equity more than productive efficiency, full employment more than price stability, fiscal policy more than monetary policy and collective necessity more than individual freedom. Those stressing the long‐run tend to believe in the opposite way. Any emphasis on one particular time frame, however, represents at best a partial and biased analysis of the whole economic reality and at worst a distortion of it. It would be necessary, therefore, in economic theory and policy, for both the short‐run and the long‐run effects, to be monitored with equal interest and intensity.