Demand Side Response Participation in Reserve Configuration Optimization Based on Decomposition and Coordination

Abstract

As the proportion of new energy sources in the grid increases and the structure of the ultra-highvoltage grid becomes more complicated, the variability of the external environment and the complexity of the grid itself bring many new challenges to the power system reserve configuration problem. The multilevel and multitime scale characteristics of the grid reserve are analyzed in this paper, and the reserve is classified according to the response time characteristics combined with the system function. We establish a demandside response participation system reserve configuration optimization model, including synchronous generator generation and reserve models, demand-side scheduling and reserve models, grid power generation planning and reserve optimization mathematical models. Based on the idea of decomposition coordination, the current power generation plan and reserve optimization problem are decomposed into a finite fault state safety constraint unit combination subproblem, Monte Carlo secondary negative reserve constraint check subproblem, frequency safety constraint checking subproblem based on large-disturbance long-process time domain simulation analysis, and fault state static safety constraint check subproblem based on minimum load shedding. Considering the demand side response to the reserve configuration of the system, combined with the problem of previous unit association, the optimal allocation of the reserve coal consumption units is realized by determining the start and stop status of the unit and the unit output.

Research on joint optimization model and algorithm of multi‐area generation and reserve with considering its availability

“…The research on spinning reserve in power system can be divided into two major categories, one is the determination of the total reserve demand [2][3][4][5][6], and the other one is the reasonable allocation of reserve resources among different providers [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. In a traditional way, the reserve capacity was determined according to the maximum capacity of integrated generating units and load fluctuation.…”

“…However, the maximum power shortage was regarded as the most severe scenario, while this is not appropriate if the transmission capacity constraints are considered, and the coupling among multiple periods was not covered in the literatures. In addition to the optimization of reserve allocation among conventional units, the use of load response resources [14,15] and HVDC [16] as the reserve resource providers can effectively enhance the flexibility of system regulation to cope with more large-scale renewable energy integration.…”

Application of Decomposition and Coordination Optimization Methodology in Reliability Allocation of Systems

“…Some other schemes were researched such as stochastic dual dynamic parallel programming [6], Dantzig Wolfe decomposition algorithms [7], and the distributed local selfish optimization models [8], to deal with high-dimensional state-spaces and optimize power generation planning or large-scale block angular linear programming such as transmission and distribution grids. In addition, probabilistic distributed assessments or nonlinear programing [9]- [11] were studied via decomposition and coordination approach. All of these investigations improved the computational efficiency or minimized the cost for the systems [12]- [14].…”

Enabling Active Distribution Systems’ Participation in Tertiary Frequency Regulation Through Coalitional Game Theory-Based Reserve Allocation

“…In [18], a data-oriented technique for estimating secondary and tertiary reserves is introduced and evaluated on an actual system. The challenges of power system reserve configuration in a grid with increasing new energy sources and complex ultra-high-voltage grid structures have been analyzed in [19] by establishing an optimization model for demand-side response participation in reserve configuration, ensuring system stability and reliability through decomposition coordination and unit allocation. The paper [20] has focused on optimizing a local energy community's participation in providing tertiary frequency reserves using electric vehicles and a battery storage system, with a two-stage scheduling approach for maximizing profits and demonstrating the impact of control parameters on realtime profitability.…”