Showing items 1 - 14 of 14

A mathematical formulation of the joint economic and emission dispatch problem of a renewable energy-assisted prosumer microgrid

- Damisa, Uyikumhe, Nwulu, Nnamdi I., Sun, Yanxia

  • Authors: Damisa, Uyikumhe , Nwulu, Nnamdi I. , Sun, Yanxia
  • Date: 2019
  • Subjects: Emissions dispatch , Energy management , Microgrid
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/406821 , uj:34219 , Citation: Damisa, U., Nwulu, N.I. & Sun, Y. 2019. A mathematical formulation of the joint economic and emission dispatch problem of a renewable energy-assisted prosumer microgrid.
  • Description: Abstract: Operational planning of prosumer microgrids with solar and wind energy sources is quite a complex task considering the intermittency of these sources and energy import/export from prosumers. Reserve capacities which can be reliably provided by dispatchable sources like conventional generators (CGs) may be needed to ensure reliability of the grid. However, these sources produce emissions which have adverse effects on the environment. Hence, emission curtailment should be incorporated in the operational planning of microgrids with these generators. In this paper, a mathematical formulation for the joint economic and emission dispatch of a renewable energy-assisted prosumer microgrid is presented and solved using the CPLEX Solver in Advanced Interactive Multidimensional Modelling System (AIMMS). A modified microgrid test system is used as a case study in this work. Results show that incorporating an emission function in the objective of the operational dispatch formulation not only reduces emissions, but could be of advantage to customers as larger capacities of their behind-the–meter resources get the chance to provide grid ancillary services; however, it also puts a restriction on the profit that could be made from selling energy to the main grid during periods when energy prices are high.
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A review on DC collection grids for offshore wind farms with HVDC transmission system

- Musasa, Kabeya, Nwulu, Nnamdi I., Gitau, Michael Njoroge, Bansal, Ramesh C.

  • Authors: Musasa, Kabeya , Nwulu, Nnamdi I. , Gitau, Michael Njoroge , Bansal, Ramesh C.
  • Date: 2017
  • Subjects: DC collection grid , Active rectifier , Offshore wind farm
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/256925 , uj:26980 , Citation: Musasa, K. et al. 2017. A review on DC collection grids for offshore wind farms with HVDC transmission system.
  • Description: Abstract: Traditionally, the internal network composition of offshore wind farms consists of alternating current (AC) collection grid; all outputs of wind energy conversion units (WECUs) on a wind farm are aggregated to an AC bus. Each WECU includes: a wind-turbine plus mechanical parts, a generator including electronic controller, and a huge 50-or 60-Hz power transformer. For a DC collection grid, all outputs of WECUs are aggregated to a DC bus; consequently, the transformer in each WECU is replaced by a power converter or rectifier. The converter is more compact and smaller in size compared to the transformer. Thus reducing the size and weight of the WECUs, and also simplifying the wind farm structure. Actually, the use of offshore AC collection grids instead of offshore DC collection grids is mainly motivated by the availability of control and protection devices. However, efficient solutions to control and protect DC grids including HVDC transmission systems have already been addressed. Presently, there are no operational wind farms with DC collection grids, only theoretical and small-scale prototypes are being investigated worldwide. Therefore, a suitable configuration of the DC collection grid, which has been practically verified, is not available yet. This paper discussed some of the main components required for a DC collection grid including: the wind-turbine-generator models, the control and protection methods, the offshore platform structure, and the DC-grid feeder configurations. The key component of a DC collection grid is the power converter; therefore, the paper also reviews some topologies of power converter suitable for DC grid applications.
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A robust energy and reserve dispatch model for prosumer microgrids incorporating demand response aggregators

- Damisa, Uyikumhe, Nwulu, Nnamdi I., Sun, Yanxia

  • Authors: Damisa, Uyikumhe , Nwulu, Nnamdi I. , Sun, Yanxia
  • Date: 2018
  • Subjects: Microgrid , Robust optimization , Operational dispatch
  • Language: English
  • Type: Article
  • Identifier: http://ujcontent.uj.ac.za8080/10210/385963 , http://hdl.handle.net/10210/289857 , uj:31457 , Citation: Damisa, U., Nwulu, N.I. & Sun, Y. 2018. A robust energy and reserve dispatch model for prosumer microgrids incorporating demand response aggregators.
  • Description: Abstract: The uncertainty introduced by intermittent renewable energy generation and prosumer energy imports makes operational planning of renewable energy‐assisted prosumer microgrids challenging. This is due to the difficulty in obtaining accurate forecasts of energy expected from these renewable energy sources and prosumers. Operators of such microgrids therefore require additional grid‐balancing tools to maintain power supply and demand balance during grid operation. In this paper, the impact of demand response aggregators (DRA’s) in a prosumer microgrid is investigated. This is achieved by developing and solving a deterministic mathematical formulation for the operational planning of the grid. Also, taking a cue from CAISO’s proposed tariff revision which allows the state‐of‐charge of non‐generator resources (like storage units) to be submitted as a bid parameter in the day‐ahead market and permits scheduling coordinators of these resources to self‐manage their energy limits and state‐of‐charge, the proposed formulation permits prosumers to submit battery energy content as a bid parameter and self‐manage their battery energy limits. Furthermore, a robust counterpart of the model is developed. Both formulations are constrained mixed integer optimization problems which are solved using the CPLEX solver in Advanced Interactive Multidimensional Modelling System (AIMMS) environment. Results obtained from tests carried out on a hypothetical prosumer microgrid show that the operating cost of the microgrid reduces in the presence of DRA’s. In addition, the storage facility owner may benefit from self‐managing its energy limits, but this may cut the amount of grid‐balancing resource available to the microgrid operator, thereby increasing the operating cost of the microgrid.
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A survey of machine learning methods applied to anomaly detection on drinking-water quality data

- Dogo, Eustace M., Nwulu, Nnamdi I., Twala, Bhekisipho, Aigbavboa, Clinton

  • Authors: Dogo, Eustace M. , Nwulu, Nnamdi I. , Twala, Bhekisipho , Aigbavboa, Clinton
  • Date: 2019
  • Subjects: Machine learning , Anomaly detection , Deep learning
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/406768 , uj:34213 , Citation: Dogo, E.M. et al. 2019. A survey of machine learning methods applied to anomaly detection on drinking-water quality data.
  • Description: Abstract: Traditional machine learning (ML) techniques such as support vector machine, logistic regression, and artificial neural network have been applied most frequently in water quality anomaly detection tasks. This paper presents a review of progress and advances made in detecting anomalies in water quality data using ML techniques. The review encompasses both traditional ML and deep learning (DL) approaches. Our findings indicate that: 1) Generally, DL approaches outperform traditional ML techniques in terms of feature learning accuracy and fewer false positive rates. However, is difficult to make a fair comparison between studies because of different datasets, models and parameters employed. 2) We notice that despite advances made and the advantages of the extreme learning machine (ELM), application of ELM is sparsely exploited in this domain. This study also proposes a hybrid DL-ELM framework as a possible solution that could be investigated further and used to detect anomalies in water quality data.
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A wireless sensor network system for monitoring environmental factors affecting bulk grains storability

- Onibonoje, Moses O., Nwulu, Nnamdi I., Bokoro, Pitshou N.

Accessing imbalance learning using dynamic selection approach in water quality anomaly detection

- Dogo, Eustace M., Nwulu, Nnamdi I., Twala, Bhekisipho, Aigbavboa, Clinton

  • Authors: Dogo, Eustace M. , Nwulu, Nnamdi I. , Twala, Bhekisipho , Aigbavboa, Clinton
  • Date: 2021
  • Subjects: Classification , Imbalance learning , Dynamic selection
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/478606 , uj:43260 , Citation: Dogo, E.M.; Nwulu, N.I.; Twala, B.; Aigbavboa, C. Accessing Imbalance Learning Using Dynamic Selection Approach in Water Quality Anomaly Detection. Symmetry 2021, 13, 818. https://doi.org/10.3390/ sym13050818
  • Description: Abstract: Automatic anomaly detection monitoring plays a vital role in water utilities’ distribution systems to reduce the risk posed by unclean water to consumers. One of the major problems with anomaly detection is imbalanced datasets. Dynamic selection techniques combined with ensemble models have proven to be effective for imbalanced datasets classification tasks. In this paper, water quality anomaly detection is formulated as a classification problem in the presences of class imbalance. To tackle this problem, considering the asymmetry dataset distribution between the majority and minority classes, the performance of sixteen previously proposed single and static ensemble classification methods embedded with resampling strategies are first optimised and compared. After that, six dynamic selection techniques, namely, Modified Class Rank (Rank), Local Class Accuracy (LCA), Overall-Local Accuracy (OLA), K-Nearest Oracles Eliminate (KNORA-E), K-Nearest Oracles Union (KNORA-U) and Meta-Learning for Dynamic Ensemble Selection (META-DES) in combination with homogeneous and heterogeneous ensemble models and three SMOTE-based resampling algorithms (SMOTE, SMOTE+ENN and SMOTE+Tomek Links), and one missing data method (missForest) are proposed and evaluated. A binary real-world drinking-water quality anomaly detection dataset is utilised to evaluate the models. The experimental results obtained reveal all the models benefitting from the combined optimisation of both the classifiers and resampling methods. Considering the three performance measures (balanced accuracy, F-score and G-mean), the result also shows that the dynamic classifier selection (DCS) techniques, in particular, the missForest+SMOTE+RANK and missForest+SMOTE+OLA models based on homogeneous ensemble-bagging with decision tree as the base classifier, exhibited better performances in terms of balanced accuracy and G-mean, while the Bg+mF+SMENN+LCA model based on homogeneous ensemble-bagging with random forest has a better overall F1-measure in comparison to the other models.
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An IoT-based approach to real-time conditioning and control in a server room

- Onibonoje, Moses O., Bokoro, Pitshou N., Nwulu, Nnamdi I., Gbadamosi, Saheed L.

  • Authors: Onibonoje, Moses O. , Bokoro, Pitshou N. , Nwulu, Nnamdi I. , Gbadamosi, Saheed L.
  • Date: 2019
  • Subjects: Server room , Real-time , Conditioning
  • Language: English
  • Type: Conference proceedings
  • Identifier: http://hdl.handle.net/10210/409115 , uj:34339 , Citation: Onibonoje, M.O. et al. 2019. An IoT-based approach to real-time conditioning and control in a server room.
  • Description: Abstract: Server room provides the needed lodging for computer network infrastructures which support data transfer and storage. Beyond network attacks and failure in connectivity, the safety of the data depends mainly on the protection of such infrastructures from breakdown as a result of environmental effects. This paper presents an implementation of an Internet-of-Thing (IoT) based system for conditioning and controlling the environmental factors in real time. A model is proposed which relates the heat index which is the major factor of negative influence in the server room, to the air temperature and humidity within the area. The hardware and software units of the system were designed and implemented to condition the server room by monitoring power outage, heat, water leakage, smoke, flame and light-out; and initiate a real-time corrective measure to keep them within the respective set thresholds. The implemented real-time control measures include: setting-off air-conditioning system whenever the heat threshold is exceeded, turning off the perimeter water supply whenever there is water-leak within the room, tripping off the system and triggering the alarm system for smoke or fire detection. Data and notifications are sent to the internet cloud, administrator’s personal computer and mobile phone. The data are relayed through developed user interface platforms.
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Assessment of encryption and decryption schemes for secure data transmission in healthcare systems

- Adedeji, Kazeem B., Nwulu, Nnamdi I., Aigbavboa, Clinton, Gbadamosi, Saheed L.

  • Authors: Adedeji, Kazeem B. , Nwulu, Nnamdi I. , Aigbavboa, Clinton , Gbadamosi, Saheed L.
  • Date: 2019
  • Subjects: Data security , Decryption , Encryption
  • Language: English
  • Type: Conference proceedings
  • Identifier: http://hdl.handle.net/10210/405247 , uj:34022 , Citation: Adedeji, K.B. et al. 2019. Assessment of encryption and decryption schemes for secure data transmission in healthcare systems.
  • Description: Abstract: In the biomedical research community, transmitting a patient medical record via wireless means to an administrative centre or other medical centres is increasingly common. However, due to the open nature of wireless media, the security of such a system is a major concern, so, it is desirable to have a reliable security scheme. Amidst the numerous methods used to secure medical data, encryption schemes are becoming more popular due to their performance and relative simplicity. In this study, the performance of some data encryption and decryption schemes used to secure medical data is evaluated. These schemes are Blowfish, DES, AES, RC4, RSA, ECC, CBE, MTLM and CEC. The performance of these schemes was assessed through their execution time, throughput, average data rate and information entropy. For this performance assessment, some medical data were used for this task. The results showed that the performance of CBE, MTLM and CEC was better. CBE and MTLM offer a secure way to encrypt data with a significant reduction in the execution time. Moreover, if some of these schemes were combined to form a hybrid system, an enhancement in the security of medical data over wireless communication networks is guaranteed.
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Dataset for a wireless sensor network based drinking-water quality monitoring and notification system

- Sithole, Mhambi Phila Philadephian, Nwulu, Nnamdi I., Dogo, Eustace M.

  • Authors: Sithole, Mhambi Phila Philadephian , Nwulu, Nnamdi I. , Dogo, Eustace M.
  • Date: 2019
  • Subjects: Water quality parameters , Sensors , Internet of things
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/407383 , uj:34289 , Citation: Sithole, M.P.P., Nwulu, N.I. & Dogo, E.M. 2019. Dataset for a wireless sensor network based drinking-water quality monitoring and notification system.
  • Description: Abstract: This paper presents the collected experimental data for water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, salt, washing powder, chlorine and vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the water quality parameters standards proposed by the World Health Organisation (WHO) and the South African Department of Water Affairs (DWA), with respect to the sensor measurement readings obtained. While the error measurements were calculated based on the expected parameter measurement per conducted experiment and repeated for 26 measurements. Pure tap water was the benchmark of water safe for human consumption. The first five experiments were performed by introducing each contaminant into the water and thereafter, two contaminants in the sixth experiment and their additions until all different contaminants were experimented at once in the last experiment.
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Harmonic and power loss minimization in power systems incorporating renewable energy sources and locational marginal pricing

- Gbadamosi, Saheed Lekan, Nwulu, Nnamdi I., Sun, Y.

IoT-based smart water network management challenges and future trend

- Adedeji, Kazeem B., Nwulu, Nnamdi I., Clinton, Aigbavboa

Leak localisation in urban water supply system : a literature synopsis on model based methodologies

- Adedeji, Kazeem B., Nwulu, Nnamdi I., Aigbavboa, Clinton

Optimal dispatch for a microgrid incorporating renewables and demand response

- Nwulu, Nnamdi I., Xia, Xiaohua

Techno-economic analysis of storage degradation effect on levelised cost of hybrid energy storage systems

- Gbadegesin, Azizat O., Sun, Yanxia, Nwulu, Nnamdi I.

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