Integrated Community Energy System Research Articles

Stochastic robust optimal operation of community integrated energy system based on integrated demand response

In the context of the rapid development of the energy internet, the traditional power demand response has gradually expanded to an integrated demand response. Multiple energy sources such as electricity, gas, heating, and cooling, are coupled and coordinated in integrated energy system, which is conducive to improving comprehensive energy utilization efficiency and providing more opportunities for the demand side to participate in system optimization. This paper focuses on the optimal operation of community integrated energy system (CIES). From the perspective of demand response, the horizontal complementary substitution and vertical time shift strategy of electric-gas-heating-cooling are introduced based on the interactive response characteristics analysis of multiple energy loads, and the cooperative complementarity and flexible transformation of multiple energy sources are taken into account to establish a stochastic robust optimal operation model of CIES based on integrated demand response. In this paper, a mixed-integer linear programming method is applied to solve the model, and the simulation results show that the proposed method can effectively reduce the operation costs and promote a balance between energy supply and demand while further tapping the potential of the energy demand side and achieving the economical, flexible and efficient operation of community integrated energy system.

A Two-Stage Configuration Method of Integrated Community Energy System Considering Demand Response

The integrated community energy system (ICES) has aroused considerable attention for its low emission and high operating efficiency. The existing configuration methods for ICES with multi-energy sectors ignored the controllable load. In this paper, a two-stage configuration method of ICES is developed to achieve the minimum annual investing and operating cost. At the first stage, the capacities of components in ICES are optimized to minimize the annual investment cost of ICES. At the second stage, the annual operating cost including the electricity and gas purchase costs and the component maintenance cost is minimized to satisfy the energy load. The controllable load under the time-of-use energy price in seasonal typical days is considered in the second stage. Relevant simulations are conducted to validate the effectiveness of the proposed configuration method for ICES. Considering the controllable load, comparative simulations illustrate that the proposed configuration method can significantly reduce the battery investment cost.

Optimal Dispatch of Integrated Community Energy System Considering Energy Flexibilities in Pipelines and Buildings

The development of cogeneration, distributed generation, information and communication technology has facilitated the application of integrated community energy system (ICES). However, some ICESs may lack operational flexibility due to the strict constraints of community heating system (CHS), which reduce the energy efficiency of ICESs. To solve this problem, an optimal dispatch model of ICES considering energy flexibilities in pipelines and buildings is proposed, in which the thermal dynamics of pipelines and buildings are described by node method and equivalent thermal parameter (ETP) method. The objective of the proposed dispatch method is to minimize the daily operation cost of ICES. What’s more, renewable energy accommodation cost and power purchase cost are both analysed to verify the improvement of ICES flexibility. It is demonstrated that the proposed method can unlock the flexibility of CHS and improve the energy efficiency of ICES.

A Planning Method for Energy Storage System of Integrated Community Energy System Considering Demand Response

Demand response plays a significant role in peak load shifting, storage capacity configuration and renewable energy utilization. A bi-level planning method for energy storage system of integrated community energy system considering the demand response is proposed in this paper. In the upper level, the investment cost of electrical energy storage and thermal energy storage, operation and maintenance cost and fuel cost of the integrated community energy system, as well as the compensation cost to the energy consumer, are considered; in the lower level, the responded demand of the energy consumer is taken into consideration to minimize the energy bill of the energy consumer. An actual planning for energy storage system of integrated community energy system shows the effectiveness of the proposed method.

Research on Integrated Energy Simulation System of Distribution Network

This article discussed multiple energy flow simulation technology based on the research status of integrated community energy system. Under the unified platform architecture, simulation, planning, optimization, and analysis of distribution multiple energy flow are realized. According to the idea of three cascades of energy utilization, the modeling of equipment in various professional fields is completed under unified software architecture, and the simulation system is finally developed. The system is built with plug-in software, which is open and extensible. The simulation system developed in this paper can be used in the simulation of distribution integrated energy system to realize the interaction between energy flow and information flow.

A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies

The energy hub is considered a unit where multiple energy carriers can be converted, conditioned, and stored, thereby providing the functions of input, output, conversion, and storage of multiple energy carriers using a defined coupling matrix. Thus, the energy hub is widely used in the planning and operation of integrated energy systems. However, the coupling factors (or the efficiencies of the energy conversion devices) in the energy hub coupling matrix are usually assumed to be constant for the sake of simplicity, which may result in unreasonable planning and operation schemes for the integrated energy system. For this reason, an integrated energy system planning method at the community level that considers varying coupling factors was developed in this study. First, a dynamic energy hub model was developed, where an efficiency correction model was built to determine the time-varying coupling factors with the variation in load rate. On this basis, a double-layer planning model was built to determine the optimal planning and operation schemes for the integrated community energy system. A typical integrated community energy system was employed as a test system to illustrate the effectiveness of the planning method, and the results were analysed.

The energy management strategies based on dynamic energy pricing for community integrated energy system considering the interactions between suppliers and users

The proliferation of cogeneration technology, information and communication technology has facilitated the integrations of different energy infrastructures and markets. In this paper, the energy management of an integrated energy system composed of multiple energy hub operators and numerous integrated energy providers is formulated as dynamic energy pricing problem. From the perspective of maximizing social welfare, a distributed gradient projection iterative algorithm is proposed to decide the dynamic energy prices and optimal operation strategies of all the participants. Furthermore, the dual decomposition method is employed to decouple the coupled constraints and the primal problem is decomposed into several independent subproblems which can be solved in a distributed manner without violating privacy. Simulation results indicate that the proposed energy pricing algorithm shows a good convergence and availability, which can guarantee the supply-demand balance in each time slot, as well as promote the interactions between the energy supply and consumption sides.

Integrated Energy Load Priority Scheduling Model Based on Customer Satisfaction

The integrated energy system is of great significance to improve the efficiency of social energy utilization, promote the large-scale consumption of renewable energy and the cascade utilization of energy. In view of the uncertainty of cooling, heating and electric load demand of users, this paper proposes a load priority supply model for integrated energy service providers, which considers the user satisfaction and the penalty function of energy supply interruption, and is used to deal with the scheduling optimization of various uncertain energy demand and translatable load. The optimal scheduling mathematical model of community integrated energy system is established. The various optimization objectives and the constraints of different energy demand are considered, the heuristic algorithm is used to solve the optimal scheduling, and the economic of operation mode is analyzed. The model can effectively reflect the impact of energy demand, user satisfaction and system cost on the priority of supply load, and provide the optimal decision to weigh the system cost and user satisfaction. The simulation results show the feasibility and effectiveness of the proposed model.

Optimal Operation Strategy of a Community Integrated Energy System Constrained by the Seasonal Balance of Ground Source Heat Pumps

Ground source heat pumps (GSHPs) are now widely used in community integrated energy systems (CIES) because of their high efficiency in energy conversion. However, the coefficient of performance (COP) of GSHPs is unstable if the soil temperature changes with seasonal imbalanced cooling and heating loads, thus downgrading the overall performance of CIES. In this paper, an annual optimization model for CIES that considers the seasonal balance of GSHPs is established. Then, a day-ahead operation strategy based on the pre-allocated load of the GSHP in the yearly balance is proposed while considering the uncertainties in daily conditions. The proposed strategy is validated on a practical CIES in China and assessed on a year-round time scale. The results show that the operation of CIES can be stable, economical and sustainable while ensuring the seasonal balance of the GSHP.

Remote community integrated energy system optimization including building enclosure improvements and quantitative energy trilemma metrics

Design strategies for sustainable energy systems in remote communities require holistic approaches, as policy, technological development and complex energy systems operation are inherently intertwined. The present work takes a multi-domain perspective in which various energy solution philosophies co-exist. In particular, a multi-objective energy system model has been developed to determine the optimal configuration of integrated electrical and thermal energy systems for Sachs Harbour, the Northernmost community in the Northwest Territories of Canada. From the four scenarios implemented in the model, the Pareto front curves show that the fuel consumption can vary from 0 to 700,000 L/yr while the cost of energy is in the range of 0.5–2.7 CND $/kWh. Further, a comparative dynamic simulation has been carried out to analyze the impacts of using electric baseboard heaters versus air-source heat pumps. The results indicate that load fluctuations caused by the variations of the heat pumps’ coefficients of performance negatively impact the operation of the energy system. These demand fluctuations result in a larger battery storage requirement, along with an increase in overall energy system costs. Building enclosure improvements alone were found to reduce space heating loads by up to 40%. Finally, nine solutions of interest from the Pareto front were quantified and tested in the energy trilemma index model. From the multiple viable configurations, the proposed solution was estimated to have a weighted average trilemma score of 73.3. Overall, the use of such innovative modeling approaches in real-world applications can support policy makers to make informed decisions in balancing trade-offs from various energy solution viewpoints.

Stakeholders’ Interests in Developing an Energy Ecosystem for the Superblock—Case Hiedanranta

Policy objectives aimed toward zero-energy buildings call for the utilization of building-integrated renewable energy and distributed energy resources (DER). To enhance the utilization of DER, previous literature proposed the concept of an integrated community energy system (ICES). This research suggested using superblocks (units of multiple urban blocks) to define geographical limits, social contexts, and possibly common administrations for ICESs along with other living- and sustainability-related activities in an urban context. Through interviews with key stakeholders and an analysis, this research investigates the applicability of the superblock-ICES as a way of reaching the low-carbon objectives in the Hiedanranta brownfield development project in the city of Tampere, Finland. This research confirms that the driving forces of community-based solutions are economic benefits, technical development, and objectives of sustainability, and reveals or confirms that social acceptability, missing planning practices, economic risk, and missing or hindering legislation are the main issues or barriers of superblock-ICESs. For a wider adoption of superblock-ICESs, this research suggests cross-disciplinary piloting, together with developing planning practices and simulation tools. In Finland, legislative reforms are needed to remove the barriers and clarify issues related to security, reliability, customer protection, and public interest in governing a locally and collectively owned energy system.

Trilateral Planning Model for Integrated Community Energy Systems and PV-Based Prosumers—A Bilevel Stochastic Programming Approach

This paper proposes a trilateral bilevel stochastic mixed integer bilevel linear programming (MIBLP) model to handle a joint master-slave operation-planning problem. This model considers the interactions among an integrated community energy system (ICES), prosumers, and the wholesale electricity market (WM). The ICES, in the upper level, makes a joint optimal photovoltaic (PV) and energy storage system plan taking into account the concurrent interactions with the WM and prosumers to maximize its profit. On the other hand, in the lower level, the prosumers aim at minimizing their bills via an optimal PV-package sizing while interacting with the ICES and the WM simultaneously. The strong duality theorem is used to recast this MIBLP model into an equivalent single-level model. Since the lower level is also an operation-planning problem, this recast results in a mixed integer nonlinear programming (MINLP) model that prevents finding a satisfactory solution. To remedy this issue, sensitivity analysis and a separation-based linearization technique are applied. Numerical results illustrate the effective performance of the proposed business model while providing valuable information for the ICES and consumers.

Reliability modeling for Integrated Community Energy System considering dynamic process of thermal loads

The Integrated Community Energy System (ICES) has developed rapidly, but the reliability assessment models of ICES are somehow out of date. A new reliability assessment model for ICES is proposed incorporating electricity, gas and heat, considering dynamic process of thermal loads. First, the static model of ICES consisting of three subsystems is constructed based on the energy hub model. Then the inertial features of loads are incorporated in the reliability of ICES. Thereafter, a quasi-sequential simulation based on a decomposed optimisation method is proposed to assess the reliability of ICES. Case studies are conducted on an ICES with four energy hubs to validate the performance of the presented model. Results show that the proposed reliability assessment model is more practical and the identified weak points of each subsystem have changed after utilising the new model.

Model predictive control based robust scheduling of community integrated energy system with operational flexibility

Community integrated energy system (CIES) couples multiple energy forms and links, it is important to cope with the inadequacy of flexibility for realizing efficient utilization and reliable supply. Based on the detailed modeling of central energy station, district heating network (DHN) and building loads, a unified scheduling model is established by fully considering the coupling characteristics of the sources, the networks, and the loads. Meanwhile, the flexibilities from adjustable capacity of thermal storage device and the indoor temperature on the demand side, as well as the energy storage of DHN, are utilized to improve the economy. Furthermore, a model predictive control (MPC) based robust scheduling strategy is proposed to maintain and utilize CIES flexibility for enhancing the uncertainty adaptability. The scheduling framework consists of rolling optimization and robust constraint generation. The rolling optimization schedules the system with a better adaptation to flexibility demands, and the robust constraints generate adjustable margin for building demands by modifying the upper/lower and ramping limits. After the linearization of nonlinear terms in the model, case studies are conducted based on the data of a typical day in summer. The results show that the unified source-network-load scheduling strategy can give full play to the flexibilities of different energy links with a better operation economy. Additionally, the MPC-based optimization can well adapt to the rolling forecasting uncertainties, and the schedule generated by advance reserving means has stronger robustness for real-time errors.

Resilient Configuration Approach of Integrated Community Energy System Considering Integrated Demand Response Under Uncertainty

Integrated community energy system (ICES) enables multi-energy synergy and impulses interaction of integrated demand response (IDR) from the demand side. Nevertheless, the randomness lies in IDR resources and renewable generation in the ICES configuration issue still lacks thorough analysis. Furthermore, the widely focused concern of resiliency urges more proactive consideration of potential emergencies at the planning stage of ICES. To this end, this paper proposed a resilience-oriented stochastic ICES configuration framework considering IDR influence. First, generalized IDR models are set up in detail with elaborate fuzzy feature analysis of price-responsive multi-energy loads. Then, the vulnerability indicators of tie lines and converting devices of the ICES are first introduced to demonstrate the occasional outage in the normal operation and blackout in the emergent case. In addition, the worst-case conditional value-at-risk (WCVaR) theory is innovatively integrated to the traditional risk-neutral model, which is formulated as a two-stage stochastic chance-constrained programming problem, aiming to combine portfolio with minimizing the worst-case cost caused by a disaster. The models are then transformed into mixed-integer linear programming problems via several linearization techniques. Finally, the results of the case studies showed the established model’s superiority in improving the overall economy (reduce 6.94% of the worst-case cost) and system resiliency (decrease the value-at-risk by 3.20%) against an unforeseen hurricane. Meanwhile, the ICES reliability was also improved by declining 25.65% of unintended load curtailment faced with an emergency. The proposed approach provided an efficient preventive portfolio scheme of the IDR-integrated ICES for decision-makers’ different risk preferences of natural hazards.

Urban energy system planning from wide area network perspective

The urban energy system, consisting of multiple subsystems ranging from energy production, transformation, transmission, storage, to consumption, plays a critical role in the national and regional energy network. Due to its complexity, to optimize the urban energy system from multiple aspects and scales are necessary. Currently, a large number of urban energy planning studies have focused on optimization methods and theories targeting integrated energy systems at community scale. Several energy system optimization models have also been developed based on different technical ideas. However, from a wide area perspective, the integrated community energy system represents a small local network in the overall urban energy system network. Neglecting the mutual interaction between the local network and wide area network can result in a severe segmentation issue and low energy efficiency. But it is impractical to take into account each end-user individually during the optimization of the urban energy system, since the construction activities involved in the energy demand-supply planning cover a wide range of aspects and a long period. Therefore, the coordination between the local and overall energy networks requires in-depth exploration of the incidence relation among them. In this study, the formation of the urban energy demand and supply chains and the structure of urban energy flow network being described by tracking the energy flow from the end-users to the energy source extraction. Based on the concepts of primary energy market and secondary energy market in urban regions and local areas, respectively, the differences and connections between energy flow networks from the supply and demand sides have been discussed. Subsequently, a two-layer four-stage urban energy planning system was proposed based on the planning objects and contents. Furthermore, the typical nested and parallel relations between different local networks were proposed based on energy transformations and dissipation flows. From the structure investigation of urban energy network, such conclusions are listed as flows: (1) The overall energy flow network can be divided into two independent layers. The first network is responsible for the optimization of energy extraction from sources and the trade of energy between difference cities. The formation and evolution of the first network is dominated by the price mechanism of primary energy. The second network is focused on the local distribution of different energy resources (e.g., electricity, gas) based on the demand, and its formation and evolution are governed by the urban municipal plan (local regulations or policies). These two energy markets are independent systems interconnected by the energy price and the demand-supply information. (2) The topology of the primary energy market is flat, which indicated that there is no apparent monopoly of information or controlling center in the market. Therefore, the trading flow of energy resources forms naturally under the influence of price mechanisms. The secondary energy market is, however, controlled by an information center where the centralized processing of the scattered end-user information leads to a highly controlled limited energy market. (3) In order to integrate the different urban energy sources into an overall energy planning scheme, the current energy distribution situation with fixed beneficiaries should be changed drastically. However, there is a lack of leadership and motivation to drive such change. (4) The cost of electricity and gas used for cooling and heating in urban areas has a high impact on the secondary energy planning. An improper choice of energy price system will adversely affect the process of reducing energy consumption. (5) Establishing a smart energy supply system in urban areas requires a synergetic integration of information systems for both energy and social-economic systems. However, currently there is no study on the mutual interaction between energy systems and social-economic systems.

Modeling and optimal operation of community integrated energy systems: A case study from China

The operation of community integrated energy systems (CIESs) is challenging because it is necessary to couple energy production, conversion and consumption on the end-user side. Multiple energy demands need to be fed simultaneously with the goal of economy and reliability. This paper formulates the optimal scheduling problem based on a real community integrated energy system in China. The system has multiple chillers (i.e. three ground source heat pumps, two conventional water-cooled chillers and two double-duty chillers) and two types of thermal storage devices (i.e. two cold water tanks and an ice-storage tank). Based on detailed device modeling, a community integrated energy system operation strategy considering unit commitment is proposed, and then is transformed into a mixed-integer linear programming model by linearization of nonlinear items. Case studies are conducted based on the data for a typical day in summer. The results show that the proposed strategy can utilize the flexibility of the energy storage devices and realize an economic and reliable operation of the community integrated energy system by coordinating various energy devices. The strategy can also reduce the startup/shutdown frequency of chillers significantly.

Synergistic Scheduling in Integrated Community Energy System Considering Wind Power Accommodation

To address wind power curtailment by the mechanism of “ordering power by heat”, integrated community energy system (ICES) is firstly established based on a major breakthrough in large-scale centralized power supply; then, a day-ahead scheduling optimization model for ICES is built by quantum-behaved particle swarm algorithm, and the rigid coupling between heating network and power grid is improved by adjusting CHP output; finally, the influences of energy storage devices and energy interactions on CHP output are analyzed in a typical case, and the improved wind power accommodation capability is obtained to verify the correctness and practicability.

An optimal dispatching method for integrated community energy systems based on the economic optimality

In order to strengthen the community energy interconnection and promote the optimization and complementation of various energy sources, the scheduling of the integrated community energy system (ICES) has become the basic work of the development of community energy systems. At the same time, the economic dispatch of ICES is an important measure to accept new energy and improve the economic performance of community energy consumption. Without a suitable economic dispatching method, the system cannot fully accept new energy, which will cause the decrease of overall efficiency of the integrated energy system. For the object of economic optimization, this work proposes a holistic optimization dispatching method of several energy devices (electric boilers, hot water tanks and heat pumps) to minimize the operation cost of ICES. Considering that under low temperature the utilization rate of heating equipment is relatively high, a typical season, winter is selected to build operation constraints models. Example analysis shows that the proposed ICES optimization dispatching method provides an appropriate dispatching scheme for the planner of the ICES. This optimization dispatching method not only reduces the operation cost, but also promotes the consumption of renewable energy.

Toward The Flexible Operation Of Integrated Community Energy System: A Two-Stage Multi-Objective Scheduling Method

Toward The Flexible Operation Of Integrated Community Energy System: A Two-Stage Multi-Objective Scheduling Method