Performance and cost benefit analyses of university campus microgrid.

Doctoral Degree. University of KwaZulu- Natal, Durban.Affordable and clean energy is one of the sustainable development goals (SDGs) to be achieved by the year 2030. Renewable energy sources such as wind, hydro, solar are free and inexhaustible globally to produce clean, reliable and cost effective power. However, most renewable energy sources are intermittent, to overcome this barrier, the concept of microgrid has been deployed in many applications to aggregate renewable energy resources, energy storage system and energy management system for sustainable, reliable, economical and environmental - friendly power system. Furthermore, considering the continuous increase in the cost of electricity and recent load shedding in South Africa, universities can reduce cost of energy demand, avoid interruption of academic activities due to load shedding and develop a test-bed or laboratory in which students and faculty staff can conduct research to advance modern power system through a self-sustaining microgrid. The university is like a separate entity and can operate as an island with sufficient resources to meet her energy demands. This thesis analyses the performance of a university campus microgrid using the five campuses of the University of Kwa-Zulu Natal as case studies considering economical and environmental benefits. Three different studies are carried out to achieve the aim and objectives of this work. The first study considers a grid connected microgrid using the real time data from the university energy management system, the modelling and simulations are implemented in HOMER Grid®. The main objective is to determine the optimal generation mix and size of a hybrid system consisting of the utility (eThekwini Electricity), solar PV, wind turbine, diesel generator and battery system taking into consideration the cost of energy (COE), net present cost (NPC), return on investment (ROI), payback period (PBP), utility cost saving and CO2 emission reduction. The second study aims to optimize the operational cost of a hybrid power system (PV-Wind-Diesel Generator-Battery) using two campuses as case studies. The objective function is formulated as a non-linear cost function and solved using a MATLAB function, ‘quadprog’ considering daily demands during summer and winter study and vacation periods with the aim of comparing the fuel costs and assess the effectiveness of the hybrid system. The third study proposes a novel optimization algorithm, the Quantum-behaved bat algorithm (QBA) to solve combined economic and emission dispatch (CEED) problem in an off-grid microgrid with onsite thermal generators and renewable energy sources (PV and Wind). The results obtained from these studies show and validate the fact that renewable energy source (RES) can be used to meet university energy demands in an economical way and reduce carbon footprint on campuses. It is observed from the result that the annual utility bill savings range from R3.97 million to R17.42 million and directly proportional to the peak load. The average emission reduction for all campuses is 49.6% except Pietermaritzburg where it is 33.7 %. In addition, the results will help university management as well as city management to invest wisely in renewables for energy sustainability and reliability

Economic and environmental analysis of a grid-connected hybrid power system for a University Campus

Abstract Background The generation of clean and affordable energy by 2030 is a challenging task, necessitating the integration of renewable energy sources to reduce greenhouse gas emissions associated with coal, crude oil, and natural gas. This study examines the optimization and performance analysis of a hybrid microgrid for a university campus as a potential solution to achieve this goal. The primary objective is to decrease the cost of energy and reduce CO2 emissions on the campus using a hybrid approach. Results The Howard college campus of the University of KwaZulu Natal (UKZN) was used as a case study, with meteorological data obtained from NASA and real hourly electrical load data for 2019 from the university smart meters. HOMER, an optimization software, was employed to model and simulate the case study. The results demonstrated significant savings of R15.7 million (approximately $ 820 000) in annual utility bills, a 51% reduction in CO2 emissions, a return on investment of 20%, and a payback period of 4 years. Conclusion The study's findings suggest that universities can become self-sustaining during load shedding periods, as recently experienced in South Africa. The implementation of a hybrid microgrid system on a university campus offers considerable economic and environmental benefits, providing a potential blueprint for other large institutions seeking to achieve similar sustainability goals

A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

The requirement for clean energy has increased drastically over the years due to the emission of CO2 and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work

Performance Analysis of a Hybrid Micro-Energy System for SA Data Centers

The integration of hybridized renewable energy sources (RES) with AC/DC converters has become the focus of the 21st century for green Information Communication Technology (ICT) applications such as the data center. As the data traffic grows exponentially, the corresponding demand for energy to drive the growth becomes a great challenge and considering the environmental impact, a hybrid renewable energy system is favored for eco-sustainability and economic reasons. This is especially true for data centers which represent a dominant share of the total power in cellular networks. This paper evaluates the actual performance of a fuel cell in a renewable energy hybrid system considering the hybridization of photovoltaic (PV), Wind, Fuel Cell, and battery storage system with a choice of a half-grid mode. The reduction and the absence of available PV power by shading and rainy conditions will be easily reduced by the compensation of the other renewable sources. The modeling and simulations are performed using HOMER software. The results show the effectiveness of the proposed system as the energy supply is less intermittent and more stable

Performance Analysis of a Hybrid Micro-Energy System for SA Data Centers

The integration of hybridized renewable energy sources (RES) with AC/DC converters has become the focus of the 21st century for green Information Communication Technology (ICT) applications such as the data center. As the data traffic grows exponentially, the corresponding demand for energy to drive the growth becomes a great challenge and considering the environmental impact, a hybrid renewable energy system is favored for eco-sustainability and economic reasons. This is especially true for data centers which represent a dominant share of the total power in cellular networks. This paper evaluates the actual performance of a fuel cell in a renewable energy hybrid system considering the hybridization of photovoltaic (PV), Wind, Fuel Cell, and battery storage system with a choice of a half-grid mode. The reduction and the absence of available PV power by shading and rainy conditions will be easily reduced by the compensation of the other renewable sources. The modeling and simulations are performed using HOMER software. The results show the effectiveness of the proposed system as the energy supply is less intermittent and more stable

A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

The requirement for clean energy has increased drastically over the years due to the emission of CO2 and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work

A Comparative Evaluation of Biodiesel and Used Cooking Oil as Feedstock for HDRD Application: A Review

The search for clean energy for transportation fuel across the globe has grown in intensity. The use of biodiesel as a fuel for compression ignition (CI) engines has shown some deficiencies, e.g., poor storage, and poor pour point. The carbon chain of biodiesel is one of the factors to be considered; the longer carbon chain length leads to decreased ignition delay, which leads to the formation of OH during the premixed combustion phase. The major challenges that render biodiesel inefficient are discussed, like higher viscosity, lower energy content, higher nitrogen oxide (NOX) emissions, lower engine speed and power, injector coking, engine compatibility, high cost, and higher engine wear. The novelty of this work is that it shows that biodiesel conversion to green diesel is possible using a biowaste heterogeneous catalyst to obtain quality and high yield of HDRD with lower cost. This renewable energy (HDRD) possesses properties that are directly compatible with CI engines and transportation engines. This research reviewed biodiesel and UCO as feedstocks for the production of HDRD, including the cost–benefit of these feedstocks. Hydrogenation of biodiesel has the potential to overcome the drawbacks of conventional chemically catalyzed processes

Optimal Allocation of Photovoltaic Distributed Generations in Radial Distribution Networks

Photovoltaic distributed generation (PVDG) is a noteworthy form of distributed energy generation that boasts a multitude of advantages. It not only produces absolutely no greenhouse gas emissions but also demands minimal maintenance. Consequently, PVDG has found widespread applications within distribution networks (DNs), particularly in the realm of improving network efficiency. In this research study, the dingo optimization algorithm (DOA) played a pivotal role in optimizing PVDGs with the primary aim of enhancing the performance of DNs. The crux of this optimization effort revolved around formulating an objective function that represented the cumulative active power losses that occurred across all branches of the network. The DOA was then effectively used to evaluate the most suitable capacities and positions for the PVDG units. To address the power flow challenges inherent to DNs, this study used the Newton–Raphson power flow method. To gauge the effectiveness of DOA in allocating PVDG units, it was rigorously compared to other metaheuristic optimization algorithms previously documented in the literature. The entire methodology was implemented using MATLAB and validated using the IEEE 33-bus DN. The performance of the network was scrutinized under normal, light, and heavy loading conditions. Subsequently, the approach was also applied to a practical Ajinde 62-bus DN. The research findings yielded crucial insights. For the IEEE 33-bus DN, it was determined that the optimal locations for PVDG units were buses 13, 25, and 33, with recommended capacities of 833, 532, and 866 kW, respectively. Similarly, in the context of the Ajinde 62-bus network, buses 17, 27, and 33 were identified as the prime locations for PVDGs, each with optimal sizes of 757, 150, and 1097 kW, respectively. Remarkably, the introduction of PVDGs led to substantial enhancements in network performance. For instance, in the IEEE 33-bus DN, the smallest voltage magnitude increased to 0.966 p.u. under normal loads, 0.9971 p.u. under light loads, and 0.96004 p.u. under heavy loads. These improvements translated into a significant reduction in active power losses—61.21% under normal conditions, 17.84% under light loads, and 33.31% under heavy loads. Similarly, in the case of the Ajinde 62-bus DN, the smallest voltage magnitude reached 0.9787 p.u., accompanied by an impressive 71.05% reduction in active power losses. In conclusion, the DOA exhibited remarkable efficacy in the strategic allocation of PVDGs, leading to substantial enhancements in DN performance across diverse loading conditions