Flexible Electric Loads Research Articles

A Novel Day-Ahead Optimization-Oriented Low-Carbon Economic Scheduling Scheme for Integrated Energy Systems

As the global energy structure undergoes transformation and the low-carbon development process continues to advance, integrated energy systems have progressively emerged as crucial technical support for achieving sustainable development. In this paper, a joint-day optimal scheduling model is put forward considering the existence of dispatchable resources in community integrated energy systems (CIES). The aim is to cut down the system operation cost and enhance energy utilization efficiency. This model is founded on the concept of energy hubs and combines the shiftable, transferable, and reducible characteristics of demand-side flexible loads. It includes gas turbine power generation systems, energy storage, as well as wind and solar renewable resources. System operation cost and carbon trading cost are comprehensively taken into account, and ultimately, the CIES low-carbon economic dispatch model with the lowest total cost as the optimization objective is established. The Yalmip toolbox and Cplex solver are employed to solve the model. The optimization results of flexible electric and thermal loads participating in dispatching under different scenarios are analyzed through simulation. The economic benefits of electric and thermal independent dispatching are compared and analyzed, and the economic benefits of electric and thermal coupled dispatching are verified. The study reveals that the rational scheduling of user-side flexible loads can notably reduce operating costs, lower the load peak-to-valley difference and carbon emissions, and boost the comprehensive economic and environmental benefits of the system.

Low carbon operation and evaluation methods for integrated energy system counting EVs with whole life cycle considering demand response

The integrated energy system has gradually become an effective way of energy saving and emission reduction with the proposal of “dual carbon" target and the continuous promotion of low-carbon development. However, most of the existing studies on demand-side flexible loads only consider flexible power loads, and there are fewer studies on the controllability of thermal loads. This paper proposes a low-carbon and economic optimal scheduling model and evaluation method for integrated energy system considering demand-side response. With the goal of minimizing the total operating cost of the integrated energy system, and taking into account the transferable and curtailing characteristics of the electric and thermal flexible loads, we establish an optimal scheduling model of the integrated energy system considering the user-side flexible loads, and comprehensively evaluate the performance of the system in terms of economic performance, reliability, and environmental performance. The performance of the system is evaluated in terms of economic performance, reliability and environmental performance. The role of flexible loads in improving the economy of the combined supply system is investigated with examples, and the rationality and effectiveness of the study are verified through comparative analysis of different scenarios. The results show that the total cost of the system is reduced by 18.04 %, 9.1 %, 3.35 % and 7.03 % when carbon trading cost and demand-side flexible electric-heat load response are considered at the same time; and the total carbon emission of the system is reduced by 65.28 %, 20.63 %, 3.85 % and 18.03 %, respectively. Considering carbon trading costs and demand-side flexible electric and thermal load response can improve the reliability of the system. The overall reliability of the system is improved by 10 %, 15 %, 16.67 % and 20 % for the four scenarios, respectively.

Optimized scheduling of integrated energy systems for low carbon economy considering carbon transaction costs

With the introduction of the “dual carbon” goal and the continuous promotion of low-carbon development, the integrated energy system (IES) has gradually become an effective way to save energy and reduce emissions. This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs. With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads, an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established. The role of flexible loads in improving the economy of an energy system was investigated using examples, and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios. The results showed that the total cost of the system in different scenarios was reduced by 18.04%, 9.1%, 3.35%, and 7.03%, respectively, whereas the total carbon emissions of the system were reduced by 65.28%, 20.63%, 3.85%, and 18.03%, respectively, when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously. Flexible electrical and thermal loads did not have the same impact on the system performance. In the analyzed case, the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account. Photovoltaics have an excess of carbon trading credits and can profit from selling them, whereas other devices have an excess of carbon trading and need to buy carbon credits.

Flexible Regulation and Synergy Analysis of Multiple Loads of Buildings in a Hybrid Renewable Integrated Energy System

The insufficient flexibility of the hybrid renewable integrated energy system (HRIES) causes renewable power curtailment and weak operational performance. The regulation potential of flexible buildings is an effective method for handling this problem. This paper builds a regulation model of flexible heat load according to the dynamic heat characteristics and heat comfort elastic interval of the buildings, as well as a regulation model of the flexible electrical load based on its transferability, resectability, and rigidity. An operation optimization model, which incorporates flexible regulation of multiple loads and a variable load of devices, is then developed. A case study is presented to analyze the regulation and synergy mechanisms of different types of loads. Its results show a saturation effect between heat and electrical loads in increasing renewable energy consumption and a synergistic effect in decreasing the operating cost. This synergy can reduce the operating cost by 0.73%. Furthermore, the operating cost can be reduced by 15.13% and the curtailment rate of renewable energy can be decreased by 12.08% when the flexible electrical and heat loads are integrated into the operation optimization of HRIES.

Optimized low carbon scheduling strategy of integrated energy sources considering load aggregators

In the context of the global low-carbon energy development strategy, the massive influx of renewable energy leads to the instability of the power system, so it is necessary to carry out effective scheduling strategy and management mechanism for energy. On this basis, the Integrated Energy System including Electricity/Heat/Storage (EHSIES) is discussed in this paper. First, an ordered clustering method using a combination of simulated annealing and improved profile coefficients for load evolution number approximation is proposed. Second, a hybrid load clustering algorithm based on hierarchical clustering algorithm and K-means++ is presented and four types of load scenarios are obtained. Third, an Improved Harris Hawk Optimization (IHHO) algorithm based on the hybrid strategy is proposed and solved to the model of EHSIES. Finally, under the premise of the dynamic carbon trading mechanism considering historical compliance and load aggregator management, the scheduling strategies of flexible electric loads and thermal loads participating in EHSIES are discussed and solved by CPLEX. The results show that the solution time of IHHO is 50% and 33.3% lower than that of particle swarm optimization (PSO) and Harris hawk optimization (HHO), and the number of iterations is 76.6% and 56.25% lower than that of PSO and HHO, respectively. In addition, considering a flexible load aggregator and a compliance-based dynamic carbon trading mechanism in EHSIES scheduling can effectively reduce the actual operating cost by 27.37%, the source-side energy spill rate by 68.75%, and the carbon emission by 51.92% and improve the operating efficiency and economic benefits of EHSIES.

Optimal scheduling of park-level integrated energy system considering ladder-type carbon trading mechanism and flexible load

In an attempt to improve the utilization efficiency of multi-energy coupling in park-level integrated energy system (PIES), promote wind power consumption and reduce carbon emissions, a low-carbon economic operation optimization model of PIES integrating flexible load and carbon trading mechanism is constructed. Firstly, according to the characteristics of load response, the demand response is divided into four types: which can be shifted, transferred, reduced and replaced. Secondly, the PIES basic architecture is given by considering the combined heat and power generation coupling equipment, new energy and flexible load in the park. Finally, introducing the ladder-type carbon trading mechanism into the system and minimize the total operating cost, the low-carbon economic operation optimization model of PIES is established. The YALMIP toolbox and CPLEX solver are used to solve the example, the simulation results show that the participation of electrical and thermal coupled scheduling and flexible electric or thermal loads can significantly reduce the system operating cost, reduce the load peak-to-valley difference and relieve peak power consumption pressure.

Optimal Scheduling of Integrated Energy Systems Considering Carbon Trading

Under the background where the electricity market and the carbon market are booming, the operation and dispatch of the integrated energy system requires the introduction of a carbon trading mechanism that can help guide customers and system operators to optimize electricity consumption and dispatch plans. A mathematical model of the community-integrated energy system, including energy storage, gas turbine generation system, and flexible load, is constructed based on energy hubs. In the consideration of costs in operation and carbon trading of the system, a low carbon economic dispatch model is established for IES to achieve the optimization objective of minimizing the total cost. The simulation results show that the coupled electric and thermal dispatch and the participation and interaction of flexible electric and thermal loads can lower the load peak-to-valley difference and significantly reduce the system operation cost, and the flexible load participation and dispatch under the carbon trading system can effectively bring the system more environmental and economic benefits.

A robust multi-objective joint scheduling of integrated electricity and gas grids considering high penetration of wind and solar units and flexible loads towards achieving a sustainable operation

The cooperative planning of interconnected networks to achieve a sustainable operation and satisfy the welfare of all agents has become a critical issue. This paper optimizes the joint scheduling of integrated electricity and gas grids composed of wind turbines, photovoltaics, storage systems, power to gas and gas to power units. In this regard, a risk-constrained multi-objective programming is suggested to simultaneously model the operation costs of both networks and a robust augmented epsilon constraint method is applied to solve the problem and obtain the Pareto set. In order to simulate realistic conditions, uncertainties of wind and solar energies, electrical and gas loads and energy and gas prices are also considered. As well, the impact of flexible electrical and gas loads is analyzed using a time-of-use demand response program. According to the simulations, the presented approach is capable to create a good equilibrium between both networks. The results validate that the risk-averse strategy significantly increases the costs of electrical and gas grids by 21.41% and 10.36% compared to the risk-neutral strategy, respectively. In return, the robustness is improved against fluctuations caused by uncertain parameters. Moreover, responsive loads enhance decision flexibility and decrease the mentioned costs by 2.26% and 7.83%, respectively.

Risk-based day-ahead planning of a renewable multi-carrier system integrated with multi-level electric vehicle charging station, cryptocurrency mining farm and flexible loads

Integration of different infrastructures has become an interesting subject due to many advantages such as high flexibility and reliability. However, interconnection and coordination of components create critical challenges. In this paper, the day-ahead planning of a renewable multi-carrier system composed of various resources, loads and storage units is optimized considering multi-level electric vehicle charging station and cryptocurrency mining farm as the electrical loads with high energy consumption. Since the instability of renewable resources in such structures leads to increasing market trading and uncertain decisions, different scenarios are generated for wind speed, solar radiation and price of markets. Then, the conditional value-at-risk metric is used to simultaneously evaluate the risk of uncertainties. Moreover, the demand side management strategies are taken into consideration to analyze the role of flexible electrical, heating, cooling and vehicle loads in energy management. A sensitivity analysis is eventually proposed to indicate the effect of various parameters. The results for the risk-averse strategy approve that increasing the robustness against the worst-case scenarios reduces the profit by about 198.97 $. Although the crypto mining farm consumes high electrical energy equal to 7605 kWh, it increases the profit by about 277.34 $. The simulations also validate that implementing the demand response program improves the system flexibility and increases the profit by about 936.57 $. Furthermore, the sensitivity analysis shows the notable impact of initial state of components on the objective function.

Preparing Water Utilities for the Future of Energy Management

Key TakeawaysIn an interview, members of AWWA's Energy Management Committee share how water utilities can prepare for the future.Adding to its considerable guidance on the topic, AWWA is preparing a new Manual of Practice, M83, Energy Management of Pumping and Treatment Processes.Embracing flexible electric loads and digital technologies, while continuing to address pumping inefficiencies, will help water utilities thrive in a resource‐constrained and energy‐strained future.

Optimal Dispatching Modeling of Regional Power–Heat–Gas Interconnection Based on Multi-Type Load Adjustability

As an important research direction of the energy system, the integrated energy system of a park plays an important role in the field of energy optimization and sustainable economic operation. In this study, a low-carbon optimal operation model of the integrated energy system of an industrial park is proposed, considering a controllable flexible load response. First, the typical structure of the integrated energy system of the park and the model of each subsystem are introduced; then, under the premise that flexible electrical and thermal loads can be used for adjustment of energy utilization, a complete dispatch scheme is constructed according to the energy consumption and system operation characteristics of the integrated energy system. Finally, an optimal scheduling model for the combined supply and demand of the integrated energy system is established with the aim of minimizing the total operating cost. For experimental results, the YALMIP toolbox and the CPLEX solver are used to verify the results of the study; simulation results show that the optimal scheduling of controllable loads can effectively reduce the comprehensive operating cost of a community integrated energy system.

Decentralized and Multi-Objective Coordinated Optimization of Hybrid AC/DC Flexible Distribution Networks

The increasing penetration of distributed energy resources and flexible electrical loads makes hybrid AC/DC distribution networks become a crucial trend for future modern distribution networks. To increase the flexibility and energy efficiency of hybrid AC/DC distribution networks, a decentralized and multi-objective coordinated optimization method by considering different control means is proposed. The salient feature of this method is that it comprehensively and properly models the full variety of possible control means (i.e., active/reactive power of distributed generation, on load tap changers, flexible distribution switch, voltage source converter). The abundant means are utilized to optimize operational cost, voltage deviation and network losses simultaneously. Then, a fully decentralized optimization method based on alternating direction multiplier method (ADMM) is proposed. The hybrid AC/DC distribution networks are divided into several sub-networks. Flexible interconnected electronic devices are utilized to transfer energy between different sub-networks to achieve the efficient and flexible utilization of controllable resources in hybrid AC/DC distribution networks. Finally, the proposed coordinated optimization method is tested on a modified dual IEEE 33-node network to demonstrate its effectiveness and advantages, and the performance of the centralized method and our proposed method is compared.

A collaborative voltage optimization utilizing flexibility of community heating systems for high PV penetration

The increasing penetration of photovoltaic generation exacerbates the risk of voltage violations in distribution networks. One viable tactic for increasing the flexibility of regional distribution networks is to use the thermal inertia of community heating systems (CHSs). However, the slow heat dynamics in the heating network brings difficulties in synchronous joint operation decisions of the integrated system. In this paper, we propose a novel power-to-temperature sensitivity model (PTSM), equating the whole CHS to a flexible electric load with thermodynamic characteristics. It denotes the direct relationship between the average water temperature change and the electric power consumed by ground-source heat pumps (GSHPs). A robust collaborative voltage optimization model is then developed from the perspective of power distribution system operators. The PTSM provides accurate prediction of CHS temperature variations to construct the operation constraints of GSHPs. This mixed integer programming problem is solved by the column-and-constraint generation algorithm. The test results of an actual residential community demonstrate that the PTSM can ensure the prediction errors of the CHS average temperature within ±0.4 °C in case of the optimal time resolution and aggregated heating load location. An IEEE 69-bus distribution network with several CHSs is studied to show that, the flexibility of CHSs can achieve an extra 17.25% reduction of the daily voltage deviation. The proposed method has significant advantages in computation time and robustness.

Demand response through decentralized optimization in residential areas with wind and photovoltaics

A paradigm shift has to be realized in future energy systems with high shares of renewable energy sources. The electrical demand has to react to the fluctuating electricity generation of renewables. To this end, flexible electrical loads like electric heating devices and electric vehicles are necessary in combination with optimization approaches. In this paper, we develop a novel privacy-preserving approach for decentralized optimization to exploit load flexibility in residential areas. This approach, which is based on a set of schedules, is referred to as SEPACO-IDA. Compared to the approaches from the literature for decentralized optimization, SEPACO-IDA leads to improvements of between 0.8% and 13.3% regarding the surplus energy and the peak load. Furthermore, this paper illustrates the suboptimal results for uncoordinated decentralized optimization and thus the need for coordination approaches. Another contribution of this paper is the development and evaluation of two methods for distributing a central wind power profile to the local optimization problem of different buildings in a residential area (Equal Distribution and Score-Rank-Proportional Distribution). These wind profile assignment methods are combined with different decentralized optimization approaches. The results reveal the dependency of the best wind profile assignment method on the used decentralized optimization approach.

Programación Óptima de Cargas Eléctricas Flexibles a Nivel Residencial en Tiempos de Covid-19

Introducción— En este trabajo se presenta un modelo matemático de programación de cargas eléctricas flexibles y sistemas de almacenamiento de energía, apalancado por la estructuración de cargos horarios de la resolución CREG 015 del 2018 y analizado en el sector residencial en el contexto de nuevas curvas de demanda resultantes de las medidas en contra de la pandemia del COVID-19. Objetivos— Se plantean tres modelos de optimización matemática en los cuales se busca el menor costo de facturación para el usuario final a través de las características flexibles de la carga. Metodología— Se implementa para el cálculo de cargos horarios la formulación matemática descrita en la resolución CREG 015 y se obtienen tarifas horarias en tres niveles diferentes siguiendo una lógica similar a los esquemas de respuesta de la demanda denominados Time of Use. Resultados— Los resultados obtenidos permiten evidenciar que un programa de respuesta de la demanda por cargos horarios efectivamente introduce un incentivo económico durante el periodo evaluado, a través de la posibilidad de la modificación de patrones de consumo que redundan en disminución del pago de factura de electricidad. Conclusiones— El modelo propuesto de demanda de energía por medio de programación de cargas flexibles seleccionadas y la oportunidad de uso de la energía almacenada por los vehículos eléctricos, genera beneficios económicos para el usuario minimizando el costo de energía consumida diaria durante el periodo de teletrabajo en tiempos de COVID-19.

A Lyapunov Optimization-Based Energy Management Strategy for Energy Hub With Energy Router

The energy crisis and increasing concerns about the environment in modern society have fostered the development of the integrated energy system (IES) in smart grid. The energy hub (EH) is a minimum construction of the IES. The chief purpose of this paper is to propose a Lyapunov optimization-based energy management strategy for the energy hub with an energy router. First, this paper describes a configuration of the EH with an energy router and sets the basic operating principles of the energy router. Second, a method is proposed to analyze the energy balance equations of the EH. Furthermore, the problem of energy management is formulated considering the constraints of energy balance equations, energy storage, flexible loads, and other constraints of operation. Finally, energy storage and flexible electric loads are modeled as stochastic processes, and three virtual queues are constructed to relax these constraints. The Lyapunov drift-plus-penalty function is applied to formulate a relaxed form of the energy management problem. Case studies of a single EH and two-connected EHs are performed to test the effectiveness of the proposed strategy, and the results are compared with a greedy algorithm.

Distributed coordination of deferrable loads: A real-time market with self-fulfilling forecasts

Increased uptake of variable renewable generation and further electrification of energy demand necessitate efficient coordination of flexible demand resources to make most efficient use of power system assets. Flexible electrical loads are typically small, numerous, heterogeneous and owned by self-interested agents. Considering the multi-temporal nature of flexibility and the uncertainty involved, scheduling them is a complex task. This paper proposes a forecast-mediated real-time market-based control approach (F-MBC) for cost minimizing coordination of uninterruptible time-shiftable (i.e. deferrable) loads. F-MBC is scalable, privacy preserving, and usable by device agents with small computational power. Moreover, F-MBC is proven to overcome the challenge of mutually conflicting decisions from equivalent devices. Simulations in a simplified but challenging case study show that F-MBC produces near-optimal behaviour over multiple time-steps.

Quantification of energy flexibility of residential net-zero-energy buildings involved with dynamic operations of hybrid energy storages and diversified energy conversion strategies

Abstract For immediate response and sufficient reaction to building energy demands by avoiding excessive production, increasing stability of energy networks, and minimising energy congestion, building energy flexibility has potentials to enhance the resilience of hybrid grids to fluctuations in energy demands of multi-energy systems. However, few studies focused on dealing with the complexity of energy flexibility quantification regarding diversified energy conversions and hybrid energy storages. Moreover, few studies focused on the exploitation of energy potential provided by building energy systems itself through flexible energy control strategy. In this study, a generic methodology was proposed to characterise energy flexibility of diversified energy systems. A series of new flexibility indicators are proposed such as flexible power, flexible electricity, on-site flexible electric load fraction, on-site flexible surplus renewable fraction ratio, and flexibility factors. Technical solutions are proposed to improve the energy flexibility using integrated solutions of energy conversion, energy storage, and rule-based control strategies. Case studies with different control strategies (i.e. “battery-to-demand control strategy” and “renewable-to-demand control strategy”) are studied for the technical viability assessment. This study provides a generic methodology to characterise the energy flexibility regarding sophisticated building energy systems, and a rule-based control strategy for the flexibility enhancement, which will be effective in the promotion of energy flexible buildings.

Decentralized optimization approaches for using the load flexibility of electric heating devices

Electric heating devices can provide the needed load flexibility for future energy systems with high shares of renewable energies. To exploit these flexibilities, the literature often suggests centralized scheduling-based optimization. However, centralized optimization has crucial drawbacks regarding complexity, privacy and robustness while uncoordinated decentralized optimization approaches yield non-optimal results for the entire system. In this paper, we develop two novel coordinating decentralized optimization approaches, PSCO and PSCO-IDA. Furthermore, we define an optimization procedure to generate a solution pool with diverse schedules for the coordinating approaches. The results show that all investigated approaches for coordinated decentralized optimization lead to lower surplus energy and thus to higher self-consumption rates of locally generated renewable energy compared to the uncoordinated approach. Moreover, using solution pools generated by our optimization procedure strongly improves the Iterative Desync Algorithm (IDA), an effective and privacy-preserving algorithm for decentralized optimization. A comparison of the different decentralized optimization approaches reveals that PSCO-IDA leads to an average improvement of 10% compared to IDA while PSCO leads to similar results with reduced communication effort. All decentralized approaches have significantly reduced runtimes compared to centralized optimization. Our study reveals the strong advantages of coordinated decentralized optimization approaches for using flexible electrical loads.

Robustly Coordinated Operation of a Multi-Energy Microgrid With Flexible Electric and Thermal Loads

A multi-energy microgrid (MEMG) can simultaneously supply electric and thermal energy to customers to improve overall energy utilization efficiency. However, intermittency and uncertainty from renewable power generation, such as wind turbines and solar photovoltaics, as well as electric and temperature-dependent thermal loads can significantly challenge and complicate the operation of an MEMG. To conquer the challenges, this paper utilizes price-based demand response and indoor temperature control to flexibilize the electric and thermal loads, respectively. Then, a two-stage coordinated operation method is proposed to optimally coordinate the combined cooling, heat, and power plants, flexible electric and thermal loads, and thermal storage under these multiple uncertainties. The mathematical problem is modeled as a two-stage robust optimization model and solved by column-and-constraint generation algorithm. Simulation results verify high energy utilization efficiency and operating robustness of the proposed method.