Bi-level Optimal Operation Model of Mobile Energy Storage System in Coupled Transportation-power Networks

Abstract

The operation characteristics of energy storage can help the distribution network absorb more renewable energy while improving the safety and economy of the power system. Mobile energy storage systems (MESSs) have a broad application market compared with stationary energy storage systems and electric vehicles due to their flexible mobility and good dispatch ability. However, when urban traffic flows rise, the congested traffic environment will prolong the transit time of MESS, which will ultimately affect the operation state of the power networks and the economic benefits of MESS. This paper proposes a bi-level optimization model for the economic operation of MESS in coupled transportation-power networks, considering road congestion and the operation constraints of the power networks. The upper-level model depicts the daily operation scheme of MESS devised by the distribution network operator (DNO) in order to maximize the total revenue of the system. With fuzzy time windows and fuzzy road congestion indexes, the lower-level model optimizes the route for the transit problem of MESS. Therefore, road congestion that affects the transit time of MESS can be fully incorporated in the optimal operation scheme. Both the IEEE 33-bus distribution network and the 29-node transportation network are used to verify and examine the effectiveness of the proposed model. The simulation results demonstrate that the operation scheme of MESS will avoid the congestion period when considering road congestion. Besides, the transit energy consumption and the impact of the traffic environment on the economic benefits of MESS can be reduced.

Energy storage complementary control method for wind‐solar storage combined power generation system under opportunity constraint

“…In this paper, the battery is used as the energy storage equipment of the wind power storage combined power generation system. In the constraint of the energy storage device, the charge and discharge power and the state of charge (battery power) are taken as the key considerations of the constraint [11]. A formula for an energy storage device constraint can be expressed as $$$$\begin{equation}\left\{ \def\eqcellsep{&}\begin{array}{l} {q}_{b\min } \le {q}_{bt} \le {q}_{\scriptstyle b\max \hfill\atop \scriptstyle \hfill}\\ {E}_{\min } \le {E}_t \le {E}_{\max } \end{array} \right.\end{equation}$$$$wherein $${q}_{b\min }$$ is used to represent the maximum charging power, and its value is negative; $${q}_{\scriptstyle b\max \hfill\atop \scriptstyle \hfill}$$ represents the maximum discharge power, the value of which is positive.…”