Renewable Generation and Transmission Expansion Planning Coordination with Energy Storage System: A Flexibility Point of View

Abstract

This paper presents a method for coordinated network expansion planning (CNEP) in which the difference between the total cost and the flexibility benefit is minimized. In the proposed method, the generation expansion planning (GEP) of wind farms is coordinated with the transmission expansion planning (TEP) problem by using energy storage systems (ESSs) to improve network flexibility. To consider the impact of the reactive power in the CNEP problem, the AC power flow model is used. The CNEP constraints include the AC power flow equations, planning constraints of the different equipment, and the system operating limits. Therefore, this model imposes hard nonlinearity onto the problem, which is linearized by the use of first-order Taylor’s series and the big-M method as well as the linearization of the circular plane. The uncertainty of loads, the energy price, and the wind farm generation are modeled by scenario-based stochastic programming (SBSP). To determine the effectiveness of the proposed solution approach, it is tested on the IEEE 6-bus and 24-bus test systems using GAMS software.

Evolutionary Algorithm-Based Adaptive Robust Optimization for AC Security Constrained Unit Commitment Considering Renewable Energy Sources and Shunt FACTS Devices

“…However, increase in load related to increase of both the active and reactive loads. Hence, a serious fault could occur in the network expansion, the effects of which will become apparent in the coming years, this issue was confirmed in [21,28].…”

“…(1) presents the objective function of the problem, which was equal to the total fuel, start-up, and shutdown of costs of CGUs [19][20]. Also, the AC-OPF constraints of the transmission network in the presence of CGUs, RESs, and parallel FACTS are respectively given in Equations ( 2) to ( 7) [21][22][23]; these equations correspond to the balance of active power, reactive power, active power and reactive flow through the transmission line, capacity limit of the transmission line, and voltage limit [24][25][26][27] of the network bus, respectively [28]. The CGU scheduling constraints are formulated in Equations ( 8) to (17).…”

“…In (21), the number of columns in the matrix u is the number of simulation hours nt, and the number of rows is 2nl + nr. The terms nr and nl represent the number of RESs and loads, respectively.…”

“…This network had a base power and voltage of 100 MW and 230 kV, with the allowed voltage range of [0.95, 1.05] p.u. [21]. The specifications of transmission lines were extracted from [28], the data for generation units and parallel FACTSs are listed in Table 2 [28,[37][38].…”

An expansion planning method for extending distributed energy system lifespan with energy storage systems

“…Even the degradation process is not well-known, though some studies have tried to consider the degradation of batteries technically in the optimization of EP. On the other hand, some studies consider EP without ESS degradation in the recent literature (Ansari et al, 2021;Larsen and Sauma, 2021;Saber et al, 2018;Trpovski et al, 2020;Tsianikas et al, 2021). The operational cost of the ESS may cover degradation resulting in capacity loss.…”