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The universal power demand is increasing every day because of population growth, industrial revolution and high standards of living. The renewable energy technologies (RETs) are environmental and cost‐effective solutions to satisfy dynamic load profile based on the application of multiple components of a standalone microgrid system that encompasses photovoltaic (PV), diesel generator (DG), electric storage system and wind turbine generator (WTG). This study reveals more insight into various research questions that have not been completely addressed in past investigations. The contributions of the study are expressed: (i) analyse the effects of RETs on the total cost, (ii) test the total benefits, (iii) estimate the market benefit share of the unit that reflects the benefit of one generation unit in proportion to the whole power system, (iv) maximise and minimise the yearly average power generated by (PV and WTG) and DG. This research work presents the application of fmincon optimising tool to accomplish the objectives of the study owing to some significant characteristics. The outcomes of the work show the validity of the model and can assist the utilities to minimise the costs that are identified with the optimal operation of their power systems. [ABSTRACT FROM AUTHOR]

Summary: The addition of photovoltaic (PV)‐based distributed generators introduces several challenges to power system protection and control engineers. In a multi‐source distribution network, power flow becomes bi‐directional, and conventional overcurrent and earth fault protection schemes are threatened. Addition of PV‐based distributed generation could lead to protection blinding, sympathetic tripping, and loss of coordination in conventional overcurrent protection. This paper evaluates the general concerns regarding protection in a PV‐based distributed generation network, by modeling a power system with sequence networks for different types of faults. The power system is simulated with Digsilent PowerFactory. The results show that many of the general concerns can be mitigated by using sequence components to identify faults. A method is presented to adapt conventional overcurrent protection schemes without the need for communication‐assisted protection. [ABSTRACT FROM AUTHOR]

This study explores optimisation of the hybrid power system in the smart grid framework, in conjunction with the model predictive control (MPC) design. This study also creates a strategy that can maximise the use of renewable energy, e.g. photovoltaic, the wind turbine with battery storage and minimise the utilisation of the utility grid for electricity usage in the industry. This is devised by modelling a discrete state‐space model of the hybrid power system for a given industry application. The system design is implemented within a real‐time electricity pricing environment that is integrated with renewable energy to optimally meet the demand according to a specific performance of the consumer. The emphasis of this approach is on its capacity to supply optimal power to the demand side by selecting the appropriate source; and its robustness against uncertainties. The results show that MPC design for hybrid power system not only optimises the energy flow but also improves the overall process of energy management. It was also observed that the optimal solution minimises the delay cost of energy demand from the utility grid according to a given reference from the consumer for the specified tuning parameter values of the performance index. [ABSTRACT FROM AUTHOR]

• Renewable obligation policy is used to increase renewable penetration in the grid. • Stochastic multi-objective economic dispatch model is presented. • This model includes renewable obligation and battery storage. • Inactive line constraints are reduced to improve computational complexity. In this paper, a stochastic multi-objective economic dispatch model is presented under renewable obligation policy framework. This proposed model minimises the total operating costs of generators and spinning reserves under renewable obligation while maximising renewable penetration. The intermittent nature of the wind and photovoltaic power plants is incorporated into the renewable obligation model. In order to minimise the cycling costs associated with ramping the thermal generators, the battery energy storage system units are included in the model to assist the system spinning reserves. Dynamic scenarios are created to deal with the intermittency of renewable energy sources. Due to the computational complexity of all possible scenarios, a scenario reduction method is applied to reduce the number of scenarios and solve the proposed stochastic renewable obligation model. A Pareto optimal solution is presented for the renewable obligation, and further decision making is conducted to assess the trade-offs associated with the Pareto front. To show the effectiveness of the proposed stochastic renewable obligation model, two IEEE test systems are used, i.e., the modified IEEE 30-bus and IEEE 118-bus system. In both test systems, the proposed model can attain high renewable penetration while minimising the expected operating cost. In the large IEEE 118-bus test system, the computational efficiency of the renewable obligation model is demonstrated by reducing the line constraints by 87% which minimises the computing time. A comparative study evaluates the impact of the stochastic model to the deterministic one, and it shows that the stochastic model can achieve high renewable penetration. [ABSTRACT FROM AUTHOR]

Smart grid technologies are a catalyst for the modernisation of the electrical system whilst satisfying all electrical power stakeholders. The application of intelligent systems results in more flexibility and reliability. This paper presents a dynamic energy management system for a microgrid connected to a grid for residential application. The system models a smart metering system to collect data from different components of the electrical system. A grid-tied photovoltaic and energy storage system model is optimally designed. The model uses the framework of a smart grid based on demand response and energy pricing to coordinate the energy flow of a home. Three optimal control scenarios are formulated, where the opportunity energy is considered to be injected to the main grid. These scenarios are two linear methods (open and closed-loop models) and a quadratic approach based on model predictive control. It was observed that the energy storage system plays an essential role in the context of energy-saving and gain from the demand side. The models provide benefits in terms of energy-saving and energy cost. The performance of dynamic modelling is validated with the experimental data from the smart metering system. • Formulates linear and quadratic model of smart home energy coordination for the intelligent microgrid application. • Designs optimal energy flow control strategies by the use of a smart metering system based on wireless communication. • Compares the dynamic performance of the energy management schemes based on demand response. • Provides the consumer with an opportunity of selling the energy to the utility for a microgrid connected to the main grid. • Applies system analysis on the energy components of a residential home. [ABSTRACT FROM AUTHOR]