Abstract
A control strategy Is proposed In this paper based on considering the upper and lower's arms modulation functions of a MMC in HVDC applications. The designed modulation-functions-based controller is consisted of the modulation index and phase that are accurately evaluated according to ac-side voltage, MMC voltage and current components in a-b-c reference frame. Two main contributions of the proposed control strategy over the other existing control techniques are robust against the MMC parameter variations and simplicity operation that causes MMC to perform the ac/DC conversion for the HVDC applications. The simulation results verify the ability of the proposed control strategy at approaching to the stable performance of MMC under various operating conditions. © 2018 IEEE.

Abstract

Abstract
Bundled generation and transmission expansion planning (BGTEP) aims to solve problems related to ascendant demand of power systems. A BGTEP model is considered in this paper and the optimal planning for a long-term period is obtained such that the cost of installation and operation would be minimized. Also, due to the recent orientation toward renewable energy sources, the influence of wind farms is involved in the methodology. An important aspect of load and wind power is their uncertain nature and the characteristic of being unforeseen. This matter is under consideration by a bounded and symmetric uncertainty optimization approach. In fact, the combination of two uncertainty methods, i.e., robust and stochastic optimization approaches are utilized and formulated in this paper. Besides, to cope with this uncertainty, Weibull distribution (WD) is considered as wind distribution, while load distribution is counted by a normal distribution (ND). A unique approximation approach for WD to be considered as ND is presented. In addition, a linear formulation is obtained by alternative constraints in order to drastically reduce the level of complexity of the formulation. Accordingly, a mixedinteger linear programming formulation is proposed to solve the BGTEP problem. The modified 6-bus and IEEE 24-bus RTS test systems are used to prove the applicability of the proposed method.

Abstract
This paper presents an approach to the energy management and control of the effective cost of energy in real-time electricity pricing environment. The strategy aims to optimise the overall energy flow in the electrical system that minimises the cost of power consumption from the grid. To substantiate these claims different cases of time-of-use (TOU) and renewable energy electricity tariff, i.e. in summer and winter seasons, and the robustness of system is analysed. A given energy demand for commercial usage in the city of Tshwane (South Africa) is used to investigate the behaviour of the designed method during low and high demand periods. As grid integrated renewable energy resources, photovoltaic (PV) is an important consideration in assuring excellent power supply and environmental issues in the commercial building. An adaptive optimal approach in the framework of model predictive control (MPC) is designed to coordinate the energy flow on the electrical system. The results show that the proposed adaptive MPC strategy can promote the new approach of an optimal electrical system design, which reduces the energy cost to pay the utility grid by about 46% or more depending on the set target.

Abstract
The comprehensive understanding of the residential electricity consumption patterns (ECPs) and how they relate to household characteristics can contribute to energy efficiency improvement and electricity consumption reduction in the residential sector. After recognizing the limitations of current studies (i.e. unreasonable typical ECP (TECP) extraction method and the problem of multicollinearity and interpretability for regression and machine learning models), this paper proposes an association rule mining based quantitative analysis approach of household characteristics impact on residential ECPs trying to address them together. First, an adaptive density-based spatial clustering of applications with noise (DBSCAN) algorithm is utilized to create seasonal TECP of each individual customer only for weekdays. K-means is then adopted to group all the TECPs into several clusters. An enhanced Apriori algorithm is proposed to reveal the relationships between TECPs and thirty five factors covering four categories of household characteristics including dwelling characteristics, socio-demographic, appliances and heating and attitudes towards energy. Results of the case study using 3326 records containing smart metering data and survey information in Ireland suggest that socio-demographic and cooking related factors such as employment status, occupants and whether cook by electricity have strong significant associations with TECPs, while attitudes related factors almost have no effect on TECPs. The results also indicate that those households with more than one person are more likely to change ECP across seasons. The proposed approach and the findings of this study can help to support decisions about how to reduce electricity consumption and CO2 emissions.

Abstract
Navigation through immersive virtual environments is a key concept for virtual reality as it allows users to explore those environments. Therefore, it is important to understand virtual reality navigation interfaces and their impact on the users' experience. This paper presents an objective performance evaluation of two types of navigation: natural (real walking and walk-in-place) vs. unnatural (gamepad). Steering Law was the objective performance metric chosen since it captures the relationship between the time to travel a path and the difficulty of that path. In addition to performance, subjective metrics were also considered, namely the feeling of presence, cybersickness and user satisfaction. The experiments consisted of having participants complete a series of paths with different indexes of difficulty and the time that a participant took to walk each path was measured. Overall results show that the navigation through real walking yielded better results when it comes to performance, cybersickness, and user satisfaction than the walk-in-place and gamepad navigation interfaces.