Multi-Objective Optimization of EV Charging and Discharging for Different Stakeholders

As a dynamic energy storage system,electric vehicles(EV)play important roles in future power grids.In this paper,a model for EV aggregator participation in the electricity market has been built with a focus on the feasibility issue of the model arising from economic interest inconsistencies between different stakeholders:EV owners and aggregator.In the model,the EV aggregator attends day-ahead energy and reserve markets for profit maximization by scheduling charging and discharging behaviors of EVs.This issue exists since different stakeholders have different interests which are not necessarily consistent,e.g.profit maximization leads to increasing EV owners'charging fee.To investigate the economic relationship between the two stakeholders,two multi-objective optimization methods(weighted sum and$\varepsilon$-constraint methods)are proposed to take the aggregator profit and EV owners'charging fee into account in the model.A sensitivity analysis is applied to examine the aggregator profit under different price scenarios,which reveals the internal relationship between EV owners'charging fees and aggregator profit.The proposed EV charging and discharging strategy in this paper could be used to determine the settlement price between the aggregator and owners to ensure the feasibility of participation from both EV owners and stakeholders in electricity markets.

Optimal proportion of wind and PV capacity in provincial power systems based on bilevel optimization algorithm under low-carbon economy

In order to boost contributions of power systems to a low-carbon economy,the installed capacity of renewable power generation,such as wind and photovoltaic(PV)power generation should be well planned.A bilevel formulation is presented to optimize the proportion of wind and PV capacity in provincial power systems,in which,carbon emissions of generator units and features of renewable resources are taken into account.In the lowerlevel formulation,a time-sequence production simulation(TSPS)model that is suitable for actual power system has been adopted.In order to maximize benefits of energy conservation and emissions reduction resulting from renewable power generation,the commercial software called General Algebraic Modeling System(GAMS)is employed to optimize the annual operation of the power system.In the upper-level formulation,the optimal pattern search(OPS)algorithm is utilized to optimize the proportion of wind and PV capacity.The objective of the upper-level formulation is to maximize benefits of energy conservation and carbon emissions reductions optimized in the lowerlevel problem.Simulation results in practical provincial power systems validate the proposed model and corresponding solving algorithms.The optimization results can provide support to policy makers to make the polices related to renewable energy.

Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Successful distributed photovoltaic (PV) planning now requires a hosting capacity assessment process that accounts for an appropriate model of PV output and its uncertainty. This paper explores how the PV hosting capacity of distribution networks can be increased by means of spatial correlation among distributed PV outputs. To achieve this, a novel PV hosting capacity assessment method is proposed to account for arbitrary geographically dispersed distributed PVs. In this method, the empirical relation between the spatial correlation coefficient and distance is fitted by historical data in one place and then applied to model the joint probability distribution of PV outputs at a neighboring location. To derive the PV hosting capacity at candidate locations, a stochastic PV hosting capacity assessment model that aims to maximize the PV hosting capacity under thermal and voltage constraints is proposed. Benders decomposition algorithm is also employed to reduce the computational cost associated with the numerous sampling scenarios. Finally, a rural 59-bus distribution network in Suzhou, China, is used to demonstrate the effectiveness of the proposed PV hosting capacity assessment methodology and the significant benefits obtained by increasing geographical distance.