Voltage and Frequency Stability Constrained Unit Commitment for Power Systems With Heterogeneous Regulation Resources

To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). First, incentive-based DR and price-based DR are introduced to enhance the flexibility of the demand side. To ensure the system can provide frequency support, the unit commitment model incorporates constraints such as the rate of change of frequency, frequency nadir, steady-state frequency deviation, and fast frequency response. Next, for the unit commitment planning problem, the binary particle swarm optimization algorithm is employed to solve the mixed nonlinear programming model of unit commitment, thus obtaining the minimum operating cost. The results show that after considering DR, the load becomes smoother compared to the scenario without DR participation, the overall level of load power is lower, and the frequency meets the safety constraint requirements. The results indicate that a comparative analysis of unit commitment in power systems under different scenarios verifies that DR can promote rational allocation of electricity load by users, thereby improving the operational flexibility and economic efficiency of the power system. In addition, the frequency variation considering frequency safety constraints has also been significantly improved. The improved binary particle swarm optimization algorithm has promising application prospects in solving the accommodation problem brought by large-scale wind power integration.

With the increasing of wind power penetration rate in large power grid, it is of great importance to analyze the impact of wind power on unit commitment of power system and economic dispatch. In the security-constrained unit commitment problem, the introduction of wind turbine can reduce the operating cost of thermal power units and improve the economy of system operation. Because the energy storage system has the characteristics of fast two-way regulation, it can improve the power grid’s ability to absorb wind power and the economy of the system operation. By controlling the charging and discharging of energy storage, it can provide certain flexibility for determining the system unit commitment scheme. Therefore, by considering the forecast error influences of wind power and load, this paper introduces the energy storage system into the security-constrained unit commitment of power system with wind power. Moreover, the constraint condition of rotating reserve opportunity based on trust theory is introduced to avoid over configuration of backup. Thus, the uncertainty of wind power can be effectively improved and the operation cost of the system can be reduced. In addition, the paper compares and analyzes the changes of unit commitment status and system operation cost with or without energy storage, as well as the influence of energy storage parameters and the way of access system (close to wind power side, load side and decentralized access) on the unit commitment model under wind power curtailment condition. Finally, the linearized security-constrained unit commitment model is analyzed and validated with 10 units system.

With the increasing penetration of renewable energy sources, power system operation has to be adapted to ensure the system stability and security while considering the distinguished feature of the Inverter-Based Generator (IBG) interfaced generators. The static voltage stability which is mainly compromised by heavy loading conditions in conventional power systems, faces new challenges due to the large scale integration of IBG units. This paper investigates the static voltage stability problem in high IBG-penetrated system. The analytic criterion that ensures the voltage stability at the IBG buses are derived with the interaction of different IBGs being considered. Based on this, an optimal system scheduling model is proposed to minimize the overall system operation cost while maintaining the voltage stability during normal operation through dynamically optimizing the active and reactive power output from IBGs. The highly nonlinear voltage stability constraints are effectively converted into Second-Order Cone (SOC) form, leading to an overall Mixed-Integer SOC Programming (MISOCP), together with the SOC reformulation of AC power flow and frequency constraints. The effectiveness of the proposed model and the impact of various factors on voltage stability are demonstrated in thorough case studies.

The large-scale commissioning of combined heat and power unit leads to difficulty of peak regulation and wind consumption, and combined heat and power optimized dispatch is one of effective ways to solve this problem. Under existing optimized dispatch models of combined heat and power system, pre-decided unit commitment scheme may cause a large amount of wind curtailment because of excessive operating units and total minimum technical output of units. In view of these problems, through combination of unit commitment and optimized dispatch, an optimized dispatch model of combined heat and power system unit commitment considering heating network characteristics is established. Similarities and differences of heat and power energy transmission are analyzed, heat load partition balance equation as well as positive and negative spinning reserve constrains of thermal system partition are established, and influence of heating network characteristics, including time delay and heat loss, on unit commitment scheme and wind curtailment is studied. A numerical example shows that heating network characteristics influence unit commitment scheme (one unit shuts down an hour ahead and starts up an hour later). Besides, it shows that while meeting power and heat load demand, the model of this paper can timely start up or shut down units according to load change and spinning reserve demand, reduce total minimum technical output of operating units to 632.4 MW, and further improve wind power accommodation quantity to 3410.24 MW·h.

A robust aggregate model and the two-stage solution method to incorporate energy intensive enterprises in power system unit commitment

Strategic Tabu Search for Unit Commitment in Power Systems

This paper presented a method of unit optimization considering voltage stability, which based on the actual engineering application. In order to keep the safety and reliability of power system operation and the quality of power energy, the power balance analysis, power flow analysis, voltage stability analysis, load balance analysis and power exchange are adopted to determine the optimal unit commitment of power system. The results of unit optimization of Shanghai grid of different load levels show that, the proposed method provide a great of helps to solve the problem of unit optimization. It is also an effective mean to ensure the stability of power system running.

Wind and solar (photovoltaic) power generations have rapidly evolved over the recent decades. Efficient and reliable planning of power system with significant penetration of these resources brings challenges due to their fluctuating and uncertain characteristics. In this paper, incorporation of both PV and wind units in the unit commitment of power system is investigated and a risk-constrained solution to this problem is presented. Considering the contribution of PV and wind units, the aim is to determine the start-up/shut-down status as well as the amount of generating power for all thermal units at minimum operating cost during the scheduling horizon, subject to the system and unit operational constraints. Using the probabilistic method of confidence interval, the uncertainties associated with wind and PV generation are modeled by analyzing the error in the forecasted wind speed and solar irradiation data. Differential evolution algorithm is proposed to solve the two-stage mixed-integer nonlinear optimization problem. Numerical results indicate that with indeterminate information about the wind and PV generation, a reliable day-ahead scheduling of other units is achieved by considering the estimated dependable generation of PV and wind units.

Unit commitment is a key and important function in power system operation. The goal of this function is to supply the load demand economically. In order to achieve this goal, unit commitment function determines the condition of the units to be on or off and the amount of generation for generating units of power system for a period of time. The extended form of this operational function, i.e. Security constrained unit commitment, which is the objective of this paper, considers the security constraints, for example transmission lines overload, beside the other constraints in determining the condition of the generating units to be on or off. In this paper, a hybrid method is proposed for dynamic programming, genetic algorithm and particle swarm optimization. In order to solve the unit commitment of power systems considering system security constraints. The condition of the units to be on or off and economic dispatch are determined and solved by considering system security constraints through previously mentioned combination method.

Unit commitment is a key and important function in power system operation. The goal of this function is to supply the load demand economically. In order to achieve this goal, unit commitment function determines the condition of the units to be on or off and the amount of generation for generating units of power system for a period of time. The extended form of this operational function, i.e. Security constrained unit commitment, which is the objective of this paper, considers the security constraints, for example transmission lines overload, beside the other constraints in determining the condition of the generating units to be on or off. In this paper, a hybrid method is proposed for dynamic programming, genetic algorithm and particle swarm optimization. In order to solve the unit commitment of power systems considering system security constraints. The condition of the units to be on or off and economic dispatch are determined and solved by considering system security constraints through previously mentioned combination method.

Frequency-constrained unit commitment for power systems with high renewable energy penetration

This article presents a research on unit commitment(UC), which consider the interaction between conventional power system and district-level integrated energy system(IES). The increasing number and scale of IES projects at distribution network bring incremental effect to the whole energy system. Their influence on power system transmission level unit commitment becomes one of the notable topics. Within these IES projects, gas-power and cooling-heating-power are two main types of `integrated' forms. In this article, a model system is built for UC analysis in which several district-level IESs are connected to a conventional power system. Heating, cooling and electrical forms of energy are integrated in these IESs. The UC problem is modeled and solved by mixed integer linear programming(MILP), the partial load characteristics of these power plants are handled by piecewise linearization. The common piecewise linearization method used in power and gas system is modified to reduce binary variables and constraints. The purpose of this modification is to increase the MILP solving speed. Case studies are carried out to evaluate the influence of IESs on two different time scales. The simulation result shows that the application of IESs can reduce the whole energy system service cost. As the number of applied district-level IESs increases, the cost reduction becomes more significant. The reduction relies on preventing high-cost small capacity plants go into operation, reducing the number of generator startup, and choosing an economical power output level. These benefits are owing to the reinforcement from gas network via CCHPs (Combine cooling, heating and power) and the buffer from multiple forms of energy storage devices (thermal and cooling).

The line random failure caused by multiple uncertainties has become a non-negligible factor which influences the safe operation of power systems. In this paper, a risk-based coordination model of maintenance scheduling and unit commitment is established and the objective is to minimize the total operation cost consisting of the maintenance cost, generation cost and risk cost. A random generation method is proposed to obtain line failure scenarios based on arbitrary failure rate functions. In the base case, security constraints must be satisfied while the potential overflow caused by line outages is calculated in contingency scenarios. In order to handle this mixed integer quadratic programming, a solving strategy based on three-layer iterations is applied. In the exterior iterative layer, Lagrangian relaxation technology is used to coordinate the maintenance scheduling and the risk-based unit commitment until the maintenance schedule is available for the optimized unit commitment plan. In other two iterative layers, Benders decomposition method is adopted to the further problem decomposition. In the middle layer, iterations between the unit commitment sub-problem and the risk-based dispatch sub-problem are used to guarantee the optimality of risk-based unit commitment. In interior iterations, the feasibility of unit commitment plan is checked by an optimal load shedding model. Case studies are performed on a 6-bus test system and a 118-bus test system. Results show that the total operation cost decreases by coordination while the system operating risk can be effectively controlled.

A novel projected two-binary-variable formulation for unit commitment in power systems

With the continued development of renewable energy generation technologies and increasing pressure to combat the global effects of greenhouse warming, plug-in hybrid electric vehicles (PHEVs) have received worldwide attention, finding applications in North America and Europe. When a large number of PHEVs are introduced into a power system, there will be extensive impacts on power system planning and operation, as well as on electricity market development. It is therefore necessary to properly control PHEV charging and discharging behaviors. Given this background, a new unit commitment model and its solution method that takes into account the optimal PHEV charging and discharging controls is presented in this paper. A 10-unit and 24-hour unit commitment (UC) problem is employed to demonstrate the feasibility and efficiency of the developed method, and the impacts of the wide applications of PHEVs on the operating costs and the emission of the power system are studied. Case studies are also carried out to investigate the impacts of different PHEV penetration levels and different PHEV charging modes on the results of the UC problem. A 100-unit system is employed for further analysis on the impacts of PHEVs on the UC problem in a larger system application. Simulation results demonstrate that the employment of optimized PHEV charging and discharging modes is very helpful for smoothing the load curve profile and enhancing the ability of the power system to accommodate more PHEVs. Furthermore, an optimal Vehicle to Grid (V2G) discharging control provides economic and efficient backups and spinning reserves for the secure and economic operation of the power system