Integration and optimal control of microcsp with building hvac systems: Review and future directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost

Droop control in DQ coordinates for fixed frequency inverter-based AC microgrids

This paper presents a proof-of-concept for a novel dq droop control technique that applies DC droop control methods to fixed frequency inverter-based AC microgrids using the dq0 transformation. Microgrids are usually composed of distributed generation units (DGUs) that are electronically coupled to each other through power converters. An inherent property of inverter-based microgrids is that, unlike microgrids with spinning machines, the frequency of the parallel-connected DGUs is a global variable independent from the output power since the inverters can control the output waveform frequency with a high level of precision. Therefore, conventional droop control methods that distort the system frequency are not suitable for microgrids operating at a fixed frequency. It is shown that the proposed distributed droop control allows accurate sharing of the active and reactive power without altering the microgrid frequency. The simulation and hardware-in-the-loop (HIL) results are presented to demonstrate the efficacy of the proposed droop control. Indeed, following a load change, the dq droop controller was able to share both active and reactive power between the DGUs, whereas maintaining the microgrid frequency deviation at 0% and the bus voltage deviations below 6% of their respective nominal values

Decentralized Hamiltonian control of isolated AC microgrids: Theory & design

© 2015 IEEE. Microgrids technology is the cornerstone of smart grid, the electricity network of the future. Based on distributed generation, microgrids can contribute to increase the penetration rate of renewable energy resources and hence reduce costs and gas emissions. This paper presents a new design methodology, based on Hamiltonian Surface Shaping and Power Flow Control (HSSPFC), for a decentralized control of isolated microgrids (ImGs) with multiple distributed energy resources (DERs). The local controllers insure the stability of the overall ImG while regulating the voltage at the point of common coupling (PCC) of their respective DERs. Each controller is synthesized independently, using only local information on the corresponding DER, its dedicated load, and the corresponding line. This decentralized control procedure guarantees scalability and plug-and-play (PnP) operations of the ImG

Decentralized Hamiltonian control of multi-DEr isolated microgrids with meshed topology

© 2019 The Authors. Published by Elsevier Ltd. The new electricity grid of the future, smart grid, can be seen as the interconnection of multiple microgrids. These microgrids are usually composed of distributed energy resources (DERs) that connect to each other in different topologies. Therefore, the modeling and control of meshed microgrids are requisite. This paper presents a mathematical approach for the modeling and decentralized control of multi-DER isolated microgrids (ImGs) with a meshed topology. Based on the advanced control scheme: Hamiltonian surface shaping and power flow control (HSSPFC), decentralized controllers are designed independently using only local information. These controllers regulate the voltage at the point of common coupling (PCC) of their respective DERs and guarantee the stability of the overall ImG without requiring any communication infrastructure; hence, avoiding a single point of failure and harvesting the scalability of the ImG

Building-to-grid optimal control of integrated MicroCSP and building HVAC system for optimal demand response services

The world is shifting toward cleaner and more sustainable power generation to face the challenges of climate change. Renewable energy sources such as solar, wind, hydraulic are now the go-to technologies for the new power generation system. However, these sources are highly intermittent and introduce uncertainty to the power grid which affects its frequency and voltage and could jeopardize its stable operations. The integration of micro-scale concentrated solar power (MicroCSP) and thermal energy storage with the heating, ventilation, and air conditioning (HVAC) system gives the building greater leeway to control its loads which can allow it to support the power grid by providing demand response (DR) services. Indeed, the optimal control of the power flowing between the MicroCSP, the HVAC system, and the thermal zones can bring additional degrees of freedom to the building which can be relegated to the power grid based on the objective function and the incentives provided by the latter. This article presents an in-depth investigation of the MicroCSP potential to provide ancillary services to the power grid. It focuses on evaluating the effect of incentives provided by the power grid on the building participation to the load following programs. It also demonstrates how the MicroCSP can help the building deal with constraints related to load peak shaving and ramp-rate reduction set by the power grid as part of long-term DR contracts. A sensitivity analysis is carried out to confront the results to prediction uncertainties of the energy prices and the weather conditions

A DQ droop control strategy for fixed frequency VSI-based AC microgrids

© 2018 IEEE. The development of distributed energy resources, renewable technologies, and storage systems has given great importance to power electronics that enable coordination and parallel operations of multiple distributed generation units (DGUs) in microgrids. These DGUs are electronically-coupled to each other through power converters that can accurately control their output frequency. This paper presents a droop control technique for fixed frequency VSI-based ac microgrids that combines reference frame transformation, Lyapunov stability analysis, and a modified dc droop control strategy to share active and reactive power between the DGUs without altering the frequency and magnitude of the bus voltage in the islanded microgrid. The simulations show that the proposed distributed droop control ensures proper sharing of the active and reactive power, and regulates the bus voltage at the nominal value while operating at a fixed frequency

MPC-trained ANFIS for control of MicroCSP integrated into a building HVAC system

This paper presents the design of an easily implementable rule-based controller that can minimize the electrical energy consumption of a building heating, ventilation, and air-conditioning (HVAC) system integrated with a microscale concentrated solar power (MicroCSP) system. A model predictive control (MPC) scheme is developed to optimize Mi-croCSP electrical and thermal energy flows for HVAC use in a building. Despite its attractiveness regarding energy savings and thermal comfort satisfaction, MPC requires high computational resources and can not be easily implemented on the common low-cost HVAC controllers available in the market. To cope with these issues, two MPC-trained adaptive neuro-fuzzy inference system (ANFIS) models are designed to control the building HVAC with MicroCSP. Simulation results exploiting real operation data from an office building at Michigan Technological University and our newly purchased MicroCSP are presented. It is shown that the resulting controller can reproduce the MPC reasoning and performance while being simpler and much more computationally efficient

Model predictive control of micro-CSP integrated into a building HVAC system for load following demand response programs

Building heat, ventilation and air conditioning (HVAC) systems are good candidates for demand response (DR) programs as they can flexibly alter their consumption to provide ancillary services to the grid and contribute to frequency and voltage regulation. One of the major ancillary services is the load following demand response (DR) program where the demand side tries to track a DR load profile required by the grid. This paper presents a real-time Model Predictive Control (MPC) framework for optimal operations of a micro-scale concentrated solar power (MicroCSP) system integrated into an office building HVAC system providing ancillary services to the grid. To decrease the energy cost of the building, the designed MPC exploits, along with the flexibility of the building’s HVAC system, the dispatching capabilities of the MicroCSP with thermal energy storage (TES) in order to control the power flow in the building and respond to the DR incentives sent by the grid. The results show the effect of incentives in the building participation to the load following DR program in the presence of a MicroCSP system and to what extent this participation is affected by seasonal weather variations and dynamic pricing

Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost

Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost