Study on the operation strategy for integrated energy system with multiple complementary energy based on developed superstructure model

The energy flow in energy supply system has become further complicated due to the addition of multiple clean primary energy and the integration of energy storage technique, which gives rise to the main challenges for integrated energy system (IES) designing on how the IES coordinates the start and stop or varying load operation of multiple equipment so as to maximize the energy conservation and emission reduction and economic benefits. In this paper, with the integration of multiple primary energy utilization technologies and combination of various energy conversions and storage equipment, a superstructure model of IES with multiple complementary energy is established by the way of gradually decomposing and modeling, taking the optimal annual total cost (ATC), primary energy consumption (PEC), and CO₂ emission (CE) as the objective function, which can harmonize the energy supply and demand restrictions and the relations of energy flow in the subsystems of energy production system (EPS), energy conversion system (ECS), and energy storage system (ESS). The scientific installed capacity and optimum operation strategy can be solved by this model, which is applied for the designing of integrated energy supply scheme for one certain park. The result shows that the model is both suitable for the energy supply scheme research and the scientific and rational planning and designing for integrated energy of IES with multiple complementary energy.     

A model for planning energy requirements for residential heating

A model is presented for planning the energy required for heating residential areas, and a case study where the model has been applied to an urban area in Sweden is discussed. The model has been used as a basis for decisions concerning mainly local and regional energy planning in Sweden. The model is a combined dynamic simulation and optimization model. The results are obtained through optimal balancing of investments in heat supply and energy conservation.     

Modelling and control of hydrogen and energy flows in a network of green hydrogen refuelling stations powered by mixed renewable energy systems

The planning of a hydrogen infrastructure with production facilities, distribution chains, and refuelling stations is a hard task. Difficulties may rise essentially in the choice of the optimal configurations. An innovative design of hydrogen network has been proposed in this paper. It consists of a network of green hydrogen refuelling stations (GHRSs) and several production nodes. The proposed model has been formulated as a mathematical programming, where the main decisions are the selection of GHRSs that are powered by the production nodes based on distance and population density criteria, as well the energy and hydrogen flows exchanged among the system components from the production nodes to the demand points. The approaches and methodologies developed can be taken as a support to decision makers, stakeholders and local authorities in the implementation of new hydrogen infrastructures. Optimal configurations have been reported taking into account the presence of an additional hydrogen industrial market demand and a connection with the electrical network. The main challenge that has been treated within the paper is the technical feasibility of the hydrogen supply chain, that is mainly driven by uncertain, but clean solar and wind energy resources. Using a Northern Italian case study, the clean hydrogen produced can be technically considered feasible to supply a network of hydrogen refuelling stations. Results show that the demands are satisfied for each time period and for the market penetration scenarios adopted.     

Cross-regional integrated energy system scheduling optimization model considering conditional value at risk

Integrated energy system is a very important way to improve energy efficiency. Based on the combined heating cooling and power system, combined with energy storage equipment, a cross-regional integrated energy system scheduling optimization problem is studied. An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region. Meanwhile, the value at risk (VaR) theory is introduced and the operating constraints of equipment in the integrated energy system fully considered, the integrated energy system scheduling model with VaR is established. The example shows that the model can realize multi-type electrical, heating, and cooling load optimized by schedule across regions under the premise of satisfying the balance of energy supply and demand, which can reduce the system operation cost. The sensitivity analysis of the minimum expected cost and the influencing factors of conditional VaR is carried out to verify the validity and feasibility of the proposed model.

• An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region.
• By using the conditional value at risk theory to consider various types of the integrated energy system complements and evaluates the operational risk of the system under optimal operating conditions of the system.
• The total cost of system scheduling operation is proportional to the storage capacity, which is inversely proportional to the heat storage capacity and inversely proportional to the pipeline capacity within a certain interval.

     

基于能量枢纽的综合能源系统优化规划

  [目的]  提出了基于能量枢纽的综合能源系统优化规划模型用于解决综合能源系统长期规划问题。  [方法]  能量枢纽(Energy Hub)是分析综合能源系统的重要模型,代表各种不同能源形式之间的耦合关系,例如电力,天然气,供热系统等。  [结果]  此综合能源系统优化规划模型在考虑系统可靠性,能源效率,排放指标等多种决策因素的情况下解决了不同能源形式之间的最优规划问题。  [结论]  综合能源系统算例分析用于验证该模型用于优化规划综合能源系统的有效性,并表明基于能量枢纽的综合能源系统针对系统的长期规划具有更大的灵活性,是研究综合能源系统规划的重要方向。     

Mathematical model for energy planning of rural India

This paper describes an integrated energy system planning approach for Wardha District in Maharashtra State, India, for the year AD 2000 and gives an optimal mix of new/conventional energy technologies using a computer-based mixed integer linear programming model. The district level planning is accomplished by successively applying in two stages a new statistical extrapolation technique for moving first from the village level energy scenarios based on surveys to the corresponding energy scenarios at the block level and then for moving next from the block level scenarios to the desired district level planning profile. The model is suitably scaled for obtaining the optimal results at the district level owing to limitations on the available memory on the PC-AT system in use. Energy options for seasonal crops have been considered explicitly in the model. Post-optimal analysis based on a linear programming model to study the effect of the variations in parameters on the optimal solution has been performed.     

RIEP: Regional integrated energy plan

The energy planning endeavours for a particular region involves the finding of a set of sources and conversion devices so as to meet the energy requirement/demand of all the tasks in an optimal manner. This optimality depends on the objective to minimise the total annual cost of energy and the dependence on non-local resources or maximise the overall system efficiency. Factors such as availability of resources in the region and task energy requirements impose constraints on the regional energy planning exercise. Thus, regional energy planning turns out to be a constrained optimisation problem. This paper describes an optimum energy allocation using integrated energy planning approaches for Uttara Kannada district and makes a satisfying energy allocation plan for the years 2005, 2010 and 2015. Integrated energy planning gives an optimal mix of new/conventional energy sources and is developed based on decision support systems (DSS) approach.The central theme of the energy planning at decentralised level would be to prepare regional energy plans to meet energy needs and development of alternate energy sources at least- cost to the economy and environment. Regional integrated energy planning (RIEP) mechanism takes into account various available resources and demands in a region. This implies that the assessment of the demand supply and its intervention in the energy system, which may appear desirable due to such exercises, must be at a similar geographic scale. Regional energy planning exercises need to be flexible (to cope with rapidly changing energy systems) and easy to use. The application of DSS is a new approach to this problem. Towards the goal of implementing analytical methods for integrated planning, computerised decision-system provides useful assistance in the analyses of available information, the projection of future conditions, and the evaluation of alternative scenarios. Some of the features of DSS found particularly useful in regional energy planning are: (i) flexible structure—allows appropriate feasible levels of disaggregation, (ii) integrated nature—promotes a better overall understanding of many processes and concepts involved in planning, allowing planners to concentrate on specific energy subsectors, and (iii) iterative nature and easy scenario testing features—provide guidance in optimising data collection activities. Regional integrated energy plan (RIEP) is a computer-assisted accounting and simulation tool being developed to assist policy makers and planners at district and state level in evaluating energy policies and develop ecologically sound, sustainable energy plans. Energy availability and demand situation are projected for various scenarios (base case scenario, high-energy intensity, and transformation, state-growth scenarios) in order to get a glimpse of future patterns and assess the likely impacts of energy policies.The application of DSS for Uttara Kananda district energy planning focuses on renewable resources that could be harnessed for energy, land use database, sectorwise energy demand database and optimal allocation of energy resources for various tasks, and then explore the energy use consequences of alternative scenarios, such as, base case scenarios, high-energy intensity and improved end use efficiency options. Linear programming formulation for optimum allocation based on the cost minimisation objective shows that there is substantial savings of about 19.19% in energy and 36.24% cost reduction in overall energy system. Cost per unit (kWh) of energy with optimal allocation of energy is Rs. 0.31/kWh (as against Rs. 0.39/kWh without optimisation). Optimisation carried out with the objective of maximisation of efficiency of ‘ijk’ combination for all combinations shows energy saving of 19.98% and cost of energy as Rs. 0.34/kWh. The scenario analyses reveal that relatively vigorous growth in energy demand in Uttara Kannada district can be accomplished without exceeding available resources.     

Multicarrier energy systems: Optimization model based on real data and application to a case study

Multicarrier energy systems are increasingly used for a number of applications, among which the supply of electricity, heating, and cooling in buildings. The possibility of switching between different energy sources is a crucial advantage for the optimal fulfillment of the energy demand. The flexibility of these systems can benefit from the integration with smart grids, which have strong variations in time during their operation. The energy price is the parameter that is usually considered, but also the primary energy factor and the greenhouse gases emissions need to be accounted. This paper presents an application of an operational optimization method for a multicarrier energy system, based on real data–driven model and applied to different countries. The generation plant of a hospital is considered as case study, coping with multiple energy needs by relying on different conversion technologies. The optimal operation of the system shows a wide range of variability, depending on the chosen objective function, the hour of the day, the season, and the country. The results are affected mostly by the energy mix of the electricity supplied from the power grid, which has a direct influence on the primary energy consumption and the greenhouse gases emissions and an indirect influence on the electricity prices.     

Potential evaluation of power-to-hydrogen-to methane conversion technology in robust optimal energy management of a multi-energy industrial park

Multi-energy industrial parks are required to render a huge variety of services in an eco-friendly, secure, reliable, and affordable way. The industrial energy park is a separate area consisting of multiple distributed generations, energy storage systems, etc., which supply local gas, heating, and electrical consumers. Meanwhile, the integration of power-to-X technologies such as power-to-gas and power-to-heat, which convert the electricity into other forms of energies while facilitating the integration of renewable energy in the industrial park, can enhance the flexibility and efficiency of energy supply. Therefore, this paper proposes novel robust energy management of multi-energy industrial parks integrated with wind power resources, cogeneration units, power-to-X technologies, and demand response programs to total operation cost minimization. The industrial park can simultaneously participate in a multi-energy market, including power, thermal, and gas markets, to meet local heating, gas, and electrical load. The robust optimization framework is extended to address the power price uncertainty and manage the conservatism level of the operator against price variability. The proposed model is examined on the industrial park test system, and numerical results will be presented for the different cases. Under the robust energy management, the total operation cost of the multi-energy industrial park reduces up to 53 %.     

Decision support tools for advanced energy management

Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices.     

The value of flexibility for pulp mills investing in energy efficiency and future biorefinery concepts

Changing conditions in biomass and energy markets require the pulp and paper industry to improve energy efficiency and find new opportunities in biorefinery implementation. Considering the expected changes in the pulp mill environment and the variety of potential technology pathways, flexibility should be a strong advantage for pulp mills. In this context, flexibility is defined as the ability of the pulp mill to respond to changing conditions. The aim of this article is to show the potential value of flexibility in the planning of pulp mill energy and biorefinery projects and to demonstrate how this value can be incorporated into models for optimal strategic planning of such investments. The paper discusses the requirements on the optimization models in order to adequately capture the value of flexibility. It is suggested that key elements of the optimization model are multiple points in time where investment decisions can be made as well as multiple scenarios representing possible energy price changes over time. The use of a systematic optimization methodology that incorporates these model features is illustrated by a case study, which includes opportunities for district heating cooperation as well as for lignin extraction and valorization. A quantitative valuation of flexibility is provided for this case study. The study also demonstrates how optimal investment decisions for a pulp mill today are influenced by expected future changes in the markets for energy and bioproducts. Copyright © 2014 John Wiley & Sons, Ltd.     

An interactive optimization model for energy systems planning associated with clean‐energy development under uncertainty

In this study, an interactive fuzzy chance‐constrained resolution (IFCR) method is developed for supporting energy systems planning (ESP) under uncertainty. IFCR can not only tackle multiple uncertainties presented as fuzzy membership functions and probability distributions using an interactive resolution method, but also enable decision makers to seek optimal solutions between satisfaction degree of objective and feasibility of constraints. Then, an IFCR‐ESP model is formulated for energy systems of Bayingolin Mongol Autonomous Prefecture (abbreviated as Bazhou). Results provide decision makers with a complete view of the relationship between uncertain inputs and solutions. Policy‐based solutions concerning energy consumption, electricity generation, capacity expansion, pollutant emission, and system cost are analyzed, which can help decision makers to identify desired strategies for ESP. Results indicate that transitioning from the conventional energy system to a sustainable one is associated to policy support, resources availability, energy supply security, and capital investment; clean energy policy (e.g. shift from coal to gas) is an effective way to facilitate the local energy system development in a sustainable manner; the solutions under different feasibility degrees can help decision makers to conduct in‐depth analyses of tradeoffs between system cost and constraint‐violation risk in an interactive way. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimal operation of integrated energy system including power thermal and gas subsystems

As a form of hybrid multi-energy systems, the integrated energy system contains different forms of energy such as power, thermal, and gas which meet the load of various energy forms. Focusing mainly on model building and optimal operation of the integrated energy system, in this paper, the dist-flow method is applied to quickly calculate the power flow and the gas system model is built by the analogy of the power system model. In addition, the piecewise linearization method is applied to solve the quadratic Weymouth gas flow equation, and the alternating direction method of multipliers (ADMM) method is applied to narrow the optimal results of each subsystem at the coupling point. The entire system reaches its optimal operation through multiple iterations. The power-thermal-gas integrated energy system used in the case study includes an IEEE-33 bus power system, a Belgian 20 node natural gas system, and a six node thermal system. Simulation-based calculations and comparison of the results under different scenarios prove that the power-thermal-gas integrated energy system enhances the flexibility and stability of the system as well as reducing system operating costs to some extent.     

A multiobjective programming approach to energy resource allocation problems

The optimal allocation of energy resources to various energy end uses is an important strategy for bridging the energy supply and demand gap in India. It has been recognized that the allocation should be guided by multiple criteria. A multiobjective programming model for such an allocation process is presented in the paper. The normative model has been applied for the households sector of Madras city. The model is solved using non pre-emptive goal programming. Variations in the original model have been made to build alternative scenarios. The results of the original model and the alternative scenarios indicate that the use of solar thermal energy, natural gas, LPG, fuelwood, kerosene and lignite should be promoted for cooking, and the use of grid electricity and diesel, should be promoted for meeting water pumping demands. They favour the use of electricity generated from diesel for lighting, and the use of solar photovoltaics for meeting the electricity demands of household appliances. The results also indicate that grid electricity and electricity generated from fuelwood should be promoted to meet the demands of all the four household end uses, and point to the need for more research into solar photovoltaics, which may become competitive for meeting household demands in the future.     

Linear mixed-integer models for biomass supply chains with transport,storage and processing

This paper presents a linear mixed-integer modeling approach for basic components in a biomass supply chain including supply, processing, storage and demand of different types of biomass. The main focus in the biomass models lies on the representation of the relationship between moisture and energy content in a discretized framework and on handling of long-term processes like storage with passive drying effects in the optimization. The biomass models are formulated consistently with current models for gas, electricity and heat infrastructures in the optimization model ‘eTransport’, which is designed for planning of energy systems with multiple energy carriers. To keep track of the varying moisture content in the models and its impact on other biomass properties, the current node structure in eTransport has been expanded with a special set of biomass nodes. The Node, Supply, Dryer and Storage models are presented in detail as examples of the approach. A sample case study is included to illustrate the functionality implemented in the models.     

基于主从博弈理论的综合能源系统优化运行方法

综合能源系统作为实现智慧能源的关键技术形式,其优化运行问题是一门重要课题。针对综合能源系统优化运行问题,考虑到系统多能互补协调,基于主从博弈理论进行建模。其中:主体博弈模型以多能互补协调计划为博弈策略,以综合能源系统综合运行成本最小化为博弈支付,计及多能互补协调约束等必要约束条件;从体博弈模型以各个形式能源子网的运行计划为博弈策略,以能源子网运行收益最大化为博弈支付,计及分布式供能设备运行约束等必要约束条件。分析得到主从博弈模型的纳什均衡,基于混沌粒子群算法设计模型求解流程。最后通过仿真算法表明,所建立的模型适用于综合能源系统优化运行方案制定,能够显著降低系统运行成本。     

含冷、热、电、气的园区综合能源系统选址定容规划案例分析

为实现含冷、热、电、气的园区综合能源系统的多能互补优势和能量梯级利用,以某园区综合能源系统项目实例为基础,从资源评估、负荷预测、综合能源系统建模、优化算法求解、区域供能站和管网规划原则等方面进行详细的案例分析。构建上层网损最小,下层全寿命周期内经济性最优的双层选址定容规划模型,通过改进粒子群算法进行优化求解,得到近景和远景区域供能站和各能源管网的最优选址定容方案,并结合项目数据验证了其合理性。将综合能源规划方案和传统分供规划方案进行对比,结果表明前者具有更好的经济性和节能性,可为园区级综合能源系统规划项目提供参考和思路。     

多区域间热网交互的综合能源系统配置优化

考虑多区域间热网交互的综合能源系统规划和运行优化能有效提高能源综合利用率,有助于节能减排、促进分布式能源就地消纳。在独立分区综合能源系统的基础上,在不同负荷特性区域间引入热网交互,以热网建设费用、CCHP设备投资、运行成本和碳排放税最低为综合优化目标,对多区域综合能源系统的配置和运行进行整体优化。对上海市某典型城区进行仿真优化结果表明,多区域间热网的引入有利于提高系统清洁能源利用率,合理配置设备容量,区域间用能互补特性增强,系统综合效益更佳。     

含冷、热、电、气的园区综合能源系统选址定容规划案例分析

为实现含冷、热、电、气的园区综合能源系统的多能互补优势和能量梯级利用,以某园区综合能源系统项目实例为基础,从资源评估、负荷预测、综合能源系统建模、优化算法求解、区域供能站和管网规划原则等方面进行详细的案例分析。构建上层网损最小,下层全寿命周期内经济性最优的双层选址定容规划模型,通过改进粒子群算法进行优化求解,得到近景和远景区域供能站和各能源管网的最优选址定容方案,并结合项目数据验证了其合理性。将综合能源规划方案和传统分供规划方案进行对比,结果表明前者具有更好的经济性和节能性,可为园区级综合能源系统规划项目提供参考和思路。     

A computer-aided planning (CAP) system for the gas engine co-generation plant

The objective of this study is to develop a computer-aided optimal planning (CAP) system for the initial design of the cogeneration plant composed of combining a gas engine-driven generator, electric and gas refrigerators, gas engine- and electric-driven heat pumps, gas boiler, single effect refrigerator, heat exchanger, etc. In the CAP system, it is first necessary to effectively determine the energy demand categorized by electric power, space heating and cooling, and hot water supply, together with the configuration of the plant's equipment and the tariff of fuel by utilizing the man-machine interactive ability of a personal computer. Then to calculate the optimal operation of the co-generation plant; the load allocation problem is investigated based on the mixed-integer linear programming method by adopting zero-one integer variables indicating the on/off status of operation, together with continuous variables indicating the operational level of each equipment. By using the branch and bound algorithm, the optimal operational policy is determined by a large computer. Lastly, the economical comparison of some alternative plants is made based on the annual cost method obtained on the above results.