No abstract

Energy consumption in the building sector is a major concern, particularly in this time of worldwide population and energy demand increases. To reduce energy consumption due to HVAC systems in the building sector, different models based on measured data have been developed to estimate the cooling load. The purpose of this work is to develop a linear regression model for cooling load of a research room based on the radiant time series (RTS) components of the cooling load that consider the building material and the environment. Using the forward step method, linear regression models were developed for both all-seasons and seasonal data from three years of cooling load data obtained from the RTS method for a research room at Mangosuthu University of Technology (MUT), South Africa. The male and female occupants, window cooling load, and roof cooling load were found to be the most influential predictors for the cooling load model. The obtained relative errors between the best all-seasons model and seasonal models built with the same predictors for the respective data subsets are almost zero and are given as 0.0073% (autumn), 0.0016% (spring), 0.0168% (summer), and 0.0162% (winter). This leads to the conclusion that the seasonal models can be represented by the all-seasons model. However, further study can be performed to improve the model by incorporating the occupancy behaviours and other components or parameters intervening in the calculation of cooling load using the radiant time series method.

Major changes in the technologies of power generation and distribution systems have been introduced in recent years due to concern over rapid climate change. Therefore, disturbances in the large-scale generation, transmission, and distribution of energy are expected to occur in the near future. This is due to the difficulty in controlling the transmission and distribution of energy produced from renewable energy sources (RESs), caused by the instability of these sources and the intermittent nature of their energy. As a result, maintaining the dynamic stability of wind power flow and control of the network frequency is becoming more challenging due to the high penetration impacts of RESs. In this paper, a control algorithm using the power-sharing method is proposed for a wind-based energy storage system to maintain the dynamic stability of wind power flow and control of frequency in the power network. To maintain the network stability, a storage system (battery) was installed to store the excess wind power without throwing it into the Secondary/Dump Load (SL) and minimize losses in power generated by the wind turbine. The results show, the transient time of wind power flow and the fluctuation rate of frequency are reduced significantly using a Fuzzy Logic (FL) controller compared to the Proportional Integral Derivative (PID) controller.

The conversion of solar irradiance into electricity by a photovoltaic module (PV) is 6-17% of the incom-

The photovoltaic (PV) technology as the third renewable energy (RE) generation source is growing faster than most of the RE technology due to intense research performed in this field. This last year has seen an important growing of PV technology in efficiency, cost, applications, capacity and economy. The global total solar PV installed capacity in 2018 is dominated by APAC (China included) with 58 % of solar PV installed capacity, follows by Europe (25 %), America (15 %) and MEA (2 %). Even with a decline of 16 % in 2018, the global solar PV market continue to be dominated by China with 44.4 GW installed in 2018 against 52.8 % GW in 2017. The 2018 solar PV outlook market forecast presents a growth of solar market with progressive slow down, from 2019 to 2023 over 5 years. Based on the predictions, the world could centre the Tetrawatts production capacity level by 2021, only 3 years after reaching 0.5 TW level. This paper is an update on the PV systems growing. Detailed summary on the evolution of PV cell structure, energy conversion, efficiency, cost, applications, environmental impact, capacity and economy are presented.