Evaluating the Economic Impact of Users’Personality on Selection of Demand Response Programs

Demand response creates an opportunity for consumers to play an important role in the development of smart grids.With the advent of renewable energies and their uncertainties,demand response provides a possible solution to resolve these uncertainties.In addition to demand response schemes in the presence of renewable energy,the personality types of consumers can influence the choice of tariffs and change their electricity costs.In this paper,first,household residents with different types of personalities are considered as energy consumers.Secondly,the uncertainty of renewable energy sources is considered for the distributed generations scheduling by using a stochastic method called the Here-and-Now approach and considering three tariffs,time of use,real-time pricing,and direct load control in the residential sector to reduce total costs.Finally,the tariff choice is compared based on people preferences via various personality types,the Myers-Briggs Type Indicator test,and simulations results.Also,a probabilistic unit commitment methodology is used for distributed generations scheduling to minimize the total cost.The financial losses caused by non-optimal tariffs selection are determined through the comparison of tariffs.Simulation results show that time of use and direct load control tariffs are optimal ones in summer and winter seasons,respectively.

Stability analysis and decentralized control of inverter-based ac microgrid

This work considers the problem of decentralized control of inverter-based ac micro-grid in different operation modes.The main objectives are to(i)design decentralized frequency and voltage controllers,to gather with power sharing,without information exchange between microsources(ii)design passive dynamic controllers which ensure stability of the entire microgrid system(iii)capture nonlinear,interconnected and large-scale dynamic of the micro-grid system with meshed topology as a port-Hamiltonian formulation(iv)expand the property of shifted-energy function in the context of decentralized control of ac micro-grid(v)analysis of system stability in large signal point of view.More precisely,to deal with nonlinear,interconnected and large-scale structure of micro-grid systems,the port-Hamiltonian formulation is used to capture the dynamic of micro-grid components including microsource,distribution line and load dynamics as well as interconnection controllers.Furthermore,to deal with large signal stability problem of the microgrid system in the grid-connected and islanded conditions,the shifted-Hamiltonian energy function is served as a storage function to ensure incremental passivity and stability of the microgrid system.Moreover,it is shown that the aggregating of the microgrid dynamic and the decentralized controller dynamics satisfies the incremental passivity.Finally,the effectiveness of the proposed controllers is evaluated through simulation studies.The different scenarios including grid-connected and islanded modes as well as transition between both modes are simulated.The simulation conforms that the decentralized control dynamics are suited to achieve the desired objective of frequency synchronization,voltage control and power sharing in the grid-connected and islanded modes.The simulation results demonstrate the effectiveness of the proposed control strategy.

Optimum allocation of FACTS devices in Fars Regional Electric Network using genetic algorithm based goal attainment

This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensators (TCSCs) and static var compensators (SVCs) are the utilized FACTS devices. Our objectives are active power loss reduction, newly introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, were considered in the optimum allocation. A goal attainment method based on the genetic algorithm (GA) was used to approach the global optimum. The estimated annual load profile was utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. Fars Regional Electric Network was selected as a practical system to validate the performance and effectiveness of the proposed method. The entire investment of the FACTS devices was paid off and an additional 2.4% savings was made. The cost reduction of peak point power generation implies that power plant expansion can be postponed.