Optimal dispatch for a microgrid incorporating renewables and demand response

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A robust energy and reserve dispatch model for prosumer microgrids incorporating demand response aggregators

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

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

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

IoT-based smart water network management challenges and future trend

Abstract: In recent years, internet of things (IoT)-based tech- nology has been deployed to different areas of water supply system. This is in line with the Smart Water Network Manage- ment (SWNM) initiative, that aims to propose a methodology to improve operational performance and monitoring of water supply systems. In the smart water network management applications, IoT-based technology is facing quite a few challenges. In this paper, we present IoT’s applications for monitoring the water supply network with emphasis on its application to water quality and leakage monitoring. In these applications, the technical challenges of IoT-based technology are also discussed. Finally, future research directions in this domain are also highlighted, which may be useful for further studies

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

Abstract: In water supply systems (WSS), water loss is inex- orable, nevertheless, the volume of these losses differ from one WSS to the other. Because of its association with financial losses, environmental concern and most importantly saving of the water resource, advanced computing tools and methodologies have been developed for sustainable management of water resource through leak localisation. Over the years, several research studies have been conducted proposing different methodologies for leak localisation in WSS. Amongst the previous methodology used, a model-based approach is cost-effective. Thus, this paper presents a literature synopsis on the model-based approach to localising leaks in WSS. We categorise the model-based approach under orifice discharge modelling, pressure measurement and leak sensitivity analysis, water audit and minimum night flow analysis, leak signature analysis, and optimisation approach. Numerous research studies in this category are discussed therein. Also, technical challenges and research gaps for further studies are introduced

Harmonic and power loss minimization in power systems incorporating renewable energy sources and locational marginal pricing

Abstract: In composite expansion planning, improving the efficiency and power quality of power supplied from Renewable Energy Sources (RES) is highly essential. Therefore, this paper focuses on developing an optimal power flow optimization model for minimizing power loss and harmonics emanating from RES with emphasis on reducing their impacts on the Locational Marginal Prices (LMP). In order to assess the magnitude of harmonics, grid modelling and simulation with RES such as wind and solar energy was carried out using the Electrical Transient Analyzer Program (ETAP 12.6.0) software. The proposed mixed integer nonlinear programming mathematical model was solved using the Outer Approximation Algorithm (AOA) solver in the Advanced Interactive Multidimensional Modelling System (AIMMS), and the efficiency of the model was tested on the modified IEEE 6 bus and 24 bus system. The results obtained from simulations reveal the efficiency of the proposed model in terms of effective costs reduction, nodal marginal price reduction, minimization of harmonic losses and additional lines in the power system network

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

Abstract: The inclusion of storage systems in renewable-based energy systems is a promising option to boost the reliability of power supply for offgrid communities. A major consideration is the cost and performance of the selected storage system. This study investigates different energy storage combinations to form a hybrid energy storage system (HESS). The goal is to exploit the complementary characteristics of each storage system. The effects of system degradation on energy output and replacement costs over a 20-year period are analysed and used in obtaining the Levelised Cost of Hybrid Energy Storage Systems (LCOHESS); which can be used as a basis for comparing the techno-economic benefits of different HESS configurations. The model is run with data for a community in the Northern Cape Province, South Africa, to show the best HESS option that could be deployed by rural electrification planners and investors, based on the value of LCOHESS obtained

A survey of machine learning methods applied to anomaly detection on drinking-water quality data

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

Assessment of encryption and decryption schemes for secure data transmission in healthcare systems

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

A review on DC collection grids for offshore wind farms with HVDC transmission system

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