Given that the capital cost of energy storage systems is still high, the concept of energy sharing attracts more attention. In this paper, an energy sharing model in the forms of hydrogen and electricity is proposed. In this integrated sharing system, besides the aggregators who own power-to-gas (P2G) devices, plug-in hybrid electric and hydrogen vehicles (PH2EVs) aggregators become the new coupling points of the electricity network and gas network, because they can either consume electricity or hydrogen. In the objective function, the total social welfare considering energy dispatch in different systems is maximized. The distributed optimization method is applied to solve the formulated problem. In this way, the privacy of each aggregator can be protected. When the aggregator solves its sub-problem, it is not necessary to obtain all the system information. Besides, the computational complexity is reduced through the distributed optimization. Simulations are conducted on a 35-bus electricity network coupled with a 15-bus gas network. The simulation results reveal that the sharing amount of different kinds of energy can be obtained and the unified market clearing prices of each kind of energy can be achieved. It can be concluded that with the integrated energy sharing of hydrogen and electricity, the total system cost is the lowest and the largest total social welfare can be reached. Besides, the distributed energy storage can be more effective to improve the system stability.

Under the pressure of climate change, the transportation sector is under electrification and electric vehicles (EVs) are encouraged to reduce its reliance on fossil fuels. However, in those regions where coal is a dominating power generation fuel source, different opinions about whether EVs can help emission reduction exist. In other words, whether EVs can help emission reduction depends on the energy system configuration and the power generation mix. To achieve the overall emission reduction in both systems, a collaborative planning strategy for electricity and transportation systems is proposed. In the electricity distribution network, the renewable energy source is planned to cope with future demand growth due to the increasing use of EVs. In the transportation network, hydrogen fuel cell vehicles (FCVs) are introduced to realize the coordinated development of different types of vehicles. The location of the hydrogen refueling stations can be planned and the penetration ratio of internal combustion vehicles, EVs and FCVs are optimized. The proposed planning model is verified on the 46- bus electricity distribution network and the 21-bus transportation network. The Mixed-integer Linear Programming (MILP) and Sub-gradient methods are employed to solve the proposed optimization model. According to the simulation results, the proposed model can achieve the lowest emission, since the electricity and transportation systems can cooperate well.

Electric vehicles (EVs) have the promising potential to be effective in mitigating greenhouse gas emissions in the transportation sector. Hence, the penetration of EVs in some countries experiences steady growth. However, the proliferation of EVs can cause negative impacts on the power distribution network (PDN) and the transportation network (TN). Thus, in this paper, a dynamic pricing strategy for electric vehicle charging stations (EVCSs) is proposed to facilitate EVCSs to earn higher profits while alleviating the potential negative impacts on both PDN and TN. First, a pricing strategy, considering the competition effect established based on the TN, is formulated to facilitate the EVCS to attract the defined competitive charging demand. Second, a two-step approach is proposed to mathematically formulate the responsiveness of demand towards the charging price. Third, EV user behaviors are incorporated based on both an admission control scheme and a queueing model to further adjust the charging demand. We have conducted simulations to verify the effectiveness of the pricing strategy in a PDN and TN coupled system, which contains approximately 2000 EVs. Results show that the proposed pricing strategy can facilitate the EVCS to gain 14.2% more net charging profit on average compared with the other three cases. Moreover, the operational stability of the EVCS can be ensured because the proposed pricing strategy can result in the least queueing length volatility with moderate profit variance compared with the other three cases. Furthermore, the proposed pricing strategy can achieve spatial load shifting by incentivizing EVs to alter their station-selection decisions to avoid possible power congestion in the electricity network.

The acceleration of distributed energy resources and carbon pricing policies has compelled utilities to act and to prioritize carbon-constrained infrastructure augmentation in their capital programs. To implement various carbon emission reduction policies, power system transmission planning has become more challenging. The existing energy system will face massive retirement of coal-fired power plants (CFPPs), large scale integration of renewable energy and network expansion. In this paper, an electricity network planning and transformation roadmap, which has two milestones, is put forward. In the first milestone, a mathematical model is proposed based on the average cost of carbon emission reduction to realize the cooperation of CFPPs retirement and renewable energy devices investment. It can help the network carry out the transition from a fossil-fuel dominated system to a low-carbon oriented system. Because of the promising prospect of power-to-gas (P2G) technology, in the second milestone, a method based on carbon emission flow (CEF) is employed to help the power-to-gas stations (P2GSes) to select the construction site and capacity. According to simulation results on the IEEE 24-bus system, our method can reach the emission reduction target more economically and effectively, and the P2GSes can produce and absorb clean energy.

Hydrogen production has become an emerging technology and offered a pathway to sustainable energy utilization in transportation systems. In this paper, we propose a coordinated planning of the electricity network and hydrogen refueling and production station planning strategy for hydrogen fuel cell electric vehicles (FCEVs). In the proposed system structure, a hydrogen supply chain for FCEVs mainly composes hydrogen refueling stations (HRSs), hydrogen production stations (HPSs), hydrogen storage, and hydrogen delivery network. To enhance the system's flexibility, hydrogen delivery combines both gas pipeline delivery and truck logistics delivery. In the mathematical models, the synergistic effect and coupling relationship of the electricity network, gas network, and transportation network are presented. To ensure the efficiency and effectiveness of the hydrogen refueling system, a quality of service (QoS) and reliability assessment method is presented. The proposed methodology is verified in case studies. It is found out that compared with the single delivery methods, the proposed multi-network coordinated planning has the lowest total cost with less unserved energy. Besides, through QoS and reliability assessment, enough hydrogen reserves can be maintained to cope with contingencies.

The proliferation of electric vehicles (EVs) is an inevitable trend to realize transportation electrification. However, the increasing charging demand of EVs also brings challenges to future smart grids. To cope with the EV diffusion, this paper presents an adaptive fast charging station (FCS) strategy that considers the integrated network planning and quality of service (QoS) guarantee. First, based on the EV diffusion model and the proposed EV-integrated traffic assignment model, the charging demands at different regions and stages are forecasted. Based on the predicted spatial and temporal EV charging demand, a multistage stochastic distribution expansion planning model is presented, where the distribution network assets and FCSs are jointly considered. To guarantee the quality of the fast-charging services under EV diffusion, a QoS assessment is conducted based on the average waiting time and the average number of dissatisfied leaves. Finally, the proposed planning model allows several alternatives at both the distribution and transmission levels. The cost of electricity network expansion planning is considered as the adaptive cost arisen from the EV diffusion and the increase of the other electrical loads. We aim to find a planning strategy that can adapt to different penetration levels of EVs. The proposed framework and methodology are verified on the IEEE 24-bus power system encompassing 6 IEEE 33-bus distribution networks. It is found out that the proposed strategy shows superiority in both QoS and total costs.