Optimal Energy Flow and Nodal Energy Pricing in Carbon Emission-embedded Integrated Energy Systems

Green energy is driving the evolutions of energy industry and carbon emission is becoming an important concern.Considering the increasing couplings among various energy sectors,this paper investigates multi-period optimal energy flow and energy pricing in carbon-emission embedded integrated energy systems,including electricity,natural gas,and district heating networks.Firstly,an optimal scheduling model of integrated energy systems was proposed in this paper.The models of DC power flow,natural gas pipeline flow and heating network energy flow are presented and linearized for the optimization problem.Natural gas-fired generators and combined heat and power(CHP)units are modeled as coupling components of electricitygas and electricity-heating networks.Then,based on the optimal scheduling model,the locational marginal prices(LMP)for electricity,natural gas and heating network are determined.Moreover,the carbon emission caused by energy production has been taken into account in the optimal scheduling and energy pricing process.Finally,case studies on a combined network consisting of IEEE 39-bus system,Belgium 20-node natural gas system and 6-node heating system demonstrate the effectiveness of the proposed model and the impacts of carbon emission on system scheduling and LMP.

Day-ahead Scheduling of Multi-carrier Energy Systems with Multi-type Energy Storages and Wind Power

The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.

Orbiting Optimization Model for Tracking Voltage Security Region Boundary in Bulk Power Grids

A voltage security region(VSR)is a powerful tool for monitoring the voltage security in bulk power grids with high penetration of renewables.It can prevent cascading failures in wind power integration areas caused by serious over or low voltage problems.The bottlenecks of a VSR for practical applications are computational efficiency and accuracy.To bridge these gaps,a general optimization model for tracking a voltage security region boundary(VSRB)in bulk power grids is developed in this paper in accordance with the topological characteristics of the VSRB.First,the initial VSRB point on the VSRB is examined with the traditional OPF by using the base case parameters as initial values.Then,the rest of the VSRB points on the VSRB are tracked one after another,with the proposed optimization model,by using the parameters of the tracked VSRB point as the initial value to explore its adjacent VSRB point.The proposed approach can significantly improve the computational efficiency of the VSRB tracking over the existing algorithms,and case studies,in the WECC 9-bus and the Polish 2736-bus test systems,demonstrate the high accuracy and efficiency of the proposed approach on exploring the VSRB.

Active-reactive power scheduling of integrated electricity-gas network with multi-microgrids

Advances in natural gas-fired technologies have deepened the coupling between electricity and gas networks,promoting the development of the integrated electricity-gas network(IEGN)and strengthening the interaction between the active-reactive power flow in the power distribution network(PDN)and the natural gas flow in the gas distribution network(GDN).This paper proposes a day-ahead active-reactive power scheduling model for the IEGN with multi-microgrids(MMGs)to minimize the total operating cost.Through the tight coupling relationship between the subsystems of the IEGN,the potentialities of the IEGN with MMGs toward multi-energy cooperative interaction is optimized.Important component models are elaborated in the PDN,GDN,and coupled MMGs.Besides,motivated by the non-negligible impact of the reactive power,optimal inverter dispatch(OID)is considered to optimize the active and reactive power capabilities of the inverters of distributed generators.Further,a second-order cone(SOC)relaxation technology is utilized to transform the proposed active-reactive power scheduling model into a convex optimization problem that the commercial solver can directly solve.A test system consisting of an IEEE-33 test system and a 7-node natural gas network is adopted to verify the effectiveness of the proposed scheduling method.The results show that the proposed scheduling method can effectively reduce the power losses of the PDN in the IEGN by 9.86%,increase the flexibility of the joint operation of the subsystems of the IEGN,reduce the total operation costs by $32.20,and effectively enhance the operation economy of the IEGN.

Conic Optimal Energy Flow of Integrated Electricity and Natural Gas Systems

In this letter, we propose a market-based bi-level conic optimal energy flow (OEF) model of integrated electricity and natural gas systems (IENGSs). Conic alternating current optimal power flow (ACOPF) is formulated in the upper-level model, and the generation cost of natural gas fired generation units (NGFGUs) is calculated based on natural gas locational marginal prices (NG-LMPs). The market clearing process of natural gas system is modeled in the lower-level model. The bi-level model is then transferred into a mixed-integer second-order cone programming (MISOCP) problem. Simulation results demonstrate the effectiveness of the proposed conic OEF model.