An Uncertain Optimal Energy Flow Model for CCHP Campus Microgrid Using Parameterized Probability Boxes

Due to the uncertain fluctuations of renewable energy and load power, the state variables such as bus voltages and pipeline mass flows in the combined cooling, heating, and power campus microgrid(CCHP-CMG) may exceed the secure operation limits. In this paper, an optimal energy flow(OEF) model for a CCHP-CMG using parameterized probability boxes(p-boxes) is proposed to describe the higher-order uncertainty of renewables and loads. In the model, chance constraints are used to describe the secure operation limits of the state variable p-boxes, and variance constraints are introduced to reduce their random fluctuation ranges. To solve this model, the chance and variance constraints are transformed into the constraints of interval cumulants(ICs) of state variables based on the p-efficient point theory and interval Cornish-Fisher expansion. With the relationship between the ICs of state variables and node power, and using the affine interval arithmetic method, the original optimization model is finally transformed into a deterministic nonlinear programming model. It can be solved by the CONOPT solver in GAMS software to obtain the optimal operation point of a CCHP-CMG that satisfies the secure operation requirements considering the higher-order uncertainty of renewables and loads. Case study on a CCHP-CMG demonstrates the correctness and effectiveness of the proposed OEF model.

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.

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.