An incentivized and optimized dynamic mechanism for demand response for managing voltage in distribution networks

The voltage regulation in distribution networks is one of the major obstacles when increasing the penetration of distributed generators (DGs) such as solar photovoltaics (PV), especially during cloud transients, causing potential stress on network voltage regulations. Residential demand response (DR) is one of the cost-effective solutions for voltage management in distribution networks. However, the main barriers of DR implementation are the complexities of controlling a large number and different types of residential loads, satisfying customers’ preferences and providing them fair incentives while identifying the optimum DR implementation locations and sizing as well as cooperating with the existing network equipment for the effective voltage management in the networks. A holistic and practical approach of DR implementation is missing in the literature. This study proposes a dynamic fair incentive mechanism using a multi-scheme load control algorithm for a large number of DR participants coordinating with the existing network equipment for managing voltage at medium voltage (MV) networks. The multi-scheme load control is comprised of short-interval (10-minute) and long-interval (2-hour) DR schemes. The dynamic incentive rates are optimized based on the energy contribution of DR participating consumers, their influence on the network voltage and total power loss improvement. The proposed method minimizes the DR implementation cost and size, fairly incentivizes the consumers participating in the DR and priorities their consumption preferences while reduces the network power losses and DGs’ reactive power contributions to effectively manage the voltage in the MV networks. An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. The proposed approach is comprehensively tested using the IEEE 33-bus and IEEE 69-bus networks with several scenarios considering a large number of DR participants coordinated with the DGs and on-load tap changer (OLTC) in the networks

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4 (62.3 (55.1�70.8) million) to 6.4 (58.3 (47.6�70.7) million), but is predicted to remain above the World Health Organization�s Global Nutrition Target of <5 in over half of LMICs by 2025. Prevalence of overweight increased from 5.2 (30 (22.8�38.5) million) in 2000 to 6.0 (55.5 (44.8�67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic. © 2020, The Author(s)

Author Correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017 (Nature Medicine, (2020), 26, 5, (750-759), 10.1038/s41591-020-0807-6)

An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s)

Author Correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017 (Nature Medicine, (2020), 26, 5, (750-759), 10.1038/s41591-020-0807-6)

An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s)

Penetration maximisation of residential rooftop photovoltaic using demand response

The increasing penetration of roof-top photovoltaic system has highlighted immediate needs for addressing power quality concerns, especially where PV generation exceeds the household demand. This study proposes an approach for optimal implementation of demand response in residential sector to eliminate voltage violations, especially during high PV generation periods. The proposed approach uses a load flow sensitivity method to optimise the demand response implementation location and size for PV penetration maximisation in distribution networks. The simulation results on IEEE 13-bus test system show that using the proposed approach every 1 kW of DR implementation increases PV penetration by 2 kW

Customer-Side voltage regulation to mitigate PV-induced power quality problems in radial distribution networks

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

A medium voltage CHB Inverter with a modified THPWM for Step-Up-Transformer-Less and Line-Filter-Less Grid Integration

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

Improvement of voltage magnitude and unbalance in LV network by implementing residential demand response

Maintaining voltage levels in low voltage (LV) distribution network within the standard limits is the main constraining factor in increasing network hosting ability for high penetration of rooftop photovoltaic (PV). Distribution system operator must be able to take corrective approach to avoid critical voltage unbalance and magnitude violations where rooftop PV generation is high. This study presents an effective method for voltage management in distribution networks through implementation of optimal residential demand response (DR) and transformer tap setting using a particle swarm optimization algorithm. The method is comprehensively verified on a real Australian distribution network with considerable unbalance and distributed generations. The simulation results show that PV penetration of the network can be further increased with the proposed approach

Risk-Based operation of soft open points in distribution grids integrated with photovoltaic resources and energy storage systems

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