Optimal day-ahead energy planning of multi-energy microgrids considering energy storage and demand response

Due to the environmental and economic advantages of combined heat and power (CHP) units, their use in power grids has expanded. The entry of CHP into power systems increases the complexity of the economic power flow problem. This complexity is due to the introduction of multiple constraints into problem. A mere electricity supply is not optimal in today's networks, and energies such as heat, power and gas must be planned and managed simultaneously as an energy hub. Therefore, in this paper, an intelligent multi-energy microgrid (MG) consisting of power generation units, CHP units and gas units is modeled for day-ahead energy management (DAEM). The economic distribution problem focuses on the amount of power generation, heat and gas of the units in the system. In contrast, the total generation cost of the system is minimized, and all the equality and inequality constraints of the problem are observed. The proposed microgrid includes various energy-dependent equipment such as CHP units, gas boilers, electricity-to-gas units, power and heat storage units and electric heat pumps. Also, price-based load management was included to reduce costs due to the transfer of information between the consumer and the generator in the context of smartization. Since the above problem is difficult to solve due to various constraints and decision parameters, a newly developed optimization method based on water flows was proposed. The simple movement of water flows on the ground is efficient and optimal and always follows the shortest and fastest path to reach the deepest point. In the proposed algorithm, simple movements of water in routing, a change of direction and even the creation of rapids and vortices were simulated as various mathematical operators. Finally, the proposed model and method were examined in different scenarios. The numerical outcomes demonstrated that, the proposed modeling framework is superior to hub-based multi-carrier microgrid models in terms of power system security. The sensitivity of operational expenses to changes in initial values of energy storage systems (ESS) and thermal storage system (TSS) is proved that the cost of operation reduces as the baseline values of ESS and TSS are reduced to 0.2% of the maximum capacity. Because DAEM performance is less flexible when the primary values are reduced by 0.2% of the maximum value, the system running expenses increase marginally.     

Optimal economic operation of microgrids considering combined heat and power unit,reserve unit,and demand-side management using developed adolescent identity search algorithm

In the present study, a method is proposed to solve the problem of economic load distribution in MGs, meet the challenges arising from the use of renewable sources periodically, ensure the stable performance of MGs, and minimize the operating cost of MGs considering combined heat and power (CHP) units and reserve system. Moreover, demand-side management (DSM) as a tool is employed to reduce the operating cost of the power system. Therefore, the proposed model for optimal operation of MGs using DSM is formulated as an optimization problem. Load shifting is considered as an effective solution in DSM. Minimizing the total operating cost of the system is considered as the objective function of this problem. Problem constraints include operating and executive constraints for load shifting. Finally, the model is solved using the developed adolescent identity search algorithm (AISA). In the developed model, Powell's local search operator is employed to improve the efficiency of searching for the optimal solution. Due to the existing uncertainties in load consumption and day-ahead market price, the method is presented as a scenario-based stochastic energy management problem. The results reveal the proposed method is highly efficient in solving the problem, and load management can improve economic indicators.     

Techno-economic analysis of using corn stover to supply heat and power to a corn ethanol plant – Part 2: Cost of heat and power generation systems

This paper presents a techno-economic analysis of corn stover fired process heating (PH) and the combined heat and power (CHP) generation systems for a typical corn ethanol plant (ethanol production capacity of 170 dam³). Discounted cash flow method was used to estimate both the capital and operating costs of each system and compared with the existing natural gas fired heating system. Environmental impact assessment of using corn stover, coal and natural gas in the heat and/or power generation systems was also evaluated. Coal fired process heating (PH) system had the lowest annual operating cost due to the low fuel cost, but had the highest environmental and human toxicity impacts. The proposed combined heat and power (CHP) generation system required about 137 Gg of corn stover to generate 9.5 MW of electricity and 52.3 MW of process heat with an overall CHP efficiency of 83.3%. Stover fired CHP system would generate an annual savings of 3.6 M$ with an payback period of 6 y. Economics of the coal fired CHP system was very attractive compared to the stover fired CHP system due to lower fuel cost. But the greenhouse gas emissions per Mg of fuel for the coal fired CHP system was 32 times higher than that of stover fired CHP system. Corn stover fired heat and power generation system for a corn ethanol plant can improve the net energy balance and add environmental benefits to the corn to ethanol biorefinery.     

Stochastic heat storage problem—solved by the progressive hedging algorithm

In the present study, a problem concerning operation of a heat storage tank in connection with a combined heat and power (CHP) plant is considered. The heat storage is used to supply the district heating system when the CHP plant is producing electric power alone and also to redistribute optimally over time the required heat production. Stochasticity is assumed attached to the future power production, and it is assumed that accurate predictions of the future heat consumption are available. A receding horizon idea is used. The problem is solved by the Progressive Hedging Algorithm (PHA), a recently developed method to deal with multi-period optimization problems under uncertainty. The application of the method is explained in detail.     

Risk-constrained scheduling of a CHP-based microgrid including hydrogen energy storage using robust optimization approach

Recently, the integration of various energy resources, including renewable generation and combined heat and power (CHP) units in microgrids, has created the opportunity of off-grid operation with a suitable range of reliability. This paper presents an optimization model to schedule an islanded MG with various resources, including CHP, photovoltaic (PV), and boiler, as the primary energy provision sources besides electric battery storage, thermal storage and hydrogen energy system (HES). The HES has the power-to-hydrogen (P2H) and hydrogen-to-power (H2P) modes, which increases the flexibility of the scheduling. The uncertainty management is the most essential task in the CHP-based MGs scheduling problem, since the power and heat productions are interrelated and can result in economic losses without enough deliberations. Hence, this paper proposes the robust optimization approach (ROA) to cope with the uncertainties associated with the PV production and electric and heat load demands. The robust counterparts are applied to the deterministic problem to create a tractable adjustable robust framework. The problem is structured as a mixed-integer linear programming (MILP) handled by the General Algebraic Modeling System (GAMS) using CPLEX solver. The results verified the effectiveness of the proposed robust counterparts in managing the associated risk. The results illustrated a conscious scheduling strategy under robust conditions. However, the more preserved decisions are taken, the higher operational cost is realized. In this regard, the increment of robustness level from the lowest value (deterministic condition) to the highest value (conservatism condition) increased the operation cost by about 43.29%.     

An effective heuristic for combined heat-and-power production planning with power ramp constraints

Combined heat-and-power (CHP) production is an increasingly important technology for its efficient utilization of primary-energy resources and for reducing CO₂ emissions. In the CHP plant, the generation of heat-and-power follows a joint characteristic, which makes the determination of both the marginal power production cost (MPPC) and the feasible operating region for the plant more complicated than for the power-only generation plant. Due to the interdependence between heat and power production, the power-ramp constraints, which limit how much the power production of a CHP plant may increase or decrease between two successive periods, may also imply constraints on the heat production. In this paper, we investigate the impact of power-ramp constraints on CHP production planning and develop a robust heuristic for dealing with the power-ramp constraints based on the solution to the problem with relaxed ramp-constraints (RRC). Numerical results based on realistic production models show that the heuristic can generate high-quality solutions efficiently.     

基于改进布谷鸟算法含光伏电站的无功优化

针对光伏电站并网运行给配电网无功优化带来的问题,根据光伏发电的运行特性,构建了含光伏电站的配电网无功优化数学模型,并提出改进的布谷鸟算法求解无功优化模型的方法,对含光伏出力的IEEE 33节点配电系统进行无功优化。结果表明,所提出的改进算法能有效降低配电网的有功网损,各节点远离电压崩溃点。     

Design of a cost-effective on-grid hybrid wind–hydrogen based CHP system using a modified heuristic approach

An economic model and optimization procedure is developed in this paper for grid-connected hybrid wind–hydrogen combined heat and power systems for residential applications in northeastern Iran. The model considers various significant factors: energy production cost, electrical trade with local grid, electrical power generation from the wind/hydrogen energy system, thermal recovery from the fuel cell, and maintenance. Also, various tariffs for purchasing and selling electrical energy from the local grid are considered for the hybrid system operation. The optimization objective is to minimize the system total cost subject to relevant constraints for residential applications. To achieve this aim, an efficient optimization method is proposed based on particle swarm optimization. The proposed algorithm performance is compared with that for the imperialist competition algorithm. The results show that the hybrid system is the most cost-effective for the residential load, and the results of the proposed algorithm are more promising than those for the alternative algorithm.     

基于负荷侧响应的含储热热电联产的风电消纳模型

为了有效减少弃风,提高风电消纳能力,该文从负荷侧出发,通过峰谷分时电价策略引导用户的用电方式,达到削峰填谷,优化负荷曲线的目的。同时,在传统热电联产机组中应用大容量储热装置,通过对储热环节的控制,解耦“以热定电”约束,提高系统调节能力。以系统煤耗量最低为目标,构建包含储热的热电联产机组与风电联合出力优化调度模型。该模型考虑系统中的含储热热电联产机组运行成本,同时兼顾储热、负荷侧响应与热电平衡的相关约束等因素,采用基于模拟退火的粒子群算法对模型进行求解,并利用算例比较不同模式下的结果,验证了模型的有效性。     

Optimal economic-emission performance of fuel cell/CHP/storage based microgrid

In this paper, optimal heat and power dispatch of the fuel cell (FC) and combined heat and power (CHP) based microgrid (MG) in grid-connected mode is studied in the presence of demand response program (DRP). Considering cost and emission minimization has turned this study to a multi-objective problem. Multiple generating and storing units such as FC, CHP, power-only unit, boiler, battery storage system, and heat buffer tank are considered in investigated MG. Also, demand response program has been modeled, and the effects of such programs on the load profile have been discussed. The DRP transfers some amount of load from peak periods to other periods which flats the load curve and minimizes total cost and emission of the MG. To solve the multi-objective optimization problem, the Pareto solutions are generated by using the compromising programming, then, optimal solution is chosen by implementing the fuzzy satisfying approach. In comparison with other methods, the proposed method has reduced the set of efficient solutions to a more reasonable size without demanding any information about the decision making parameters. Finally, the problem is solved in two cases as with and without DRP to clarify the impact of DRP on MG scheduling.     

考虑供热系统热储能特性的电-热综合系统随机优化调度模型研究

热电联产机组、热泵等装置的应用促进了电-热综合系统间的耦合关系,为风电的消纳提供了新途径。文章考虑了供热系统热储能动态特性,采用多场景法模拟风电出力不确定性,搭建了电-热综合能源系统随机优化调度模型。首先,针对供热管道传输时延动态特性,研究分析了其储热能力;其次,以电-热综合能源系统购能费用最低为目标函数,以热网约束、电网约束为约束条件,提出了综合系统能量最优化调度方案;最后,在IEEE33节点和6节点热网上进行算例分析,验证了模型的有效性。     

Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm

The current subsidized energy prices in Iran are proposed to be gradually eliminated over the next few years. The objective of this study is to examine the effects of current and future energy price policies on optimal configuration of combined heat and power (CHP) and combined cooling, heating, and power (CCHP) systems in Iran, under the conditions of selling and not-selling electricity to utility. The particle swarm optimization algorithm is used for minimizing the cost function for owning and operating various CHP and CCHP systems in an industrial dairy unit. The results show that with the estimated future unsubsidized utility prices, CHP and CCHP systems operating with reciprocating engine prime mover have total costs of 5.6 and $2.9×10⁶ over useful life of 20 years, respectively, while both systems have the same capital recovery periods of 1.3 years. However, for the same prime mover and with current subsidized prices, CHP and CCHP systems require 4.9 and 5.2 years for capital recovery, respectively. It is concluded that the current energy price policies hinder the promotion of installing CHP and CCHP systems and, the policy of selling electricity to utility as well as eliminating subsidies are prerequisites to successful widespread utilization of such systems.     

Multi-objective optimization of wind-hydrogen integrated energy system with aging factor

Large-scale hydrogen production with wind power generation has been gaining increasing attention and applications. Achieving a good balance between the capacity and cost of wind power generation however remains as a critical challenge restricting the development of wind-hydrogen integrated energy systems (WHIES). In addition, the aging factor may come in over time, making negative impacts on the efficiency and cost of WHIES. In this work, a method is proposed to seek a good balance between the capacity and cost of WHIES. Specifically, by comparing operational data and equipment condition, we evaluate the aging status of the wind power generation system and the hydrogen production system, then the aging economic model of WHIES is proposed. By taking into account the actual operating conditions in constructing the WHIES objective function with the aging factor, the proposed model allows striving to maximize the production capacity with the minimum cost. An improved multi-objective gray wolf optimizer algorithm is developed to solve the WHIES cost optimization problem. Finally, case studies are carried out via MATLAB based on the configuration and experimental data for a specific wind farm located in Ningxia, China. Our results help achieve a balance between maximizing capacity and minimizing cost under various conditions.     

基于氢气储能的热电联供微电网容量优化配置

以光伏系统、氢燃料电池、电解槽、储氢罐构建的热电联供微电网为研究对象,制定初始投资成本等年值以及年运行成本最小的优化目标,提出热电联供微电网热负荷满足率评价指标,针对系统运行的基本约束设计微电网控制综合策略,并以某地历史源荷数据为参考,建立满足工程应用的数学模型,采用粒子群优化算法进行求解,得到氢气储能的孤岛型微电网热电需求基本方案。从应用层面论证氢气储能替代电池储能的可行性,并进行微电网系统容量优化配置,可满足居民负荷供能需求,提高系统运行经济性,预期具有较好的应用前景。     

Evaluation of combined heat and power (CHP) systems performance with dual power generation units for different building configurations

This paper evaluates the economic, energetic, and environmental feasibility of using two power generation units (PGUs) to operate a combined heat and power (CHP) system. Several benchmark buildings developed by the Department of Energy simulated using the weather data for Chicago, IL, are used to analyze the proposed configuration. This location has been selected because it usually provides favorable CHP system conditions in terms of cost and emission reduction. For the proposed configuration, one PGU is operated at base load to satisfy part of the electricity building requirements, whereas the other is used to satisfy the remaining electricity requirement operating following the electric load. The dual‐PGU CHP configuration (D‐CHP) is modeled for four different scenarios to determine the optimum operating range for the selected benchmark buildings. The dual‐PGU scenario is compared with the reference building using conventional technology to determine the benefits of this proposed system in terms of operational cost, primary energy reduction, and carbon dioxide emissions. The D‐CHP system results are also compared with a CHP system operating following the electric load (FEL) and base‐loaded CHP system. For three of the selected buildings, the proposed D‐CHP system provides comparable or greater savings in operating cost, primary energy consumption, and carbon dioxide emissions than the optimized conditions for base loading and FEL. In addition, the effect of operating the D‐CHP system only during certain months of the year on the overall operational cost is also evaluated. Results indicate that not operating the D‐CHP system for the months where the thermal load is too low is beneficial for the overall system performance. Copyright © 2012 John Wiley & Sons, Ltd.     

考虑热网特性的电热联合系统辅助服务调度

针对传统的热电系统调度中,热电机组的“热电耦合”限制其调峰范围,导致弃风高发问题,分析了热电机组可参与辅助服务的调节容量,在目标函数中计及辅助服务调峰激励机制,构建考虑热网特性的热电调度模型,进而通过算例仿真,对比热网蓄热特性、传热特性和热力系统参数对于系统调节容量及风电消纳的影响,确定了不同热网特性下热电机组调峰成本变化,验证了所提模型可提高机组调峰和风电消纳的经济效益。     

Exergetic comparison of efficiency indicators for combined heat and power (CHP)

Legislative regulations in favor of combined heat and power (CHP) production have been implemented in many countries. Although these regulations put different emphasis on power production vs. process heat production, they are based on energy quantities and not on exergy. In order to analyze and compare the exergetic consequences of the various legislations, a relative avoided irreversibility (RAI) is defined. This can be regarded as the exergy loss that is avoided when reference plants with separate production are replaced by an actual CHP plant. Some series of industrial and district heating CHP plants, under varying operational conditions, are used as test cases. It is seen that some, but not all, CHP cases are exergetically beneficial to separate generation. Comparison with the RAI allows a quantitative assessment of the various performance indicators. It is seen that exergetic improvements were only captured to a limited degree by the various energy-based efficiency indicators. Some legislatively defined indicators even appear to discourage thermodynamic improvements.     

600 MW双机热电联供系统智能优化方法研究

以600 MW双机热电联供系统为研究对象,引入基于灰狼捕食行为模拟的群智能优化算法,针对其繁琐更新机制导致热电负荷分配时效性差的问题,进一步提出改进的灰狼优化算法(GGWO),利用前3等级狼的位置和高斯采样进行种群进化机制更新。通过EBSILON平台开展仿真试验,揭示600 MW双机热电联供系统的热电耦合特性和系统运行特性,并将改进的灰狼优化算法应用于该系统的热电负荷优化分配。结果表明：两台机组电负荷一定时,尽可能增大抽凝机组的抽汽供热量可减小系统总热耗量;通过智能热电负荷运行优化,可有效降低系统总热耗量,提高系统经济效益。     

Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method

In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO–DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO–DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm.     

Techno-economic evaluation of medium scale power to hydrogen to combined heat and power generation systems

The European Hydrogen Strategy and the new « Fit for 55 » package indicate the urgent need for the alignment of policy with the European Green Deal and European Union (EU) climate law for the decarbonization of the energy system and the use of hydrogen towards 2030 and 2050. The increasing carbon prices in EU Emission Trading System (ETS) as well as the lack of dispatchable thermal power generation as part of the Coal exit are expected to enhance the role of Combined Heat and Power (CHP) in the future energy system. In the present work, the use of renewable hydrogen for the decarbonization of CHP plants is investigated for various fossil fuel substitution ratios and the impact of the overall efficiency, the reduction of direct emissions and the carbon footprint of heat and power generation are reported. The analysis provides insights on efficient and decarbonized cogeneration linking the power with the heat sector via renewable hydrogen production and use. The levelized cost of hydrogen production as well as the levelized cost of electricity in the power to hydrogen to combined heat and power system are analyzed for various natural gas substitution scenarios as well as current and future projections of EU ETS carbon prices.