Current Situation and Future Development of Activity Theory in China

The cultural-historical activity theory was developed by the Russian psychologist Vygotsky and his colleagues in the 1920s and 1930s. Since then, it has been expanded globally and rapidly, particularly during the past 15 years. However, there has been little interaction between the broader international community and China with respect to the development of the theory and its applications in China, which has taken place along a path of its own. This paper aims to examine this development, focusing on 1) the general situation and background of the research, 2) the basic understanding, theoretical construction and unique features of development; 3) the focal areas in and limitations of the application; and 4) idea evolution in terms of different generation theories. At the end of the paper, emerging trends and future prospects of activity theoretical research in China will be suggested and discussed

Enhanced frequency response from industrial heating loads for electric power systems

Increasing penetration of renewable generation results in lower inertia of electric power systems. To maintain the system frequency, system operators have been designing innovative frequency response products. Enhanced Frequency Response (EFR) newly introduced in the UK is an example with higher technical requirements and customized specifications for assets with energy storage capability. In this paper, a method was proposed to estimate the EFR capacity of a population of industrial heating loads, bitumen tanks, and a decentralized control scheme was devised to enable them to deliver EFR. Case study was conducted using real UK frequency data and practical tank parameters. Results showed that bitumen tanks delivered high-quality service when providing service-1-type EFR, but underperformed for service-2-type EFR with much narrower deadband. Bitumen tanks performed well in both high and low frequency scenarios, and had better performance with significantly larger numbers of tanks or in months with higher power system inertia

Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates

We consider performing simulation experiments in the presence of covariates. Here, covariates refer to some input information other than system designs to the simulation model that can also affect the system performance. To make decisions, decision makers need to know the covariate values of the problem. Traditionally in simulation-based decision making, simulation samples are collected after the covariate values are known; in contrast, as a new framework, simulation with covariates starts the simulation before the covariate values are revealed, and collects samples on covariate values that might appear later. Then, when the covariate values are revealed, the collected simulation samples are directly used to predict the desired results. This framework significantly reduces the decision time compared to the traditional way of simulation. In this paper, we follow this framework and suppose there are a finite number of system designs. We adopt the metamodel of stochastic kriging (SK) and use it to predict the system performance of each design and the best design. The goal is to study how fast the prediction errors diminish with the number of covariate points sampled. This is a fundamental problem in simulation with covariates and helps quantify the relationship between the offline simulation efforts and the online prediction accuracy. Particularly, we adopt measures of the maximal integrated mean squared error (IMSE) and integrated probability of false selection (IPFS) for assessing errors of the system performance and the best design predictions. Then, we establish convergence rates for the two measures under mild conditions. Last, these convergence behaviors are illustrated numerically using test examples

Benefits of using virtual energy storage system for power system frequency response

This paper forms a Virtual Energy Storage System (VESS) and validates that VESS is an innovative and cost-effective way to provide the function of conventional Energy Storage Systems (ESSs) through the utilization of the present network assets represented by the flexible demand. The VESS is a solution to convert to a low carbon power system and in this paper, is modelled to store and release energy in response to regulation signals by coordinating the Demand Response (DR) from domestic refrigerators in a city and the response from conventional Flywheel Energy Storage Systems (FESSs). The coordination aims to mitigate the impact of uncertainties of DR and to reduce the capacity of the costly FESS. The VESS is integrated with the power system to provide the frequency response service, which contributes to the reduction of carbon emissions through the replacement of spinning reserve capacity of fossil-fuel generators. Case studies were carried out to validate and quantify the capability of VESS to vary the stored energy in response to grid frequency. Economic benefits of using VESS for frequency response services were estimated

Virtual Energy Storage System for Smart Grids

AbstractThis paper forms a Virtual Energy Storage System (VESS) and validates that VESS is a cost-effective way to provide the function of energy storage through the utilization of the present network assets represented by flexible demand. As a solution to convert to low carbon cities, a VESS is firstly modelled to store and release energy in response to regulation signals by coordinating the demand response (DR) from domestic refrigerators in London and the conventional flywheel energy storage systems (FESS). The coordination of DR and FESS mitigates the uncertainties of DR and reduces the capacity of costly FESS. The VESS is applied to provide ancillary services to the power system and contributes to the reduction of carbon emission through the replacement of spinning reserve capacity of fossil fuel generators. Case studies were carried out to validate and quantify the capability of the VESS to vary the stored energy in response to grid frequency. Economic benefits of using VESS for frequency response services were firstly estimated and a potential saving of £91m-£103m is expected

Benefits of demand-side response in combined gas and electricity networks

Active demand side response (DSR) will provide a significant opportunity to enhance the power system flexibility in the Great Britain (GB). Although electricity peak shaving has a clear reduction on required investments in the power system, the benefits on the gas supply network have not been examined. Using a Combined Gas and Electricity Networks expansion model (CGEN+), the impact of DSR on the electricity and gas supply systems in GB was investigated for the time horizon from 2010 to 2050s. The results showed a significant reduction in the capacity of new gas-fired power plants, caused by electricity peak shaving. The reduction of gas-fired power plants achieved through DSR consequently reduced the requirements for gas import capacity up to 90 million cubic meter per day by 2050. The cost savings resulted from the deployment of DSR over a 50-year time horizon from 2010 was estimated to be around £60 billion for the GB power system. Although, the cost saving achieved in the gas network was not significant, it was shown that the DSR will have a crucial role to play in the improvement of security of gas supply

Multi-objective optimization of electrical distribution network operation considering reconfiguration and soft open points

High penetration levels of Distributed Generations (DG) significantly affect the operations of electrical distribution networks. In this paper, Distribution Network Reconfiguration (DNR), and the implementation of Soft Open Point (SOP) – a distribution-level power electronic device are investigated as effective solutions to facilitate large DG penetrations while meeting network operational constraints. DNR is developed based on the ant colony optimization, and the optimal SOP outputs are determined using the Taxi-cab algorithm after determining the network configuration. Both optimization problems are formulated within a multi-objective framework using the Pareto optimality. The performances of DNR and SOP to improve network operations are demonstrated on a modified 33-bus distribution system with various DG penetrations

Review of existing peer-to-peer energy trading projects

Peer-to-Peer (P2P) energy trading is a novel paradigm of power system operation, where people can generate their own energy from Renewable Energy Sources (RESs) in dwellings, offices and factories, and share it with each other locally. The number of projects and trails in this area has significantly increased recently all around the world. This paper elaborates main focuses and outcomes of those projects, and compares their similarities and differences. The results show that although many of the trails focus on the business models acting similarly to a supplier's role in the electricity sector, it is also necessary to design the necessary communication and control networks that could enable P2P energy trading in or among local Microgrids