Optimal coordinative operation strategy of the electric–thermal–gas integrated energy system considering CSP plant

Abstract

Concentrating solar power (CSP) plant, which has great controllability and scheduling flexibility, is a promising renewable energy power generation technology. The reasonable scheduling of a CSP plant can effectively reduce the operating cost of the integrated energy system (IES). In this context, a day‐ahead optimal coordinative operation model of the electric–thermal–gas IES considering CSP plant is proposed in this study with the objective function of minimising the operating cost of the IES. In the proposed model, the transmission delay characteristic of the thermal network is considered to reflect the large thermal inertia of the thermal network. Then, the incremental formulation for the piecewise linearisation and the second‐order cone relaxation method are utilised to transform the proposed non‐linear model into a mixed integer quadratically constrained programming model, which can be efficiently solved by CPLEX solver. The case study shows that the optimal operation model considering CSP plant has better performance in reducing the operating cost and promoting the wind power penetration when compared with the model considering photovoltaic. In addition, the scheduling flexibility of IES can be enhanced by the virtual thermal energy storage characteristic of the thermal network to reduce the operating cost and promote the wind power penetration of IES.

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

“…Analogously, a digester can be added to the EH to interconnect the EH with a biogas-electric multi-energy system to form a biogas-solar-wind complementary model, which improves the absorption rate of renewable energy and reduces the operation cost of the IES [6]. A concentrating solar power plant model that couples the power grid and the heating network, making the internal components of the EH more diversified, was established in [7]. The results showed that the EH can lower the operation cost and promote the wind power penetration of the IES.…”

“…On the other hand, exploring the optimal algorithms suitable for the OEF problem is also important research in the field of IESs. Numerical algorithms, such as mixed-integer linear programming [7,12,13], Benders decomposition [14], and second-order cone programming [15], are fast in convergence. However, the implementation of the numerical algorithm is complicated, and they may not converge when the objective function is discontinuous or contains multiple extreme points.…”

Optimal day‐ahead scheduling of multiple integrated energy systems considering integrated demand response, cooperative game and virtual energy storage

“…With the rapid escalation of energy consumption, the efficient utilisation of energy in the integrated energy system (IES) has become a hot topic for solving the problem of the energy crisis. IES involves the production, transmission, and utilisation of multiple energy including electricity, heating, cooling, and gas [1,2], which can improve the overall energy utilisation efficiency by using and incorporating multiple energy sources to supply multiple energy demands [3,4]. Demand response (DR) is a significant way for the demand side to participate in grid interaction, which has been widely used for optimal planning [5][6][7][8] and optimal scheduling [9][10][11][12] in power systems to maintain frequency stability and power balance [13,14].…”

Optimal low‐carbon scheduling of integrated local energy system considering oxygen‐enriched combustion plant and generalized energy storages

“…An IDR strategy combining energy substitution and load shifting is developed in [17] to exploit the demand flexibility of multi-energy buildings. For the storage side, the optimal scheduling strategies of actual multiple energy storage devices (AMESDs) in ILES, that is, electricity storage device, heat storage device and gas storage device, are studied in [18][19][20], respectively.…”