Optimal Energy Management In A Smart Home, Based On Photovoltaic Systems Energy Feed-In Tariff: Case Of South Africa

Abstract

In recent years, concern over environmental problems, such as the increase of atmospheric temperatures and destruction of the ozone layer, have amplified on a global scale. In the future, increased efficiency of energy systems and reduced end-use energy demand will be significant in attaining the 6% curtailment of greenhouse gases, targeted by the Kyoto Protocol. Although the energy research and development has been known over an extended period in large buildings, it has recently been applied at household level. In South Africa, there are approximately 9 million homes that have access to electricity. Approximately 27% of the generated energy in South Africa was consumed by the residential sector in 2015. This making the residential sector the second largest energy consumer in the economy. In South Africa, electricity is solely supplied by Eskom, a state-owned enterprise. For the last decade, Eskom have experienced challenges in meeting the national demand. The issue of the supply being less than the demand, has led to the requirement of additional fossil fuel plants, which resulted in financial challenges. These financial challenges have resulted in harsh tariff increases for consumers. With the aim to reduce the load-demand of the grid during peak periods, the electricity supply commission (ESKOM), implemented the time-of-use (TOU) tariff structure, billing consumers at a higher tariff rate during certain periods of the day. These tariff increases are compelling consumers to search for alternative ways in meeting their energy demand. Currently, many countries are permitting residential consumers to install renewable forms of energy sources. With Eskom contending to meet the load demand, load shedding was introduced, in order to reduce the load demand during certain periods of the day. If load shedding was never introduced, the load demand may have resulted in the grid collapsing. As a result of the electricity challenge in South Africa, a few municipalities have begun revising the regulations on small scale embedded generators, permitting consumers, under strict regulations, to feed-back excess energy into the grid. This study used a solar photovoltaic (PV) system, combined with battery storage. The mathematical modelling of the gridinteractive PV, with battery storage system, has been developed to allow for optimal energy storage and sales, while ensuring that the consumer load demand is met at all times, considering variable time-of-use (TOU) tariffs and load demand uncertainties, that may take place in real-time context. The aim is to develop a model for optimal operation of a residential grid-interactive PV system with battery storage, operating under TOU and FIT tariffs. The research will further assess the potential of energy cost saving and cost effectiveness that the system may achieve, under the new residential feed-in tariff; along with the impact the battery storage system will have on the profitability of the grid-interactive solar PV system. Additionally, the second aim is to maximize the energy sales into the grid, if the system is grid-interactive. The MATLAB optimization toolbox was used to evaluate the cost effectiveness of the grid-interactive system, in terms of money spent. The baseline system was established, consisting solely of energy supplied by the grid. The optimal operation of the proposed system was simulated and compared to the baseline system. A life cycle cost (LCC) analysis was conducted for a period of 20 years, for both the baseline and the optimally controlled grid-interactive PV with battery storage system scheme. Results from the analysis indicated that the proposed system would break-even in 11.5 years, with an approximate saving of 35%, translating into savings of R 270 022.83. The results clearly illustrated that the consumer could save a significant amount if the system is implemented correctly, including the parameters of the desired system. The model showed that it could be used for different operating conditions, as long as the user incorporates the new environment. The model clearly shows that managing the power flow in a proposed system could be beneficial for electricity consumers in South Africa and not merely for residential consumers.