Combined Heat And Power Dispatch Research Articles

A Robust Interval Optimization Method for Combined Heat and Power Dispatch

The increasing penetration of renewable energy, particularly wind power, and the integration of different energy systems have become two major trends in the development of energy systems. In this context, this paper proposes a robust interval optimization method for combined heat and power dispatch (CHPD) to address the challenges associated with wind power accommodation. To enhance the flexibility of a power system and support the integration of wind power, flexibility resources from a district heating system are introduced in the economic dispatch. To ensure the safety and reliability of the CHPD results, a robust interval optimization method is employed. By considering a range of possible wind power outputs, the robust interval optimization method provides a robust and reliable dispatch plan that can accommodate uncertainties and fluctuations in wind power generation. To verify the effectiveness of the proposed model and method, case studies were conducted on a 6-bus electrical power system connected with a 6-node district heating system. The results demonstrate that the proposed approach can effectively enhance the integration of wind power and improve the overall reliability and flexibility of the energy system.

Benefit allocation for combined heat and power dispatch considering mutual trust

Combined heat and power dispatch (CHPD) has attracted wide attention recently, which exploits the potential flexibility in the district heating system (DHS) and provides an economic-effective solution for better wind accommodation. However, DHS operators bear extra operation cost in CHPD, which is proved theoretically in this paper, so that they have insufficient incentive to coordinate with electrical power system. To cope with this issue, a cost allocation strategy based on the Aumann-Shapley value method is proposed, which can rationally allocate the benefit among multiple agents. And a new solution scheme with the Gauss-Legendre quadrature formula is developed to enhance computation efficiency. Also, considering the potential malicious behavior of dishonest agents in the process of allocation, the blockchain framework with Proof of Solution consensus mechanism is introduced to ensure mutual trust among multiple agents. Numerical simulations based on different cases demonstrate the effectiveness of the proposed method of benefit allocation among multiple agents. In addition, the validity of the proposed blockchain framework in preventing malicious behavior when CHPD is verified.

Operational Reliability Assessment of Integrated Heat and Electricity Systems Considering the Load Uncertainties

The wide deployment of combined heat and power (CHP) has intensified the interdependence between district heating network (DHN) and electric power system. Under such circumstances, the operational reliability assessment of the integrated heat and electricity system (IHES) becomes a significant issue, that has not been comprehensively studied before. In this paper, the reliability models of the coupling devices in the IHES, i.e., CHP units and heat pump (HP) units, are first developed considering two interdependent performance variables. Energy loads are represented by fuzzy multi-state models to capture the uncertainties due to the forecast, model, and data errors. The scenario-based combined heat and power dispatch (CHPD) model is proposed to calculate the nodal reliability indices. Several techniques are utilized to improve the computation efficiency of the reliability assessment technique. First, the traditional universal generating function (UGF) method is extended to the IHES context to combine the coupling device states and consequently reduce the number of scenarios that need to be considered. Second, a hydraulic-thermal decomposition technique is proposed to decompose the CHPD model into two linear programming (LP) models that can be iteratively solved. Case study illustrates the proposed reliability assessment framework and the effectiveness of the solution technique.

Optimal generation scheduling of large-scale multi-zone combined heat and power systems

Combined heat and power (CHP) technology can simultaneously satisfy heat and power loads. The objective of optimal production scheduling of CHP plants is finding optimal schedule of heat and power plants according to the constraints of network and component. In this research, the solution of CHP economic dispatch (CHPED) in large scale is investigated considering different scenarios. Firstly, the CHPED is tested on a 48-unit system to obtain minimum total operation cost, which includes the operation cost of thermal plants, CHP units and boilers, and the obtained optimal solutions are compared with recent publications. Then, a novel framework for a large-scale multi-zone CHPED problem is introduced, where each zone is responsible of providing the associated heat load. Finally, the multi-objective CHP dispatch problem is studied for handling two competing objectives consisting of operation cost and emissions of pollutant gases. The emission of pollutant gases includes the greenhouse gases emitted by thermal plants, CHP units and boilers. The model is tested on a three-zone 48-unit system for verifying the performance and effectiveness of the model. An annual cost saving of $1,939,534.08 can be attained by using the applied method for the 48-unit CHP system in comparison with the reported results in recent studies.

Exploiting Flexibility of District Heating Networks in Combined Heat and Power Dispatch

Combined heat and power dispatch (CHPD) is utilized for energy-efficient coordination of integrated electricity and heat systems. By incorporating district heating networks (DHNs) into CHPD, the thermal storage capability of network pipelines can be exploited to increase the operational flexibility for high penetration of renewable energy. This article proposes a flexibility evaluation method based on a generalized thermal storage model to systematically characterize and quantify the flexibility of DHNs in CHPD. In particular, systematic flexibility metrics are introduced to define the parameters of the proposed thermal storage model, including heat ramping capability, heat input limits, and heat storage capacities. A direct quantification method is proposed to explicitly derive these metrics without extensive simulations required in traditional methods. Besides, four different control modes of district heating systems are identified and modeled according to the controllability of mass flow rates and supply temperature at heat sources. A simplified CHPD model is developed based on sequential linear programming and a lumped heat loss model to enhance the computational efficiency. Comprehensive case studies validate the effectiveness of the proposed method in evaluating the flexibility of DHNs in CHPD. It is demonstrated that the flexibility of DHNs in CHPD can be exploited as far as possible in the control mode with adjustable mass flow and supply temperature.

Combined Heat and Power dispatch considering Advanced Adiabatic Compressed Air Energy Storage for wind power accommodation

As an attractive large-scale clean energy storage technique, Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) can store and generate both electricity and heat, which has great application potentials in Integrated Electricity and Heating Systems (IEHSs). However, few studies have been reported on Combined Heat and Power (CHP) dispatch by implementing AA-CAES in IEHS. This paper presents a CHP dispatch model considering the participation of AA-CAES for IEHS and mitigating wind curtailment. The mathematical model of AA-CAES for CHP dispatch is developed based on Mixed Integer Linear Programming (MILP). The off-design characteristic of AA-CAES is considered in the modelling process. The benefits of AA-CAES for mitigating wind curtailment and decreasing operation costs in IEHS has been studied. The scheduling analysis based on the developed model and the existing model without considering off-design characteristics has been carried out. The study shows that the participation of AA-CAES in CHP dispatch can increase the flexibility of IEHS, and it can lead to an apparent reduction of wind curtailment and operation costs. Also, AA-CAES’s off-design conditions need to be considered in the dispatch; otherwise it can cause the misjudgment of AA-CAES’s state of charge, which in turn results in costly operation.

Coordinated Dispatch of Integrated Electric and District Heating Systems Using Heterogeneous Decomposition

Extensive deployment of combined heat and power (CHP) units into the electric power system (EPS) makes it imperative to investigate the utilization of flexible resources in a district heating system (DHS) and avoid unnecessary wind power curtailment. In this paper, a combined heat and power dispatch (CHPD) model is developed by considering the flexibility of heat sources, pipelines, and DHS loads. Specifically, the adjustable region of the CHP units, heat storage of the heating networks and thermal inertia of the buildings are taken into account. Moreover, the heterogeneity of the EPS and DHS requires the independent control over the two systems. We propose a novel decentralized algorithm for solving the CHPD problem based on the heterogeneous decomposition method. The algorithm only requires the locational marginal prices at boundary buses of the EPS and the injected boundary power of the DHS to be exchanged. Numerical simulations are carried out for real data in Jilin. The flexible resources are optimally utilized and the wind power curtailment is reduced in the CHPD, with the alleviation of congestion in the EPS. Besides, simulations demonstrate that the proposed algorithm is efficient and robust, with a light communication burden to solve CHPD.

Research on heat and electricity coordinated dispatch model for better integration of wind power based on electric boiler with thermal storage

The thermal-electric coupling characteristics of combined heat and power (CHP) units make it critical problem to improve wind power accommodation ability in the heating season. This study establishes a CHP dispatch model for better integration of wind power based on electric boiler with thermal storage (EBTS). A start–stop strategy of EBTS is formulated that takes only the abandoned wind as the heat source. The electric boiler runs at maximum power during the wind curtailment, and the heat output of EBTS is changed by controlling the endothermic and exothermic rates of the thermal storage. Considering the scheduling difficulty of the CHP system with EBTS, the multi-agent model of heat and electricity is built. Through information exchange and load distribution between the agents, electric load is balanced by all units while thermal load by CHP units and EBTS. Finally, the Newton–Raphson iterative method is applied to solve the proposed model. The results of numerical examples validate effectiveness and economic improvement of the proposed method.

Decentralized Solution for Combined Heat and Power Dispatch Through Benders Decomposition

The operational flexibility of electric power systems (EPS) is restricted by combined heat and power (CHP) units that act to maintain sufficient heating supply. By exploiting the pipeline heat storage property in central heating systems (CHS), combined heat and power dispatch (CHPD) can significantly increase the operational flexibility and reduce wind power curtailment. In this paper, pipeline heat storage is modeled in the CHPD model under the constant mass flow heating dispatch mode, and the CHPD model can be formulized as a quadratic programming problem. Since the EPS and CHS are independently operated by the EPS and CHS operators, a decentralized solution to the CHPD model is proposed. During each iteration of the decentralized procedure, an optimal cut or a feasible cut is generated by the CHS operator and sent to the EPS operator. A robust model considering the wind power uncertainty is also studied with the proposed decentralized solution. This decentralized solution has a high efficiency and a light communication burden. Numerical tests on practical systems demonstrate the feasibility of the proposed decentralized method and the economic benefits brought by reducing wind curtailment.

Dispatch Model of Combined Heat and Power Plant Considering Heat Transfer Process

Due to the coupling of its heat and power output, combined heat and power (CHP) has limited flexibility, which is one of the main reasons for variable renewable energy source (RES) curtailment problem in Northern China. Almost all the existing studies have modelled the CHP's output characteristics as a feasible operation region of electric power and heat power. However, only the extraction steam of a CHP unit that used for district heating can be controlled directly, without considering the extraction steam's heat transfer process, the actual heat power output cannot be precisely decided. Thus this paper proposes a detailed CHP dispatch model based on the principles of heat transfer. A three-stage heat transfer model of the extraction steam is used to describe the heating process. Then, a joint dispatch model concerning CHP units, conventional thermal power units, and RESs is given. Finally, the impacts of different factors on the extraction steam's heat transfer process and its influence for RES accommodation are analyzed. Results show that considering heat transfer process is essential in modelling the CHP plant that used for district heating, especially when the CHP plant is working at a status that deviates from the rated one significantly.

Combined Heat and Power Dispatch using Hybrid Genetic Algorithm and Biogeography-based Optimization

This paper explores the performance of biogeography-based optimization (BBO) algorithm for solving combined heat and power dispatch (CHPD) or cogeneration problem of power system. BBO is a type of evolutionary algorithm which is based on the theory of biogeography and is inspired by the two concepts, namely migration of species between “islands” via flotsam, wind, flying, swimming, etc. and mutation. To improve the convergence property and solution quality, blended crossover strategy of genetic algorithm (GA) is integrated with conventional BBO algorithm in this study. The effect of valve-point in cost function is considered by adding an absolute sinusoidal term with the conventional polynomial cost function. The potential of the proposed BBO and GA based BBO (GABBO) algorithms are assessed by means of an extensive comparative study of the solutions obtained for small and medium CHPD problems of power systems. To show the priority of the proposed algorithm, comparative studies are carried out to examine the effectiveness of the proposed BBO and GABBO approaches over evolutionary programming (EP), differential evolution (DE), particle swarm optimization (PSO) and time varying acceleration coefficients PSO (TVAC-PSO reported in the literature. The experimental results and comparison with other algorithms demonstrate that the proposed GABBO algorithm can be a proficient substitute lying on solving combined heat and power dispatch problems.

Combined heat and power economic dispatch using integrated civilized swarm optimization and Powell’s pattern search method

An integrated technique that embeds civilized swarm optimization (CSO) and Powell’s pattern search (PPS) method is proposed to search economic dispatch of combined heat and power (CHP) dispatch problem. In the proposed technique, CSO is selected as global search technique and PPS is undertaken as a local search technique. Civilized swarm optimization is having attributes of particle swarm optimization (PSO) and society civilization algorithm (SCA). In CSO, mutually interacting societies forms the civilization. The positions of society particles are updated through the guidance of own leader along with their best positions. The best performing particle of CSO is further improved by PPS method based on a certain set criterion. The PPS method is based on the conjugate search direction method and does not require the gradient or Hessian matrix of the function to be optimized. The CHP dispatch problem has a mutual dependency of demand and heat-power capacity of generating units, so it requires an effective constraint handling strategy. In this work, variable reduction strategy with exterior penalty method is applied to satisfy equality constraints. The proposed technique is tested on five CHP test systems considering valve-point loading effect, prohibited operating zones constraint, and transmission losses. The obtained results are compared to the results reported in the literature and found satisfactory. Further, for verification of statistical performance of the proposed technique, t-test and Wilcoxon signed rank test is also performed.

Combined Heat and Power Dispatch Considering Pipeline Energy Storage of District Heating Network

The regional integration of variable wind power could be restricted by a strong coupling of electric power generation dispatch and heat supply of combined heat-and-power (CHP) units. The coupling in cold seasons precludes CHPs from providing the necessary flexibility for managing the wind power dispatch. The lack of flexibility problem can be tackled by exploiting the energy storage capability of a district heating network (DHN) which decouples the strong linkage of electric power and heat supplies. In this paper, a combined heat and power dispatch (CHPD) is formulated to coordinate the operation of electric power system (EPS) and district heating system (DHS). The proposed CHPD model which is solved by an iterative method considers the temperature dynamics of DHN for exploiting energy storage as an option for managing the variability of wind energy. The simulation results are discussed for several test systems to demonstrate the potential benefits of the proposed method in terms of operation economics, wind power utilization, as well as the potential benefits for real systems.

Combined heat and power dispatch by grey wolf optimization

Purpose – The combined heat and power dispatch (CHPD) aims to optimize the outputs of online units in a power plant consisting thermal generators, co-generators and heat-only units. Identifying the operating point of a co-generator within its feasible operating region (FOR) is difficult. This paper aims to solve the CHPD problem in static and dynamic environments. Design/methodology/approach – The CHPD plant operation is formulated as an optimization problem under static and dynamic load conditions with the objectives of minimizations of cost and emissions subject to various system and operational constraints. A novel bio-inspired search technique, grey wolf optimization (GWO) algorithm is used as an optimization tool. Findings – The GWO-based algorithm has been developed to determine the preeminent power and heat dispatch of operating units within the FOR region. The proposed methodology provides fuel cost savings and lesser pollutant emissions than those in earlier reports. Particularly, the GWO always keeps the co-generator’s operating point within the FOR, whereas most of the existing methods fail. Originality/value – The GWO is applied for the first time to solve the CHPD problems. New dispatch schedules are reported for 7-unit system with the objectives of total fuel cost and emission minimizations, 24-unit system for economic operation and 11-unit system in dynamic environment. The simulation experiments reveal that GWO converges quickly, consistent and the statistical performance clears its applicability to CHPD problems.

Grey wolf optimization for combined heat and power dispatch with cogeneration systems

Abstract The Combined Heat and Power Dispatch (CHPD) is an important optimization task in power system operation for allocating generation and heat outputs to the committed units. This paper presents a Grey Wolf Optimization (GWO) algorithm for CHPD problems. The effectiveness of the proposed method is validated by carrying out extensive tests on three different CHPD problems such as static economic dispatch, environmental-economic dispatch and dynamic economic dispatch. Valve-point effects, ramp-rate limits and spinning reserve constraint along with network loss are considered. Standard test systems containing 4, 7, 11 and 24 units are used for demonstration purpose. To validate the performance of the GWO, statistical measures like best, mean, worst, standard deviation, epsilon, iter and sol-iter over 50 independent runs are taken. The simulation experiments reveal that GWO performs better in terms of solution quality and consistency.

An application of grey wolf optimisation for combined heat and power dispatch

The purpose of this paper is to obtain the best feasible solution for combined heat and power dispatch (CHPD) problems. Being inspired by the hunting and searching behaviours of grey wolves, a swarm intelligence algorithm, grey wolf optimisation (GWO) has been developed and is used as an optimisation tool for the chosen problem. In addition to the nonlinear and non-convex operational characteristics of generating units, the practical operational constraints such as feasible operating regions of cogenerators, prohibited operating zones of thermal generators are considered. The GWO is implemented in the standard test systems for economic and combined economic emission dispatch operations. The obtained results are higher, feasible than or as good as the best known solutions by state-of-the-art algorithms reported in the literature. It is evident that the GWO attains a high quality solution to CHPD problems.

Oppositional teaching learning based optimization approach for combined heat and power dispatch

This paper presents a new optimization technique i.e. teaching learning based optimization (TLBO) to solve combined heat and power dispatch (CHPD) problem with bounded feasible operating region. To accelerate the convergence speed and improve the simulation results, opposition based learning (OBL) is incorporated in basic TLBO algorithm. The potential of the proposed TLBO and oppositional TLBO (OTLBO) algorithms are assessed by means of an extensive comparative study of the solutions obtained for three different standard combined heat and power dispatch problems of power systems. The results of the proposed methods are compared with other popular optimization techniques like evolutionary programming (EP), three variants of particle swarm optimization (PSO), real coded genetic algorithm (RCGA), differential evolution (DE) and bee colony optimization (BCO). Through the simulation of MATLAB programming it is seen that OTLBO provides better results than all other optimization techniques at less computational time.

Stochastic combined heat and power dispatch based on multi-objective particle swarm optimization

Conventional economic power dispatch problem uses deterministic models, which are however not able to reflect some real situations in practical applications. Since certain inaccurate and uncertain factors are normally involved in system operations, stochastic models are more suited for investigating some of the power dispatch problems. In this paper, the stochastic model for combined heat and power (CHP) dispatch is first formulated, and then an improved particle swarm optimization (PSO) method is developed to deal with the economic CHP dispatch by simultaneously considering multiple conflicting objectives. Based on the proposed optimization method, the impact of different problem formulations including stochastic and deterministic models on power dispatch results is investigated and analyzed. Furthermore, a comparative study is carried out with respect to genetic algorithm (GA) in terms of solution quality and computational expense.

COMBINED HEAT AND POWER ECONOMIC DISPATCH USING GENETIC ALGORITHM BASED PENALTY FUNCTION METHOD

ABSTRACT This paper presents a new genetic approach for solving combined heat and power (CHP) economic dispatch problems. The complication of CHP dispatch lies in the constraints imposed by the multi-demand and heat-power capacity mutual dependencies. The paper proposes improved penalty function formulation for Genetic Algorithms (GAs) to effectively handle constraints. The method has been tested and compared to demonstrate its effectiveness