Operation Of Flexible System Research Articles

Supply Inadequacy Risk Evaluation of Stand-Alone Renewable Powered Heat-Electricity Energy Systems: A Data-Driven Robust Approach

Integration of heat and electricity supply improves the overall energy efficiency and system operational flexibility. The renewable powered heat-electricity energy system is a promising way to set up residential energy supply facilities in remote areas beyond the reach of power system infrastructures. However, the volatility of wind and solar energy brings about the risk of supply inadequacy. This article proposes a data-driven robust method to quantify two measures of such a risk in the stand-alone renewable powered heat-electricity energy system. The uncertainty of renewable generation is modeled through a family of ambiguous probability distributions around an empirical one based on the Wasserstein metric; then, the probability of heat and electricity load shedding during a short period and related penalty cost are discussed. Through a polyhedral characterization of renewable power feasible region, the load shedding probability under the Wasserstein ambiguity set comes down to a linear program. With a piecewise linear optimal value function of the penalty cost, its expectation under the worst case distribution in the Wasserstein ambiguity set also gives rise to a linear program. The proposed method requires moderate information on renewable generation and makes full use of available data, whereas sustains computational tractability. The evaluation result is robust against the inaccuracy of renewable power distributions. Case studies demonstrate the effectiveness of the proposed approach.

Dynamic Microgrids in Resilient Distribution Systems With Reconfigurable Cyber-Physical Networks

Modern distribution systems energized by inverter-interfaced distributed generators (DGs) operate as coupled cyber-physical networks (C/P-networks), where the controllable components in the P-network are coordinated through the C-network. The concept of dynamic microgrids (MGs) operation has been adopted to enable distribution system autonomous operation with varying electric boundaries. To further enhance the system operation resiliency and flexibility, dynamic MGs operation with reconfigurable C/P-networks is discussed in this article. An evaluation framework is proposed to assess the operational feasibility of distribution feeders with multiple inverter-based dynamic MGs and come out with possible restoration solutions in the context of cross-layer C/P-network reconfiguration. Furthermore, distributed controllers are developed for components with different operating characteristics to realize seamless system topology variations and provide coordinated secondary regulation in various operation modes. The proposed evaluation framework, along with the developed distributed controller, has been validated using a hardware-in-the-loop (HIL) real-time CPS testbed.

Using Energy Storage to Relief Transformer Overloading after Coal-Fire Generator Retirement

Energy storage system (ESS) is believed to be a significant source of power system operational flexibility given renewable generation with high penetration. This work reports a unique scenario of relieving the overloading of a 500kV transformer after the retirement of a coal-fire generator. ESS is proven to be an ideal solution in terms of technical feasibility and economic performance. A look-ahead operation strategy is to utilize ESS to mitigate the identified transformer overloading bottleneck. A case study using a synthetic version of Zhejiang power grid confirms the effectiveness of the proposed ESS based approach.

Optimal sizing and multi‐energy management strategy for PV‐biofuel‐based off‐grid systems

This study proposes a comprehensive framework for developing a multi-energy off-grid microgrid with the decoupled flow of thermal and electrical energies in a rural setting. A carbon-neutral microgrid with a hybrid generation system constituting a photovoltaic unit and a biofuel generator is proposed. In order to enhance the fuel utilisation efficiency, the biofuel generator is operated in combined cooling, heating, and power mode, and the recovered thermal energy forms the heat distribution network in the microgrid. The flexibility of system operation is improved by suitable multi-energy (electrical and thermal) storage. Firstly, an optimal sizing framework has been developed for the system as a mixed integer linear programming model. Secondly, a coordinated multi-energy management system (MEMS) has been developed for combined optimal dispatch of multiple generation and storage resources. The MEMS has been developed as a mixed integer non-linear programming model, which minimises system operational cost while considering minimum battery degradation to prolong its lifetime. Finally, a detailed economic analysis of the proposed system has been presented, highlighting the levellised cost of energy and net present value. Extensive case studies and simulation results depict the effectiveness and suitability of the proposed MEMS for the rural off-grid microgrid.

Managing Micrologistic System Operation Flexibility for Make to Order Manufacturing

Under conditions of make to order manufacturing in the micrologistic system of the enterprise, problems arise due to inefficient use of production capacities due to irrational use of productive labor resources. In order to solve the problem of material flow parameters of logistical optimization by increasing production «flexibility» in the production chain, we propose an algorithm of operational control through redistribution of industrial labor resources of an industrial enterprise. Practical application of this algorithm allows increasing flexibility of the enterprise to meet the market demand for products on individual orders, and to increase the efficiency of its activities.

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional “heat-set” operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. The simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

Increasing operational flexibility of integrated energy systems by introducing power to hydrogen

Owing to the limited operating regions of combined heat and power (CHP) units, the operation of integrated energy systems suffers from low flexibility, low-cost efficiency, renewable curtailment etc. Meanwhile, as the capacity of renewable energies keeps growing and integrating into power systems, various methods, such as installing electric boilers to enable electricity-heat conversion, have been developed to absorb excessive renewables and increase system operation flexibility. To further increase the system operation flexibility, this study explores the possibilities of utilising electrolysers and hydrogen storage tanks to enable electricity-hydrogen-heat conversion. To better visualise the enhanced flexibility, this study presents extra flexibilities from electric boilers, electrolysers and hydrogen tanks as the equivalent operating region expansion for CHP units. In this study, the system is modelled as a mixed-integer optimisation problem which balances the electricity, heat and hydrogen demands in a 24-hour period. A 6-bus test system is used in the case studies to illustrate the effectiveness of implementing electrolysers and hydrogen storage tanks. The optimisation results show the application of hydrogen energy improves the system operation flexibility, reduces wind curtailment, thereby decreasing fuel consumption and carbon emission.

Flexible Multi-Energy Scheduling Scheme for Data Center to Facilitate Wind Power Integration

Due to the intermittent and uncontrollable nature of wind resources and inflexible operation of conventional generation units, they present challenges for the power system to integrate more wind power. With its unique flexibility on the demand side, the data center can be considered as an effective solution to relieve wind curtailment. Moreover, with the help of waste heat recovery module, the data center can reduce the utilization of conventional thermal units especially in the residential heating sector which increases the flexibility of system operation and facilitates more renewable integration. In this paper, a flexible workload management and resource scheduling model are proposed to achieve a multi-energy co-optimization for data center and enhance the integration of wind power. A two-stage stochastic programming model is formulated to address the uncertainties involved in this process. The proposed model is examined by a simulative data center microgrid and the numerical results demonstrate its effectiveness and robustness.

A new symbolic-based continuous (infinite) modal approach for systems control and operation using computational mathematics

This paper presents the new concept of symbolic-based continuous (infinite) modal approach for systems control and operation in varying parameters environment. In this approach, the system is run under varying parameters form where the variations are sensed and fed back in a continuous manner for determining using symbolic-based expressions the corresponding control functions. The approach permits the simultaneous manipulation of system control and operation with the online changes of system parameters. The generic symbolic approach enables high system operation flexibility, while the continuous (infinite) modal operation ensures complete smoothing system behavior and full operation modal compatibility all over various system varying parameters regions. The realization of the continuous (infinite) modal design is carried out through symbolic-based embedded control expressions and using computational mathematics. The proof of concept of the presented scheme is demonstrated through both an illustrative example and an application representing the implementation of control of inverted pendulum system with varying cart mass operation. It is successfully elucidated that the exact generic tracking of changing parameters could effectively be achieved in very smoothly and with complete continuous modal compatibility and full auto or self-modality. Moreover, the proposed scheme enables providing more performance flexibility compared to the known unimodal and multimodal operation approaches and adds a new dimension for future system control and operation specially in the fields of mechatronics and robotics where smooth and flexible system behavior are to be maintained all over the modes of system operation. Finally, the applications of the suggested approach to examples of parameters varying direct and networked cyber-physical systems are addressed such that the varying parameters are monitored online and continuously fed to the symbolic-control function to yield at the end the exact/generic flexible control scheme.

Operation Optimization of Multi-District Integrated Energy System Considering Flexible Demand Response of Electric and Thermal Loads

Multi-district integrated energy system (IES) can make full use of the complementary characteristics of district power and thermal system, and loads in different districts. It can improve the flexibility and economy of system operation, which has a good development prospect. Firstly, based on the general energy transfer model of the district heating network (DHN), the DHN system is described by the basic equations of the heating network and nodes considering the characteristics of the transmission time delay and heat loss in pipelines. A coupling model of DHN and multi-district IES is established. Secondly, the flexible demand response (FDR) model of electric and thermal loads is established. The load characteristics of each district in IES are studied. A shiftable load model based on the electric quantity balance is constructed. Considering the flexibility of the heat demand, a thermal load adjustment model based on the comfort constraint is constructed to make the thermal load elastic and controllable in time and space. Finally, a mixed integer linear programming (MILP) model for operation optimization of multi-district IES with the DHN considering the FDR of electric and thermal loads is established based on the supply and demand sides. The result shows that the proposed model makes full use of the complementary characteristics of electric and thermal loads in different districts. It realizes the coordinated distribution of thermal energy among different districts and improves the efficiency of thermal energy utilization through the DHN. FDR effectively reduces the peak-valley difference of loads. It further reduces the total operating cost by the coordinated operation of the DHN and multi-district IES.

Economically Optimal Uncertainty Set Characterization for Power System Operational Flexibility

Assessing the operational flexibility of the grid with high penetration of renewable resources remains an issue of critical importance. Operational flexibility insufficiency may bring about two major problems: 1) there may exist no feasible solution for operation under uncertain conditions due to insufficient available flexibility capacity; 2) even if the solution feasibility criterion is ensured, dispatch limitations of the flexible resources may force the system operating point to deviate from the optimal economic point with increased redispatch. In this paper, an optimal uncertainty set at the unit commitment time scale is proposed and characterized as a reliable operational metric. A novel robust-based framework is developed to quantify the economically optimal uncertainty set such that both feasibility and optimality robustness are guaranteed. Furthermore, the flexible capabilities of storage units, nonquick-start, and quick-start generating units are formulated to illustrate the effectiveness of the proposed metrics. Two proposed algorithms based on column and constraint generation are adopted to solve the proposed formulations. The performance of the suggested formulations is compared with the scenarios, where only the feasibility robustness is taken into account. Numerical simulations on the modified IEEE 73-bus system will verify the effectiveness and efficiency of the suggested framework.

Risk-Limiting Real-Time Economic Dispatch in a Power System with Flexibility Resources

The integration of numerous intermittent renewable energy sources (IRESs) poses challenges to the power supply-demand balance due to the inherent intermittent and uncertain power outputs of IRESs, which requires higher operational flexibility of the power system. The deployment of flexible ramping products (FRPs) provides a new alternative to accommodate the high penetration of IRESs. Given this background, a bi-level risk-limiting real-time unit commitment/real-time economic dispatch model considering FRPs provided by different flexibility resources is proposed. In the proposed model, the objective is to maximize the social surplus while minimizing the operational risk, quantified using the concept of conditional value-at-risk (CVaR). Energy and ramping capabilities of conventional generating units during the start-up or shut-down processes are considered, while meeting the constraints including unit start-up/shut-down trajectories and ramping up/down rates in consecutive time periods. The Karush–Kuhn–Tucker (KKT) optimality conditions are then used to convert the bi-level programming problem into a single-level one, which can be directly solved after linearization. The modified IEEE 14-bus power system is employed to demonstrate the proposed method, and the role of FRPs in enhancing the system flexibility and improving the accommodation capability for IRESs is illustrated in some operation scenarios of the sample system. The impact of the confidence level in CVaR on the system operational flexibility is also investigated through case studies. Finally, a case study is conducted on a regional power system in Guangdong Province, China to demonstrate the potential of the proposed method for practical applications.

Flexible Division and Unification Control Strategies for Resilience Enhancement in Networked Microgrids

Networking a series of autonomous microgrids (MGs) is a strategic effort toward the resilience enhancement in extreme conditions. In this paper, flexible division and unification control strategies are proposed to help networked MGs prepare adequately for extreme events and adapt comprehensively to subsequent changing conditions, which enhance the system resilience. According to the proposed strategies, networked MGs can switch between two distinct modes of division and unification by utilizing a sparse communication network without requiring any additional communication infrastructures or controllers. In division mode, each MG is regulated by its local master controllers (MCs) for active power sharing, which ensures that disruptions are handled effectively by local energy resources without utilizing those in adjacent MGs. Thus, any islanding or resynchronization of individual MGs would not introduce further disruptions to the remaining networked system. The proposed control strategies imply that the networked MGs system in division mode is managed in a proactive way to adequately prepare the networked system for extreme events. In the unification mode, the remaining networked MGs, which are still functional, use the proposed algorithm to share all available energy resources and adapt to continuously changing operating conditions in order to respond to extreme events. The proposed control algorithm for devising a flexible networked MGs system is a cost-effective scheme that can fully exploit the system operation flexibility corresponding to different operation stages for enhancing resilience. The proposed control strategies are applied to a networked AC MGs system and the performance is tested using time-domain PSCAD/EMTDC simulations.

Co-optimization of transmission topology and generation dispatch incorporating demand response and renewable energy uncertainty in day-ahead electricity markets

The variability of renewables requires a higher degree of flexibility in power system operation. At present, there are a variety of solutions which are being utilized, particularly demand response and transmission switching. This paper presents a model for co-optimization of transmission topology and generation dispatch based on a two-stage stochastic optimization. Demand response and renewable energy uncertainty are integrated into the proposed model. The uncertainty pertaining to renewable energy sources is presented through a set of scenarios. The model is a mixed-integer linear programming (MILP) problem and can be applied for the day-ahead market clearing. The results implemented using a 5-bus system demonstrate the effectiveness of the proposed model.

Bi-level optimization of design, operation, and subsidies for standalone solar/diesel multi-generation energy systems

Unlike grid–tied energy systems, wherein uniform renewable energy subsidies can be applied directly, the standalone multi-generation energy systems integrated with renewable energy in remote areas deserve to be subsidized specifically according to the local natural resources and energy demands. To establish an effective subsidy policy, the impacts of electrical and thermal subsidies for renewable energy on the system performance need to be investigated effectively, from the perspective of various stakeholders. In this study, a bi–level optimization model is proposed to obtain optimal design, operation, and subsidies for a standalone multi-generation energy system situated on a remote island; the system incorporates solar energy, fossil energy, and storage. Herein, the social cost to the society is set as the upper-level objective, and the private cost to the residents is set as the lower-level objective. The results indicate that production-based incentives of solar electrical energy and solar thermal energy jointly impact the design and operation of the energy system to minimize the social and private costs simultaneously; moreover, the demand response could further increase the flexibility of system operation, thus decreasing the system cost to a larger extent.

Convex Hull Based Robust Security Region for Electricity-Gas Integrated Energy Systems

Increasing interdependency between electric power systems and natural gas systems creates additional dimensions of flexibility of system operation; but it may also escalate risk levels if the two systems are managed without proper coordination. This paper presents a robust security region (RSR) for electricity-gas integrated energy systems (IESs). It is a collection of uncertain parameters, especially wind power generations, under which system power flow has at least one feasible solution. First, a nonlinear optimization model is employed to obtain a set of uniformly distributed points on power flow solvability boundaries, from which the IES security region is constructed using a convex hull. Then, the proposed RSR is constructed to provide secure operation for the base-case scenario, where uncertain wind power generation values are replaced with expected values, and provide a feasible redispatch plan for each wind power generation scenario. Other implications of the RSR on IES security assessment are also envisioned. Results for two test systems indicate that the convex hull approach provides a more accurate approximation of the IES security region than a hyperplane approach. Meanwhile, the benefits of RSR are demonstrated by comparing test results with those obtained for a deterministic security region.

Operational Flexibility Constrained Intraday Rolling Dispatch Strategy for CHP Microgrid

The increasing penetration of variable renewable energy sources (RES) such as wind power and photovoltaic cell in the microgrid poses a great threat to the power balance. The microgrid operator has to consider the system operational flexibility in the dispatch to overcome the uncertainties. For a multi-energy microgrid, the coupling relationship and complementarity of different energy provides potential capacity for operational flexibility. In this paper, we propose an operational flexibility metric to quantify the ability of the combined heat and power (CHP) microgrid to overcome RES uncertainties in operation. An intraday rolling dispatch strategy for the off-grid CHP microgrid is proposed, which consists of a dispatch decision (DD) stage and a real-time adjustment (RTA) stage. The operational flexibility constraints are incorporated in the DD model to ensure that the uncertainties in the real-time operation can be suppressed. The RTA model is based on a linear programming model. Case studies demonstrate that the proposed dispatch strategy can overcome the uncertainties efficiently and ensure the secure and economic operation of the system.

Operation Flexibility Evaluation and Its Application to Optimal Planning of Bundled Wind-Thermal-Storage Generation System

The growing penetration of wind power in a power system brings great challenges to system operation flexibility. For generation planning in presence of high wind power penetration, it is essential to take the operation flexibility of the system into account. Firstly, this paper developed the system operation flexibility metrics through considering the flexibility contribution of thermal generating units (TGUs) by operational state transition. Secondly, a planning model for the bundled wind-thermal-storage generation system (BWTSGS) that considers the operation flexibility constraints is proposed. The planning model is used to determine the power and energy rating of an energy storage system (ESS) as well as the type and number of TGUs. A daily scheduling simulation model of a BWTSGS is proposed to calculate the operation cost for the planning model and consider the sequential operation characteristics of the BWTSGS. Further, in order to accelerate the computation, a wind power sequential clustering technique based on the discrete Fourier transform (DFT) method is developed for improving the computational efficiency. Case studies have been conducted on a 1000-MW wind farm to demonstrate the validity and effectiveness of the proposed model.

Scheduling isolated power systems considering electric vehicles and primary frequency response

The incorporation of renewable energy sources in isolated power systems is being significantly slower than in well-connected power systems. The intermittency and uncertainty of the power output of most renewable power technologies prevent a greater usage of these technologies in isolated power systems, in which the supply security is the major concern. In this paper we formulate a stochastic unit commitment problem that allows the participation of electric vehicles in energy, reserve capacity and primary frequency response markets in order to increase the flexibility of the power system operation. We explicitly consider the uncertainty in the power demand and renewable power availability, as well as accounting for the possibilities of contingencies of generating units using a N-1 security criterion. The proposed formulation is tested on an actual isolated power system comprising 38 generating units and 8 buses.

Cascading Collapse of a Large-Scale Mixed Source Microgrid Caused by Fast-Acting Inverter-Based Distributed Energy Resources

Power electronic converter-interfaced distributed energy resources (DERs) are being increasingly deployed for achieving high energy efficiency, power quality, and flexibility of power system operation and controls. They facilitate access to a wide array of energy sources, including renewables, fuel cells, microturbines, variable speed engine-generator sets, etc. However, recent tests carried out at the Consortium for Electric Reliability Technology Solutions (CERTS) Microgrid have indicated that their deployment in the mixed source microgrid can cause a cascading collapse during extreme events. To investigate the problem, simulation models of two types of DERs are developed in PSCAD/EMTDC software and validated with the experimental test results. Furthermore, the validated models are used to study a cascading collapse problem in a large-scale mixed source microgrid on the benchmark IEEE 33-bus test system. In this paper, three alternative techniques are evaluated to prevent the cascading collapse in the large-scale microgrid caused by fast-acting inverter-based DERs.