Citation Zubo RHA, Mokryani G, Rajamani HS et al (2016) Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review.

In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands. It further investigates the impact of solar and wind power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment. A mixed-integer linear programming (MILP) is used to recast the proposed model, which is solvable using efficient off-the shelf branch-and cut solvers. The 16-bus UK generic distribution system is demonstrated in this work to evaluate the effectiveness of the proposed method. Results show that DR integration leads to increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.

Hybrid AC-DC microgrid (HMG) allows direct integration of both AC distributed generators (DGs) and DC DGs, AC and DC loads into the grid. The AC and DC sources and loads are separated out and are connected to respective subgrid mainly to reduce the power conversion; thus the overall efficiency of the system increases. This study aims to introduce a novel HMG planning model within a microgrid market environment to maximise net social welfare (NSW). NSW is defined as the present value of total demand payment minus the present value of total planning cost, including the investment cost of distributed energy sources (DERs) and converters, operation cost of DERs, and the cost of energy exchange with the utility grid subject to network constraints. The scenario tree approach is used to model the uncertainties related to load demand, wind speed, and solar irradiation. The effectiveness of the proposed model is validated through the simulation studies on a 28-bus real HMG.

Solar energy, amongst all renewable energies, has attracted inexhaustible attention all over the world as a supplier of sustainable energy. The energy requirement of major seawater desalination processes such as multistage flash (MSF), multi-effect distillation (MED) and reverse osmosis (RO) are fulfilled by burning fossil fuels, which impact the environment significantly due to the emission of greenhouse gases. The integration of solar energy systems into seawater desalination processes is an attractive and alternative solution to fossil fuels. This study aims to (i) assess the progress of solar energy systems including concentrated solar power (CSP) and photovoltaic (PV) to power both thermal and membrane seawater desalination processes including MSF, MED, and RO and (ii) evaluate the economic considerations and associated challenges with recommendations for further improvements. Thus, several studies on a different combination of seawater desalination processes of solar energy systems are reviewed and analysed concerning specific energy consumption and freshwater production cost. It is observed that although solar energy systems have the potential of reducing carbon footprint significantly, the cost of water production still favours the use of fossil fuels. Further research and development on solar energy systems are required to make their use in desalination economically viable. Alternatively, the carbon tax on the use of fossil fuels may persuade desalination industries to adopt renewable energy such as solar.

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The single-stage flyback Photovoltaic (PV) micro-inverter is considered as a simple and small in size topology but requires expensive digital microcontrollers such as Field-Programmable Gate Array (FPGA) or Digital Signal Processor (DSP) to increase the system efficiency, this would increase the cost of the overall system. To solve this problem, based on a single-stage flyback structure, this paper proposed a low cost and simple analog-digital control scheme. This control scheme is implemented using a low cost ATMega microcontroller built in the Arduino Uno board and some analog operational amplifiers. First, the single-stage flyback topology is analyzed theoretically and then the design consideration is obtained. Second, a 120 W prototype was developed in the laboratory to validate the proposed control. To prove the effectiveness of this control, we compared the cost price, overall system efficiency, and THD values of the proposed results with the results obtained by the literature. So, a low system component, single power stage, cheap control scheme, and decent efficiency are achieved by the proposed system. Finally, the experimental results present that the proposed system has a maximum efficiency of 91%, with good values of the total harmonic distortion (THD) compared to the results of other authors.

This paper presents a fault detection method in three-phase induction motors using Wavelet Packet Transform (WPT). The proposed algorithm takes a frame of samples from the three-phase supply current of an induction motor. The three phase current samples are then combined to generate a single current signal by computing the Root Mean Square (RMS) value of the three phase current samples at each time stamp. The resulting current samples are then divided into windows of 64 samples. Each resulting window of samples is then processed separately. The proposed algorithm uses two methods to create window samples, which are called non-overlapping window samples and moving/overlapping window samples. Non-overlapping window samples are created by simply dividing the current samples into windows of 64 samples, while the moving window samples are generated by taking the first 64 current samples, and then the consequent moving window samples are generated by moving the window across the current samples by one sample each time. The new window of samples consists of the last 63 samples of the previous window and one new sample. The overlapping method reduces the fault detection time to a single sample accuracy. However, it is computationally more expensive than the non-overlapping method and requires more computer memory. The resulting window samples are separately processed as follows: The proposed algorithm performs two level WPT on each resulting window samples, dividing its coefficients into its four wavelet subbands. Information in wavelet high frequency subbands is then used for fault detection and activating the trip signal to disconnect the motor from the power supply. The proposed algorithm was first implemented in the MATLAB platform, and the Entropy power Energy (EE) of the high frequency WPT subbands’ coefficients was used to determine the condition of the motor. If the induction motor is faulty, the algorithm proceeds to identify the type of the fault. An empirical setup of the proposed system was then implemented, and the proposed algorithm condition was tested under real, where different faults were practically induced to the induction motor. Experimental results confirmed the effectiveness of the proposed technique. To generalize the proposed method, the experiment was repeated on different types of induction motors with different working ages and with different power ratings. Experimental results show that the capability of the proposed method is independent of the types of motors used and their ages.

The increasing use of high shares of renewable energy sources (RESs) in the current electricity network introduces challenges to the design and management of the electricity network due to the variation and uncertainty nature of the RESs. Some existing energy infrastructures, such as heat, gas, and transport, all have some level of inbuilt storage capacity and demand response (DR) potentials that can be exploited in an energy system integration to give the electricity network some level of flexibility and promote an efficient transition to a low-carbon, resilient, and robust energy system. The process of integrating different energy infrastructure is known as multi-vector energy systems (MESs). This paper reviews different studies on the planning of MESs using the energy hubs (EHs) approach. The EHs model used in this paper links different energy vectors such as gas, electricity, and heat energy vectors in its planning model, as opposed to planning each energy vector independently, in order to provide more flexibility in the system, minimise total planning cost, and encourage high penetration of renewable energy source for future energy demands. In addition, different uncertainty modelling and optimization methods that have been used in past studies in planning of EH are classified and reviewed to ascertain the appropriate techniques for addressing RESs uncertainty when planning future EH. Numerical results show 12% reduction in the planning cost in the case of integrated planning with other energy vectors compared to independent planning.