Ali Arefi

Electronic-based technologies are becoming more interesting because of their advantages, such as quick response, higher lifespan, etc. Soft open point is a cutting-edge device that has been recently introduced for distribution grids. It is generally installed in tie switches, resulting in a transfer of the powers among two regions of the network. However, there are other distributed generation resources in the active distribution networks, like smart photovoltaic inverters (SPIs), energy storage systems (ESSs), diesel generators (DGs), etc. Accordingly, taking into account the coordination among mentioned technologies is essential. This paper aims to provide a strategy for simultaneous management of all mentioned resources based on a convex model, leading to taking advantage of commercial solvers, e.g., CPLEX. The uncertainties of loads and renewable energies directly affect such management schemes in addition to mentioned coordination. This paper, therefore, uses a robust framework entitled information-gap decision theory, which leads to reaching the solutions under harsh uncertainties. Here, the risk-averse strategy is utilized to model the uncertainties to achieve a robust model. The proposed method is finally evaluated under various cases by executing on a modified IEEE 33-bus test network. Through the results, SOP in the presence of SPIs, ESSs, and DGs can be an excellent remedy to improve the efficiency of networks.

A simple traditional inverter which generates a square wave is not satisfactory for grid integration. A pure sinusoidal wave is highly desired for grid tied inverter. Multilevel inverter (MLI) has emerged a key technological development in the field of energy control for high-power medium-voltage (6–36 kV) by generating sinusoidal output waveform without using large and bulky line filter. The cascaded H-bridge (CHB) inverters produce more output voltage levels (e.g., more sinusoidal) in the medium-voltage range, hence minimize the harmonic components. In this paper, a fifty-five level (55L) CHB converter is designed, simulated, and analyzed for 11kV system using a new modified third harmonic injected pulse width modulation-based (MTHPWM) switching technique. Performance of existing switching techniques and proposed switching technique with a 55L, 3- ϕ , 11kV CHB inverter is evaluated in terms of total harmonic distortion (THD) and inverter loss. The proposed modulation scheme results very promising THD profile (3.41%) and reduces switching losses over other conventional modulation techniques. All the simulated results are carried out in the MATLAB/Simulink environment.

This paper proposes a method to estimate the end-of-life failure probabilities of transformers and cable lines in distribution networks considering electric vehicle charging processes. The estimation of the probabilities is obtained using a model based on Arrhenius-Weibull distribution considering different aging speed according to load variation. The EV penetration may significantly accelerate the aging speed and the loss-of-life thus has an adversary influence on failure probability and network reliability. The impacts of different penetration of electric vehicles (EVs) on the thermal aging of transformers and lines are estimated on a distribution test feeder. The simulation results illustrate the calculation and capabilities of the proposed method.

This paper presents a family of fault-tolerant single-phase inverter topology for uninterruptible power supply (UPS) systems. The core structure is a 15-level inverter, consisting of two unidirectional switches, eight bidirectional switches, and six DC voltage sources. The proposed topology can facilitate realizing fault-tolerant multi-module inverters. If one of the power sources or semiconductor devices fails in one of the modules, the remaining modules can alternatively deliver all the expected voltage levels. Thus, this efficiently eliminates the possibility of UPS system failure for critical applications. The proposed topology is compared with the conventional 15-level inverters regarding the number of voltage sources, switches, and drivers to prove its advantages. The gate signals for the switches are produced employing the fundamental frequency switching technique. Further, the efficacy and performance of the proposed topology are supported with the simulation and experimental validations.

In this paper, a new single-phase single-ended primary-inductor converter (SEPIC) topology-based ac-dc converter is proposed pursuing only a singular switch for power conversion. The proposed converter exhibits higher input power factor, moderated total harmonic distortion (THD) in the input line current complying with IEEE-519 standards and high voltage gain compared to its traditional counterpart. In addition, the proposed topology displays promising performance under unexpected load introduction and load variations. Furthermore, the proposed converter causes a very low power loss comparing to its conventional topologies for the utilization of only a single switch to signal control. All the simulations have been performed in MATLAB/Simulink environment which upholds the performance of the topology and validates the philosophy of proposed converter.

This study illustrates the effectiveness of customer-side voltage regulation in unbalanced four-wire distribution networks, under increasing levels of distributed generation, with the overarching aim of reducing voltage magnitude and voltage unbalance violations. To this aim a series of single-phase voltage regulator (VR) devices are proposed to be installed between point of common coupling (PCC) and the customer point of access (PoA). A VR placement algorithm is developed to identify the optimum locations and sizing of the VR devices considering network constraints. Furthermore, a techno-economical analysing is carried out on a real four-wire distribution network in Australia using real load data to evaluate the performance of the VR implementation. The network is tested with different Solar Photovoltaic (PV) penetration levels from 30 to 100 percent, utilising three different loads models-constant power, constant impedance and an equal impedance-power ratio. The simulation results show that the proposed VR methodology is effective in addressing voltage magnitude and unbalance violations for most of the PV penetration levels.

This paper develops an effective approach for the locational marginal price calculation for local generations in an active distribution network containing different types of distributed generators (DGs). The proposed approach is based on encouraging private units to reduce power loss and greenhouse gas (GHG) emissions. To this end, firstly, the distribution system operator (DSO) surplus profit, obtained by the reduction of power loss and GHG gas emission due to the operation of private units in the network, is considered as a financial source for encouraging private units. Then, according to the contribution of each private DG, the locational marginal price is calculated. The proposed approach is an effective and incentive-based approach for DSO to retain control over private units to reduce power loss and GHG emissions. The simulation results on a modified 118-bus standard distribution test system demonstrate the efficiency of the proposed approach compared to the previous approaches.

Virtual power plants (VPPs) are becoming critical parts of energy systems to increase renewable energy integration and to reduce the cost of electricity. To maximize the benefits to customers and VPP owners, the consumers' engagement is important for adding flexibility to the electricity load of the VPP. In this paper, the impact of customer contributions into a VPP energy management system through gamification is studied. To this aim, the contribution of customers within a realistic VPP of 67 dwellings in Western Australia is modelled. This model is included in a robust optimized procedure to maximize the profit of a VPP owner over a year. In this platform the uncertainties associated with renewable energy generation and market electricity are considered to find the optimum solution for the worst case scenario of uncertainties. The simulation results show that the gamified customer involvement has positive impacts on increasing the profit of the VPP.

The marginal cost of reliability improvement (MCRI) is a very useful measure to compare the cost-effectiveness of various standalone microgrid (SMG) systems. This measure helps in decision making on reliability level and imports and exports between SMGs. The MCRI can elucidate how a SMG system is going to deal with the change of reliability requirements by customers and energy traders. This paper proposes an MCRI evaluation algorithm for a microgrid (MG) over its 25-year lifespan. A case study is evaluated, which consists of renewable energy resources (RES) and a battery energy storage system (BESS) as reliability improvement (RI) alternatives. Two sensitivity analysis study are performed to answer the following research questions: What if is the cost of energy resources changes? and What if demand response (DR) is included as an alternative to RI. Furthermore, whether maximum reliability can be achieved with 100% renewable generating resources is also evaluated. The Monte Carlo Simulation (MCS) method is used to model the equipment failure. The linear regression approach is used to create an equation for loss of load reduction (LOLR), for the addition of resource mix as a function of LOLR and for the addition of individual RI alternatives. A Matlab optimization tool is used to find the MCRI.

The clustering of historical electricity consumption data is an effective means of developing representative load profiles for long-term energy planning. This paper presents a multi-dimensional approach for clustering, considering scattering and separation metrics and the number of clusters. A novel hybrid approach to solve the clustering function is also proposed: a combination of Invasive Weed Optimization (IWO) and wavelet mutation strategy. The hybrid method is applied to half-hourly metered electricity consumption data from the Civic Centre of a large local (municipal) government in Perth, Western Australia, to create representative seasonal load profiles. The novel clustering approach is then tested against the well-known k-means method using Davies-Bouldin and silhouette indices. In each seasonal clustered profile, the hybrid method is found to outperform the k-means method. The hybrid method has been identified as an effective clustering approach for analyzing the behavior of loads and assisting the identification of suitable energy efficiency initiatives.