Unit Commitment Accommodating Large Scale Green Power

Abstract

As more clean energy sources contribute to the electrical grid, the stress on generation scheduling for peak-shaving increases. This is a concern in several provinces of China that have many nuclear power plants, such as Guangdong and Fujian. Studies on the unit commitment (UC) problem involving the characteristics of both wind and nuclear generation are urgently needed. This paper first describes a model of nuclear power and wind power for the UC problem, and then establishes an objective function for the total cost of nuclear and thermal power units, including the cost of fuel, start-stop and peak-shaving. The operating constraints of multiple generation unit types, the security constraints of the transmission line, and the influence of non-gauss wind power uncertainty on the spinning reserve capacity of the system are considered. Meanwhile, a model of an energy storage system (ESS) is introduced to smooth the wind power uncertainty. Due to the prediction error of wind power, the spinning reserve capacity of the system will be affected by the uncertainty. Over-provisioning of spinning reserve capacity is avoided by introducing chance constraints. This is followed by the design of a UC model applied to different power sources, such as nuclear power, thermal power, uncertain wind power, and ESS. Finally, the feasibility of the UC model in the scheduling of a multi-type generation unit is verified by the modified IEEE RTS 24-bus system accommodating large scale green generation units.

Energy Commitment for a Power System Supplied by Multiple Energy Carriers System using Following Optimization Algorithm

“…where E e 1 is the input fuel for different power plants and T u, f is the power plant efficiency matrix. The source energy carrier for electricity generation is determined using (7).…”

“…[6], the authors proposed the implementation of the UC in the presence of energy storage systems and its optimal size for a region in northern Chile. Solving the UC problem in the presence of wind, nuclear, and thermal power plants has been studied by considering the security constraints of the transmission line and the influence of wind power uncertainty on the spinning reserve capacity of the system in China [7]. A new method based on the Particle Swarm Optimization (PSO) algorithm, [8], and the solution of the UC problem using genetic algorithm was proposed in [9].…”

MILP formulation of the UC-problem with boundary conditions on the autonomous forecasting horizon

“…Thus, operational costs for maneuvering, starting and stopping units, i.e. costs for ensuring the flexibility of power systems, are additionally taken into account in the formulation of the tasks of long-term development of power systems [5][6][7][8][9][10].…”

Research on Optimal Dispatching Strategy for Micro-Energy-Grid of Protected Agriculture

“…To achieve the goal of poverty alleviation in rural areas by 2020, China implements the strategy of supporting the poor in rural areas of western China. Since renewable energy is uncertain, robust optimal scheduling algorithms [17,18] are usually applied to cope with this issue. To accommodate more renewable energy sources, flexibility from the power load is frequently adopted [19,20].…”