Flexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs

Abstract

This study presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage (ES) expansion planning in the presence of demand response (DR). The flexibility and reliability of the optimal resource expansion planning are ensured by means of appropriate constraints incorporated into the proposed planning tool where thermal generation units, ES systems, and DR programs are considered as flexibility resources. The proposed planning tool is a mixed-integer non-linear programming (MINLP) problem due to the non-linear and non-convex constraints of AC power flow equations. Accordingly, to linearise the proposed MINLP problem, the AC nodal power balance constraints are linearised by means of the first-order expansion of Taylor's series and the line flow equations are linearised by means of a polygon. Additionally, the stochastic programming is used to characterise the uncertainty of loads, a maximum available power of wind farms, forecasted energy price, and availability/unavailability of generation units and transmission lines by means of a sufficient number of scenarios. The proposed planning tool is implemented on the IEEE 6-bus and the IEEE 30bus test systems under different conditions. Case studies illustrate the effectiveness of the proposed approach based on both flexibility and reliability criteria.

Joint Planning and Operation for Renewable- Storage Under Different Financial Incentives and Market Mechanisms

“…Besides, TG operation constraints are given in (1)- (4). The investment and operation constraints of WT are given in (6)- (7). The investment and operation constraints of ESS are given in (9)- (17).…”

“…For a complex power system, coordinated planning and operation can improve the economy, because the interaction of sources, grid, and load are considered [6]. Reference [7] presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage systems (ESS) expansion planning in the presence of demand response. Reference [8] presents a scenario-based stochastic active distribution network planning model considering the multi-type distributed generation and ESS.…”

Two‐stage coupling of coordinated energy management and self‐healing strategies in a smart distribution network considering coupling neighbouring microgrids according to autonomous decentralized restoration technique

“…For each MG, Equation (11) expresses active power balance between MG power sources and active loads, that is, EVs and ESSs. ESS constraints have been formulated by Equations (12)‐(16) for stored energy calculation in ESS battery, the initial value of stored energy, energy limit of ESS, charging and discharging active power limits, respectively 28 . It is worth noting that in Equations (15) and (16), es is a binary variable illustrating the charging/discharging state of ESS, that is, es = 1 if ESS acts as charging model and es = 0 if ESS operates in discharging mode.…”

Robust generation expansion planning considering high penetration renewable energies uncertainty

“…The total investment, maintenance, and fuel costs of both candidate and existing thermal plants are defined in (10). The retirement of old inefficient plants is considered as well.…”

“…operational and investment costs, fuel price, financial constraints, water flow for hydropower units, renewable energy penetration, transmission capacity, and environmental policies. [3][4][5][6][7][8][9][10][11] Climate change has resulted in a need for a rapid transition from fossil fuels to clean energy. Therefore, high penetration of RES with thermal resources becomes an essential requirement to maintain a sustainable future low carbon energy.…”