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A distribution grid is the dispatching part of the power grid where electricity is finally utilized by the end users. In the electricity industry, automation habitually means the smart grid. The SG is a broad topic with different elements working towards grid optimization. One best way of optimizing a power grid is to balance the electricity supply and usage. This paper proposes an automated approach and presents a coordinative concept to develop a real-time interfacing network for demand-side management mitigations. The SDNS network concept uses a master–slave metering hierarchy to coordinate the devices between the utility and the end users by regulating the electrons' movement from the utility to the consumer's side. This concept was tested on MATLAB and a prototype. The results proved the efficiency of this design in demand-side management. The SDNS is an innovative tech, and it also plays a vital role in making consumers role players in easing the grid. The results proved that load management could replace load shedding by correctly implementing the SDNS concept. [ABSTRACT FROM AUTHOR]

Services surrounding green buildings are specialised and directed towards the process of design and comprise comprehensive and quantified management in its entirety. Implicitly, consultancies are unable to deliver this service at the standard and pace required in the preliminary stages of design, and not all clients or consultants will require the services to be essential. The main aim is to stabilise the several characteristics prompting one another to optimise design performance against the optimisation algorithms. Green Star is a universal evaluation tool, assessing not only green characteristics but also elements that influence wellbeing and occupant health, such as indoor environment quality. The tools for Green Star rating can be used to measure the green features of a building from the design phase right to the stage of site handover (known as "As-Built"). This paper refers, in the literature review, to the passive and low-energy design methods of a Green Star-rated building at early design stages. The "green" project management of a project is to coordinate multidisciplinary incorporation and to accompany the costing contribution tools presented in this paper. The passive and low-energy design tools discussed entails the amalgamation of electrical and mechanical services together with architecture, i.e., space layout and envelope design. This paper compares rationalised energy and indoor environment performance between two buildings against the activities and climatic conditions within a targeted Green Star-rated building. Proposals regarding 4- and 6-star ratings and techniques have been evaluated and presented for the two buildings. [ABSTRACT FROM AUTHOR]

The long-term impact of high-energy consumption in the manufacturing sector results in adverse environmental effects. Energy consumption and carbon emission prediction in the production environment is an essential requirement to mitigate climate change. The aim of this paper is to evaluate, model, construct, and validate the electricity generated data errors of an automotive component manufacturing company in South Africa for prediction of future transport manufacturing energy consumption and carbon emissions. The energy consumption and carbon emission data of an automotive component manufacturing company were explored for decision making, using data from 2016 to 2018 for prediction of future transport manufacturing energy consumption. The result is an ARIMA model with regression-correlated error fittings in the generalized least squares estimation of future forecast values for five years. The result is validated with RSS, showing an improvement of 89.61% in AR and 99.1% in MA when combined and an RMSE value of 449.8932 at a confidence level of 95%. This paper proposes a model for efficient prediction of energy consumption and carbon emissions for better decision making and utilize appropriate precautions to improve eco-friendly operation. [ABSTRACT FROM AUTHOR]

Healthcare institutions consume large amounts of energy, ranking the second highest energy-intensive buildings in the commercial sector. Within developed countries, the energy consumption of healthcare institutions may account for up to 18% of the overall energy usage in commercial sectors. Within developing countries, such as South Africa, the energy consumption of healthcare institutions is observed to be a close second to the food service sector. Energy consumption of healthcare institutions per bed typically range from 43–92 kWh per day. In this paper, the largest energy consumers in South African healthcare institutions are identified and appropriate energy-efficiency (EE) initiatives are proposed, in terms of performance, operation, equipment and technology efficiency (POET). Two main thermal energy consumers are identified as heating, ventilation and air conditioning (HVAC) and water-heating systems. These systems are critical to patient health and may be classified as non-deferrable loads. Therefore, several initiatives are suggested to improve the energy efficiency and demand-side management capability of these systems. These initiatives are subdivided into different levels: the conceptual level, active level, technical and further improvement level, as defined in the POET framework. At each level, energy-efficiency initiatives are introduced based on potential energy savings and the effort required to achieve these savings. In addition, model predictive control (MPC) approaches are discussed and reviewed as part of the further improvement section. Average possible energy savings ranged from 50%–70% at the conceptual level, while energy savings of 15%–30% may be expected for energy-efficiency initiatives at the active level. EE activities at the technical level and the further improvement level may result in savings of 50%–70% and 5%–10%, respectively. [ABSTRACT FROM AUTHOR]