In view of scarcity of traditional energy resources and environmental issues, renewable energy resources (RERs) are introduced to fulfill the electricity requirement of growing world. Moreover, the effective utilization of RERs to fulfill the varying electricity demands of customers can be achieved via demand response (DR). Furthermore, control techniques, decision variables and offered motivations are the ways to introduce DR into distribution network (DN). This categorization needs to be optimized to balance the supply and demand in DN. Therefore, intelligent algorithms are employed to achieve optimized DR. However, these algorithms are computationally restrained to handle the parametric load of uncertainty involved with RERs and power system. Henceforth, this paper focuses on the limitations of intelligent algorithms for DR. Furthermore, a comparative study of different intelligent algorithms for DR is discussed. Based on conclusions, quantum algorithms are recommended to optimize the computational burden for DR in future smart grid.

The green innovations in the energy sector are smart solutions to meet the excessive power requirements through renewable energy resources (RERs). These resources have forwarded the revolutionary relief in control of carbon dioxide gaseous emissions from traditional energy resources. The use of RERs in a heuristic manner is necessary to meet the demand side management in microgrids (MGs). The pricing scheme limitations hinder the profit maximization of MG and their customers. In addition, recent pricing schemes lack mechanistic underpinning. Therefore, a dynamic electricity pricing scheme through linear regression is designed for RERs to maximize the profit of load customers (changeable and unchangeable) in MG. The demand response optimization problem is solved through the particle swarm optimization (PSO) technique. The proposed dynamic electricity pricing scheme is evaluated under two different scenarios. The simulation results verified that the proposed dynamic electricity pricing scheme sustained the profit margins and comforts for changeable and unchangeable load customers as compared to fixed electricity pricing schemes in both scenarios. Hence, the proposed dynamic electricity pricing scheme can readily be used for real microgrids (MGs) to grasp the goal for cleaner energy production.

In high voltage direct current (HVDC) cable systems, study of electric field distortion created by space charge accumulation is very important for examining insulation performance. Therefore, in this paper the influence of space charge on short-time breakdown characteristics of cross-linked polyethylene (XLPE) are studied. Trap energy distribution is an important factor affecting space charge behavior in dielectrics. Dielectrics with various thicknesses exhibit different space charge phenomena due to various trap distribution characteristics, which regulate the injection, migration and accumulation processes of charges. Consequently, trap characteristics can affect many parameters, such as charge accumulation depth and injection barrier. XLPE with thickness less than 100 μm show lower density of deep traps which can accumulate homogeneous bulk charges as compared to thick XLPE with thickness greater than 100 μm. This phenomenon determines the internal field strength distortion rate which is 20% larger for thin XLPE and it is much higher than that for thick XLPE. The external factor which is considered for analysis is applied field strength and it shows a linear proportional affect on the electric field distortion. A quantitative relationship model between applied field strength and distortion field strength of XLPE with different thicknesses was established. Linear extrapolation was used to obtain the trend of applied, distortion, and actual field strengths at different XLPE thicknesses when breakdown occurred. When the thickness of XLPE is less than 100 μm, distortion field strengths is higher than 50kV/mm and increases with decreasing thickness, resulting in a significant effect on the breakdown phenomenon and breakdown strength increases with increasing thickness. And when the thickness of XLPE is greater than 100 μm, the distortion field strengths is less than 50 kV/mm which also confirms the volume effect on breakdown phenomenon and breakdown strength decreases with increasing thickness.

The surface charge and space charge accumulation in paper used in oil–paper insulation system may distort electric field distribution and lead to the flashover and breakdown of insulation system. In this paper, the effect of gas-phase fluorination on the surface charge and space charge characteristics of oil-impregnated Nomex paper was investigated. Nomex T410 was fluorinated at 25 °C using F₂/N₂ mixtures with 20% F₂ in volume at 0.05 MPa for 15, 30 and 45 min. Fourier Transform Infrared Spectroscopy (FTIR) proved that the molecular chain scission and cleavage occurred during gas-phase fluorination. Furthermore, the surface charge and space charge characteristic of the original and fluorinated oil-impregnated paper were measured using an electrostatic voltmeter and Pulsed Electroacoustic (PEA) equipment respectively. Furthermore, the hole and electron trap distribution of the samples were obtained by Isothermal Surface Potential Decay (ISPD) model. The results showed that both the positive and negative charge decay rates were accelerated by gas-phase fluorination and the hole, electron trap energy and density of the fluorinated samples were reduced by fluorination. It is suggested that the space charge dissipation was also accelerated by fluorination, indicating that gas-phase fluorination is an effective approach to modify the charge dynamics of oil-impregnated Nomex paper.