Combined Heat And Power Units Research Articles

Optimal energy management in a microgrid with known power from grid based on particle swarm optimization embedded Fuzzy multi-objective approach

The optimal energy management among distributed energy resources (DERs) in a microgrid is pivotal for its satisfactory operation. This paper presents the optimal dispatch of combined heat and power (CHP) units and a heat boiler is conducted in zero bus concept based microgrid (ZBMG) and in grid connected microgrid (GMG). In ZBMG, the utility exchanges a prescheduled amount of power to the microgrid. In this work, the optimal dispatch of various CHP units and boiler in all cases under GMG and ZBMG systems with power and heat demand is examined. The generation cost, emission, and energy loss objectives are fuzzified and solved using particle swarm optimization (PSO) algorithm. The results show that minimum objectives are attained in ZBMG compared to GMG system. The analysis is carried out on a 33-bus and 69-bus distribution systems with a 24-hour electrical and heat load profile pattern.

Enabling flexible CHP operation for grid support by exploiting the DHN thermal inertia

As a result of the increased penetration of intermittent renewable energy sources, Combined Heat and Power (CHP) units are being looked upon as one of the sources that might provide for the ever growing need for electrical flexibility. However, CHP units are often considered as must-run units on the grid for their main purpose is generally to cover the heat demand of an adjoining District Heating Network (DHN). This paper demonstrates how a CHP–DHN system may be used as a frequency reserve without excessively compromising the lifetime of the CHP, using either a specific storage tank or the DHN’s thermal inertia in order to compensate for the resulting heat imbalance. In the latter case, it is shown that a buffer tank, although smaller than a specific Thermal Energy Storage (TES), is required due to restrictions for acceptable DHN temperature gradients. In both approaches, the size of the tank has been mapped out considering frequency reserve’s duration and capacity. The results show that a simplistic static model of the DHN is sufficient for the design of a specific TES, while a detailed dynamic simulation is required when the DHN is used as storage, to prevent overestimating the flexibility of the CHP–DHN system. This research could be used to assess the potential for improving CHP–DHN systems flexibility, using them as frequency reserves, and to design the required storage or buffer tanks.

Heat current method-based real-time coordination of power and heat generation of multi-CHP units with flexibility retrofits

Real-time coordination and optimization of multiple combined heat and power (CHP) units under off-design conditions benefits overall efficiency improvement, whereas the coupling of power and heat generations among multi-units makes the system more complex. The existing software cannot tackle model accuracy and prompt optimization simultaneously. Herein, a heat current method-based real-time coordination method of power and heat generation is proposed. An optimization platform consisting of four software modules and corresponding hardware is developed to search for the optimal operating state of multi-units in a CHP plant with flexibility retrofits. After system modeling based on the heat current method, the data acquisition and curation module reads data from the distributed control system (DCS) server and then the parameter identification module provides the characteristic parameters of each component for optimization. The hierarchical and categorized algorithm is applied to solve the heat current-based model of the integrated cogeneration system, and the genetic algorithm is used for optimization. The information output module displays the optimized results on the DCS client interface. The platform is deployed in a practical plant with two connected CHP units. Field test results show that the reduction of standard coal consumption of the whole plant reaches up to 3.10 g/kWh.

Improved Ramping and Reserve Modeling of Combined Heat and Power in Integrated Energy Systems for Better Renewable Integration

With the largest installed capacity of wind power and solar PV in the world, China is experiencing an approximately 10% curtailment in major northern provinces. The combined heat and power (CHP) units account for over 50% of the local thermal generation capacity, hardly making contributions to ancillary services due to complex coupling of heat and power constraints, and thus are the major barriers for renewable energy integration. This paper explores opportunities for increasing the flexibility of CHP units by improving modeling of ramping and reserve constraints. Reformulated ramping constraints are proposed via analyzing the internal mechanical structure and introducing the regulation of heat exchange rate controlled by heating butterfly valve. A reformulated available reserve capacity model is put forward based on heating compensation mechanism between CHP units and heat storages. The reformulated models are examined in a 6-bus test system and the results show that the reformulated ramping constraint model improves notably the ramping capability of CHP units, especially operating in parallel with heat storages, facilitating the renewable integration during morning hours; whereas the reformulated reserve constraints release the hidden capability of heat storages to supply power reserves, enabling the system integration of additional renewable energy.

Combined heat and power plants integrated with steam turbine renovations: Optimal dispatch for maximizing the consumption of renewable energy

Steam turbine renovations, including the high back-pressure (HBP) renovation and the low pressure turbine zero power output (LZPO) renovation, can enlarge the loads supply range of one single combined heat and power (CHP) unit. Focusing on renewable energy consumption and coal saving, the problem regarding the optimal dispatch of a case CHP plant with renovated CHP units is addressed in this study. The energy and exergy analysis models are developed to evaluate the performance of various types of CHP units. The models of the minimum power load and the coal consumption for the whole plant are established based on the unit combinations in case 1 to case 4. The adaptive mutation particle swarm optimization (AMPSO) algorithm is adopted to seek the optimal value and the corresponding loads distributions. Results show that the maximum energy efficiency of the HBP renovated unit and LZPO renovated unit are 87.1% and 88.2%. Moreover, the maximum exergy efficiency of the HBP renovated unit and LZPO renovated unit are 41.3% and 32.1%. In brief, the HBP renovated unit has higher exergy efficiency and lower energy efficiency than LPZO renovated unit. In terms of optimization methods, AMPSO has better performance than PSO in terms of convergence speed and getting rid of local optimum solutions. After reasonably redistributing the loads of the case plant integrating the HBP and LZPO renovations, approximately 0.191 billion kWh more renewable energy would be consumed, and about 0.069 million tons of coal and 0.181 million tons of CO2 emissions could be saved during the heating season. Optimization results show that the LZPO renovations are more effective in consuming renewable energy, and the HBP renovations can be considered as the preferable coal-saving option. This study provides a method for optimizing the operation of renovated CHP plants. In addition, for the un-renovated CHP plant such as case 1, the renovation patterns in case 2 to case 4 provide some reference once the steam turbine renovations to be considered.

Heat-power decoupling and energy saving of the CHP unit with heat pump based waste heat recovery system

Combined heat and power (CHP) plants are operating under more fluctuating working conditions due to the increasingly inconsistent demands for heat and power and integration of renewable energy. This paper proposes to use an electric heat pump (EHP) to decouple heat and power and save energy by recovering waste heat from the cooling water. The thermodynamic model of the CHP unit under dynamic working conditions is established, and the dynamic EHP model based on an efficiency factor is proposed. The heat-power decoupling and energy-saving potential with different heat and power outputs and the heat pump DH ratio (χHP) are analyzed for a CHP unit as a case study. Absorption heat pump (AHP) and EHP-based waste heat recovery systems are also compared. The results indicate that the heat-power decoupling potential is bigger when χHP and the heat demand are increasing. The energy-saving effect is clearer by increasing the coefficient of performance (COP), χHP, or both. AHP and EHP can help the system obtain a certain level of heat-power decoupling and energy-saving effects, but these effects of the AHP-based system are smaller than that of EHP, especially under the working conditions of high heat demand and low power demand.

Stochastic optimal scheduling considering reserve characteristics of retrofitted combined heat and power plants

Increasing the proportion of non-fossil energy and developing renewable energy are greatly conducive to building a clean and low-carbon energy system. However, in the current power system, the strong thermo-electric coupling limits the feasible operating regions of combined heat and power (CHP) units, which causes serious problems about wind curtailment and reserve capacity insufficiency. To cope with this issue, it is technically feasible to retrofit inside and outside CHP units, so as to improve the operation and reserve flexibility of the system. This paper focuses on illustrating the flexible operation and hourly-level reserve characteristics of retrofitted CHP units in a power and heat integrated energy system (PHIES) with high proportion of wind power. The designed flexibility retrofit scheme based on internal thermal storage (ITS) and external thermal storage (ETS) is firstly analyzed. Secondly, the corresponding refined operation model for retrofitted CHP units is proposed to describe their technical features and energy flow process. Then, a coordinated optimization model for operation scheduling and reserve risk is presented from the perspective of the overall system. Finally, numerical simulations are performed to demonstrate the favorable influence of double thermal storage on wind accommodation improvement and reserve risk reduction in the PHIES. The impact of different wind power installed capacity and different thermal energy storage capacity is also studied in the sensitivity analysis.

Numerical Simulation of an on-Grid Natural Gas PEMFC - Solar Photovoltaic Micro CHP Unit: Analysis of the Energy, Economic and Environmental Impacts for Residential and Industrial Applications

As global natural resources depletion and concern on emission of greenhouse gases intensify, the interest for low emission technologies and the use of renewable energy increased in the world. In this context, this paper aims to present an hybrid energy system for on-grid micro residential and industrial applications. The system is composed of a micro combined heat and power (CHP) unit, including a natural gas (NG) reformer coupled with proton-exchange membrane fuel cell (PEMFC), solar photovoltaic modules (PV) and a bank of batteries (B), connected to the grid through a bidirectional inverter. Different system configurations (PEMFC + PV + B, PEMFC + B, PEMFC + PV), with or without cogeneration of the heat from the CHP system, were investigated to calculate the required NG and electricity flows and assess the economic cost during 10 years of operation in an 2020–2040 horizon. The impact of fuel cell sizing and two electricity tariffs was also assessed for both applications. Afterwards, the cash flow in terms of net present value of a 20 years operation period was simulated within the Brazilian context, yielding estimated paybacks between 7 and 19 years for the simulated cases. Finally, an environmental impact analysis was carried out to investigate the total GHG emissions for some cases of interest in this work. The proposed system could reduce total emissions up to 31% when compared to the complete power and thermal supply by the Brazilian Electricity grid and natural gas heater The results showed that the proposed system were economically viable, relatively low-polluting and more efficient than traditional PV systems.

Study on Dynamic Process Characteristics of CHP Unit With Variable Load Based on Working Point Linearization Modeling

In view of the difficulty of applying the refine modeling of combined heat and power (CHP) units to the optimization scenario of integrated energy system, a CHP unit model based on working point linearization modeling is proposed, and its variable load characteristics are analyzed. Firstly, the dynamic coupling relationship of CHP unit is analyzed, and the nonlinear dynamic model of the unit is constructed. Then, under the pure condensation and heating conditions, the linearized Laplace transform model of the working point is established, and the variable load capacity under the independent action of control variables is analyzed to test the availability of the Laplace model. On this basis, the dynamic adaptive particle swarm optimization algorithm is used for multivariable cooperative control to test the open-loop characteristics of the variable load capacity of the unit. At the same time, the control strategy of electrothermal cooperation and safety self-test is designed to adjust the control variables, and test the closed-loop characteristics of the unit’s regulation ability. Finally, a 300-MW steam extraction CHP unit is taken as an example to verify the applicability of the unit model and the effectiveness of the control strategy.

Research on the scheduling of unit operation mode for combined heat and power plants considering new energy consumption in heating season

China aims to peak carbon dioxide emissions before 2030 and achieve carbon neutrality before 2060. The traditional coal power plants need to reduce theirs power load as much as possible to reduce CO2 emissions and improve the consumption capacity of intermittent renewable energy. Nevertheless, in part of northern China, areas with a high proportion of combined heat and power (CHP) units in coal power, CHP units need to provide heat load during heating season so that the flexibility of power load adjustment for CHP units is restricted. The plant minimum operation mode model is proposed to excavate the plant-level lower boundary of power load. By analysing the heat-power coupling mechanism of each unit, under different unit commitments, the plant-level lower boundary of power load can be calculated through dispatch heat load reasonably. Then the scheduling scheme of optimal unit commitment for plant is obtained. The comparison of results with the actual operation of a case CHP plant shows that the consumption capacity of renewable energy can be increased by 1.92 billion kWh and the CO2 emissions of the reference plant could be reduced by 52.5% under the scheduling scheme of optimal unit commitment during the heating season. The reduction of CO2 emissions for the scheduling scheme of optimal unit commitment will remain more carbon allowance which can bring revenue from carbon trade market. The scheduling of unit operation mode provides a way of operation under the current policy and environmental background, how to depress the power load of CHP plants and reduce CO2 emissions in heating season.

Optimal dispatch of a thermal-electric virtual power plant considering heat storage tanks

Characteristic of thermoelectric coupling of Combined heat and power (CHP) units reduces the flexibility of power generation and heat generation in the “Three-North” region of China. Meanwhile, the uncertainty of renewable energy generation (REG) and demand side management (DSM) pose challenges to the optimal operation of the whole system, leading to difficulty in improving the economic benefits of the whole system. In order to mitigate the above problems, wind generators, solar generators, CHP units, conventional generating units, interruptible loads, battery energy storage systems (BESSs), as well as electric vehicles (EVs) are aggregated into a virtual power plant (VPP) as a community of interest. Particularly, heat storage tanks (HSTs) are introduced into VPP in this paper to realize the decoupling of heat and power of CHP units and enhance the flexibility of the VPP. Firstly, the composition and structure of the VPP are described. Secondly, a day-ahead optimal dispatching model of the VPP considering heat output is established. Finally, the effectiveness of the proposed model is verified by the modified IEEE30 bus system.

Electricity-heat integrated agent modelling for participation in spot electricity market

Due to the limitation of market rules, many small capacity power plants cannot directly participate in the spot electricity market, reducing the ability of the market to optimize the allocation of power generation resources. Among these power plants, the electric power output of some combined heat and power (CHP) plants is constrained by their heat output, which should be considered in the dispatch. Therefore, the electricity-heat integrated agents are defined and introduced to aggregate small capacity power plants and participate in the spot electricity market. Firstly, the model of electricity-heat integrated agents is formulated based on the aggregation of the internal generators and CHP units. Then, the framework of the spot electricity market with the participation of electricity-heat integrated agents is constructed. Moreover, the market clearing model is further developed by combining the electricity-heat integrated agent model and the security constrained unit commitment model. Simulation results in the case verify the effectiveness of the proposed model and technique.

Participation of Aggregated DERs to the Ancillary Services Market: A Monte Carlo Simulation-Based Heuristic Greedy-Indexing Model

In an effort to improve the stability and secure operation of the grid, regulatory bodies are opening Ancillary Services Markets participation to Distributed Energy Resources (DERs), energy storage systems, and demand response. Within this framework, this study proposes a model that simulates the coordinated operation of an aggregate of power plants, including non-dispatchable DERs and, as regulating units, Combined Heat and Power (CHP) generation and electrochemical energy storage systems. A Monte Carlo procedure is adopted to realistically create a population of aggregation scenarios. The real-time operation of the DER portfolio is managed through a Heuristic Greedy-Indexing logic, which allows the Aggregator to select the optimal control action to implement according to the technical and economic quantities characterizing the market and the grid. The techno-economic performance of the proposed algorithm is evaluated by simulating its interaction with the electricity markets. Finally, a sensitivity analysis is performed to analyze the profitability in different scenarios. The novel mathematical model proposed showed to be effective in managing a complex problem like the one at hand with an acceptable computational effort. The numerical results obtained confirmed that the aggregated participation in the market could provide interesting economic returns, especially if a CHP unit is involved as regulating unit, while the feasibility of the batteries adoption is still limited by the actual cost of the technology.

Data-Driven Optimal Design of a CHP Plant for a Hospital Building: Highlights on the Role of Biogas and Energy Storages on the Performance

Combined heat and power (CHP) generation plants are an assessed valuable solution to significantly reduce primary energy consumption and carbon dioxide emissions. Nevertheless, the primary energy saving (PES) and CO2 reduction potentials of this solution are strictly related to the accurate definition and management of thermal and electric loads. Data-driven analysis could represent a significant contribution for optimizing the CHP plant design and operation and then to fully deploy this potential. In this paper, the use of a bi-level optimization approach for the design of a CHP is applied to a real application (a large Italian hospital in Rome). Based on historical data of the hospital thermal and electric demand, clustering analysis is applied to identify a limited number of load patterns representative of the annual load. These selected patterns are then used as input data in the design procedure. A Mixed Integer Linear Programming coupled with a Genetic Algorithm is implemented to optimize the energy dispatch and size of the CHP plant, respectively, with the aim of maximizing the PES while minimizing total costs and carbon emissions. Finally, the effects of integrating biogas from the Anaerobic Digestion (AD) of the Spent Coffee Ground (SCG) and Energy Storage (ES) technologies are investigated. The results achieved provide a benchmark for the application of these technologies in this specific field, highlighting performances and benefits with respect to traditional approaches. The effective design of the CHP unit allows for achieving CO2 reduction in the order of 10%, ensuring economic savings (up to 40%), when compared with a baseline configuration where no CHP is installed. Further environmental benefits can be achieved by means of the integration of AD and ES pushing the CO2 savings up to 20%, still keeping the economical convenience of the capital investment.

Analysis of economy, energy efficiency, environment: A case study of the CHP system with both civil and industrial heat users

Integrated energy supply via the high-capacity combined heat and power (CHP) system is an effective way to achieve “win-win cooperation” for regional carbon reduction. A case study of the CHP system with both civil and industrial heat users is conducted to analysis the mixed impact of integrated energy supply on CHP systems. The steam-water equations and the off-design calculation model are developed to analyze the heat-power coupling mechanism of the CHP system. The linear-calculating diagram is obtained, which provides operational guidance for CHP system with simultaneous power, civil heat and industrial loads. Further, the analysis of economy, energy efficiency and environment within the operation region is performed. The results show that for a constant main steam flow rate, the industrial heat load is more profitable than the civil heat load. Moreover, the energy efficiency of the CHP unit can be further improved by undertaking the industrial heat load, despite at the expense of part capacity to supply civil heat. The average value of CO2 emissions per unit profit is reduced by approximately 7.69% overall after the stable industrial heat load of 100 MW, which means about 1.64 tons of CO2 can be reduced per 1000 USD profit.

Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains. A demand management model for industrial park considering the integrated demand response of combined heat and power (CHP) units and thermal storage is firstly proposed. Specifically, by increasing the electricity outputs of CHP units during peak-load periods, not only the peak demand charge but also the energy charge can be reduced. The thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP units. The heat dissipation of thermal storage, thermal delay effect, and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial park. The proposed model is formulated as a multi-period alternating current (AC) optimal power flow problem via the second-order conic programming formulation. The alternating direction method of multipliers (ADMM) algorithm is used to compute the proposed demand management model in a distributed manner, which can protect private data of all participants while achieving solutions with high quality. Numerical case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge, and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.

Flexibility Improvement of CHP Unit for Wind Power Accommodation

Improving the flexibility of combined heat and power (CHP) units is an important way to solve the problem of wind power accommodation in northern China. Firstly, this paper analyzes the principle of an extraction-type CHP unit, calculates its safe operation range, and analyzes its contradiction between heating and peaking. Secondly, the safe operation ranges of the CHP unit with several flexibility modifications are further calculated, which involve two-stage bypass, low-pressure cylinder (LPC) removal, heat storage tank, and electric boiler. Finally, based on the safe operation ranges, their effects on improving the capabilities of deep peak shaving and wind power accommodation are compared, and their adaptabilities to different wind scenarios are analyzed. The results show that: ① all flexibility modifications can improve the deep peak shaving capability of the CHP unit, especially for the two-stage bypass and the electric boiler; ② LPC removal modification can accommodate wind power to some extent, but most of wind power is still abandoned; ③ heat storage tank modification is unstable in different wind scenarios, which is determined by the surplus heating capability during the daytime.

Solution of Combined Heat and Power Economic Dispatch Problem Using Direct Optimization Algorithm

This paper presents the solution to the combined heat and power economic dispatch problem using a direct solution algorithm for constrained optimization problems. With the potential of Combined Heat and Power (CHP) production to increase the efficiency of power and heat generation simultaneously having been researched and established, the increasing penetration of CHP systems, and determination of economic dispatch of power and heat assumes higher relevance. The Combined Heat and Power Economic Dispatch (CHPED) problem is a demanding optimization problem as both constraints and objective functions can be non-linear and non-convex. This paper presents an explicit formula developed for computing the system-wide incremental costs corresponding with optimal dispatch. The circumvention of the use of iterative search schemes for this crucial step is the innovation inherent in the proposed dispatch procedure. The feasible operating region of the CHP unit three is taken into account in the proposed CHPED problem model, whereas the optimal dispatch of power/heat outputs of CHP unit is determined using the direct Lagrange multiplier solution algorithm. The proposed algorithm is applied to a test system with four units and results are provided.

Scheduling coordination of back pressure CHP coupled electricity-heat energy system with adaptive constraint strategy to accommodate uncertain wind power

A scheduling coordination approach with adaptive constraint strategy is proposed for electricity-heat integrated energy system (IES). The approach takes full advantage of heat network flexibility to smooth uncertain wind power and its natural storage capability to improve operational economics. Transmission dynamics of heating network is modeled by describing the heat dissipation in radial direction toward the insulation layer and the heat propagation in axial direction through water flow. Dynamical heating flow and steady power flow with different timescales are integrated to constitute the coordinated scheduling optimization by energy coupling component, i.e. CHP (combined heat and power) unit. In order to mitigate the discrepancy between the predicted and real values of wind power by utilizing the allowed upper limit of water temperature constraint violation, a PID idea based closed-loop adaptive adjustment strategy is implemented on the water temperature constraint at the beginning of supply pipeline. Simulations are conducted to show that in the proposed coordinated scheduling approach, heat network can serve as a natural energy storage to achieve the economic operation of IES, and simultaneously wind power uncertainties can be smoothed by the flexible temperature constraint of water flowing in heat network, with no any probability distribution information of uncertainties needed.

Energy, Environmental, and Economic Analyses of a District Heating (DH) Network from Both Thermal Plant and End-Users’ Prospective: An Italian Case Study

District heating (DH) is an alternative technology to Individual Heating (IH) for satisfying end-user’s needs. This paper assesses the competitiveness of a DH network in the center of Italy from energy, environmental, and economic points of view considering both thermal power plant and end-users’ sides. On the thermal power plant side, the energy analysis considers the Primary Energy Saving (PES) and the specific energy (Esp) of the fuel actually exploited in the thermal power plant compared to its Low Heating Value (LHV), while the environmental analysis considers the avoided CO2 and the economic analysis considers the Energy Efficiency Certificates (EECs). Results showed that the current thermal power plant configuration with two boilers and a Combined Heat and Power (CHP) unit reaches a yearly PES of 21.3% as well as 1099 tCO2 avoided. From the economic analysis of the thermal power plant side, 829 EECs with an economic return of 207,222€ are obtained, while from the end-users’ side the DH network is cheaper than IH in 84.7% of the cases. Further technologies are also studied to enhance the CHP unit flexibility.