This paper discusses a bilayer coordinated operation scheme for the multi-energy building microgrid (MEBM) with comprehensive uncertainty sources. First, model considering battery degradation, practical/detailed thermal loads, and various operating tasks of residential appliances is presented. Second, to alleviate adverse effects from diverse uncertainties electricity demands, cooling water temperature, outdoor occupants’ metabolism as well solar irradiance, applied which makes full...

Energy storage systems (ESS) are indispensable building blocks of power with a high share variable renewable energy. As energy-limited resources, ESS should be carefully modeled in uncertainty-aware multistage dispatch. On the modeling side, we develop two-stage model for that respects nonanticipativity dispatch, and implement it into distributionally robust predictive control scheme. The features multiple selective operational modes, which enable its interval to scheduled chronological...

This paper studies the robust operation of a novel hybrid AC/DC multi-energy ship (MES) microgrid with flexible thermal loads and voyage. Apart from diesel generators battery storage, photovoltaic system, combined cooling heat power (CCHP) unit, storage power-to-thermal conversion unit are also included. Then, to guarantee safe reliable voyage, diverse uncertainties renewable energies, onboard outdoor temperature addressed by coordination method. method coordinates all units in different...

Given the rapid development of ship industry and increasing operating cost gas emissions, this article studies optimal operation a multienergy (MES) microgrid to simultaneously reduce emissions. Apart from conventional diesel generators, electric energy storage, photovoltaic cells, combined cooling heat power (CCHP) unit is introduced for higher utilization efficiency. Besides, flexiblize CCHP enhance interaction, thermal storage power-to-thermal conversion are also included in MES...

The increasing prevalence of electric vehicles (EVs) has intensified the coupling between power distribution networks (PDNs) and transportation (TNs) in both temporal spatial dimensions. In order to accurately model coupled network, this paper studies dynamic network equilibrium capture temporally-dynamic interactions PDNs TNs. This encapsulates driver's choices route, departure time, charging location, electricity price. TN, a traffic with point queues is proposed describe evolution flows...

In this paper, a study of the day-ahead unit commitment problem with stochastic wind power generation is presented, which considers conditional, and correlated forecast errors through distributionally robust optimization approach. Firstly, to capture characteristics random errors, least absolute shrinkage, selection operator (Lasso) utilized develop conditional error estimator, while an unbiased estimator used obtain covariance matrix. The error, matrix are then construct enhanced ambiguity...

In this paper, an optimal coordination method for energy dispatch and voyage scheduling is proposed a renewable-energy-integrated hybrid AC/DC multi-energy ship (MES) microgrid under the continuous swinging. MES microgrid, all onboard units are dispatched coordinately with higher flexibility providing multiple energies. To guarantee reliable operation, diverse uncertainties from solar irradiation, swinging angle, demands managed by adaptive risk-averse stochastic programming approach to...

Exergy analysis is a unified approach to evaluating the quantity and quality of energy in integrated systems (IESs). However, exergy models have been relatively underexplored for IES operation transmission networks. This study addresses this gap by developing an input-benefit model loss calculation each link within heat-and-electricity-based IESs (HE-IESs), encompassing Then, exergy-based optimal HE-IESs introduced minimizing total system. In addition, effect load rate on efficiency...

In this letter, we propose a tractable formulation and an efficient solution method for the Wasserstein-metric-based distributionally robust unit commitment (DRUC-dW) problem. First, distance-based data aggregation is introduced to hedge against dimensionality issue arising from huge volume of data. Then, novel cutting plane algorithm solve DRUC-dW problem much more efficiently than state-of-the-art. The termed extremal distribution generation, which extension column-and-constraint...

The electric power industry faces tough optimization problems that are challenging for classical computers, e.g., the unit commitment (UC). Quantum computing has potential to provide a speedup combinatorial utilizing ad hoc algorithms like Grover's search algorithm. quantum oracle is indispensable search, yet it difficult realize. In this letter, we develop way construct efficient oracles solving UC in framework. features physics-informed circuit and variational picking up good solutions. A...

This paper focuses on the interchange and generation scheduling problem of multi-area power systems, where decentralized decision procedure is preferred uncertainties nodal injections should be considered. The formulated as a robust security constrained unit commitment model, with novel uncertainty set specified by variance system net load. We prove that such an can provide more precise probabilistic guarantee than conventional budgeted sets. To solve in manner, upper-level convex...

In this paper, a sparse machine learning technique is applied to predict the next-hour wind power. The hourly power prediction values within few future hours can be obtained by meteorological/physical methods, and such are often broadcast available for many generators. Our model takes into consideration those forecast values, together with real-time observations of past hours, as well in all generators nearby locations. Such consisted features high dimensions, solved technique. We...

Abstract The interdependency of power systems and natural gas is being reinforced by the emerging power‐to‐gas facilities (PtGs), existing gas‐fired generators. To jointly improve efficiency security under diverse uncertainties from renewable energy resources load demands, it essential to co‐optimise these two for day‐ahead market clearance. A data‐driven integrated electricity‐gas system stochastic co‐optimisation model proposed in tis work. accurately approximated sequential mixed integer...

This paper proposes a novel stochastic robust real-time power dispatch model considering wind uncertainty. In this that incorporates automatic generation control, system constraints are constructed with affinely adjustable optimization to enhance the security, while objective concerning expected value of cost is optimized improve efficiency. The consistent optimization, formulation for different. A Nataf conversion-based three-point estimate (NC-TPE) adopted, which uses an approximating...

This article proposes a novel segmented distributionally robust optimization method for real-time power dispatch with correlated wind forecast errors. In the proposed model, linear decision rule incorporating an allowed threshold error is developed. The excess fluctuation beyond optimized will be first discarded, and then units adopts remaining error. upgrades traditional parameterized ambiguous set into variable-involved set, which makes more flexible but meanwhile harder to solve. Through...

The deepening penetration of renewable energy sources (RESs) into power grids imposes remarkable challenges that merit special attention. In this paper, we work out a distributionally robust chance-constrained (DRCC) day-ahead unit commitment problem while the stochasticity and variability arising from RESs are taken consideration. developed framework optimizes expected objective function stipulates DRCCs will hold within moment-based ambiguity set, which additionally incorporates...

Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power systems. By considering the wind uncertainty both binary continuous decisions quick-start within intraday dispatch, we develop Wasserstein-metric-based distributionally robust optimization model for day-ahead network-constrained unit commitment (NCUC) problem with mixed-integer recourse. We propose two feasible frameworks solving problem. One approximates...

A power system unit commitment (UC) problem considering uncertainties of renewable energy sources is investigated in this paper, through a distributionally robust optimization approach. We assume that the first and second order moments stochastic parameters can be inferred from historical data, then employed to model set probability distributions. The resulting two-stage with moment constraints, we show it recast as mixed-integer semidefinite programming (MI-SDP) finite constraints. solution...

Renewable energy sources provide an important means of reducing reliance on conventional fuels. However, some renewable resources such as wind and solar energies are intermittent, their uncertainty threatens the operating security power grid. To solve this problem, study proposes use intervals to model output load demand, accordingly develops interval voltage control model, i.e. reactive optimisation model. The proposed considers modes generators can safeguard grids by ensuring that voltages...