Potential of a population of domestic heat pumps to provide balancing service

This paper investigates the model of aggregated heat pumps as a source of the flexible load in Great Britain. A thermal model of a domestic heat pump was presented. A decentralised temperature control algorithm was proposed to control the building temperature, and heat pump’s ON and OFF cycles. Seven case studies were used to identify the suitable number of individual heat pump models that can be aggregated to accurately represent the projected number of heat pumps connected to the 2030 GB’s power system. The simulation results revealed that an aggregated model of 5,000 individual heat pumps was accurately representing the entire number of heat pumps in the Great Britain power system. Also, the power consumption of a group of heat pumps was examined in response to the grid frequency. Simulation results showed that the power consumption of aggregated heat pumps was successfully controlled in response to a frequency change. The controlled heat pumps reduced the dependency on the frequency service obtained by expensive peaking generators

Design and implementation of FPGA-based systems - a review

This paper reviews the state of the art of field programmable gate array (FPGA) with the focus on FPGA-based systems. The paper starts with an overview of FPGA in the previous literature, after that starts to get an idea about FPGA programming. FPGA-based neural networks also provided in this paper in order to highlight the best advantage by using FPGA with this type of intelligent systems, and a survey of FPGA-based control systems design with different applications. In this paper, we focus on the main differences between software-based systems with respect to FPGA-based systems, and the main features for FPGA technology and its real-time applications. FPGA-based robotics systems design also provided in this review, finally, the most popular simulation results with FPGA design and implementations are highlighted

Design of fuzzy logic controller for AC motor based on field programmable gate array

This paper presents design of proportional-integral-derivative fuzzy logic controller (PIDFLC) to control the position in AC motor. Fuzzy logic controller has been designed using VHDL language for implementation in field programmable gate array (FPGA). Two version of the controller have been designed, the first one is 6-bits which uses 6-bits for each input/output variables (6FBC), while the second uses 8-bits for each input/output variables (8FBC). Second order mathematical model represents a position control in AC motor has been used in unity feedback control system with the proposed controller. Simulation environments have been built using non-synthesizable VHDL code for the purpose of simulation in ModelSim, and the same design is coded in Matlab for the purpose of simulation in Matlab (MSBC). The Mean differences between MSBC and 6FBC for Step response and control action are -0.0256 and -0.0009 respectively, and The Mean differences between MSBC and 8FBC for Step response and control action are -0.0030 and 0.0021 respectively, since the 8FBC is superior to 6FBC and its much close to MSBC

Developed method of FPGA-based fuzzy logic controller design with the aid of conventional PID algorithm

This paper proposes developed method to design a digital fuzzy logic controller with the aid of conventional Proportional – integral – derivative (PID) controller using field programmable gate array (FPGA). The method used to design a PID Fuzzy Logic controller is to design it as Proportional– derivative Fuzzy Logic controller (PDFLC) and Proportional –integral fuzzy logic controller (PIFLC) connected in parallel through a summer. This method reduces the number of rules needed significantly. To simplify the controller design, we designed the PIFLC by accumulating the output of PDFLC. The contribution in this method are, firstly, to reduce the huge number of fuzzy rules required in the normal design for PIDFLC from 512 rules (in the case of three inputs PIDFLC) to 64 rules (in the case of two inputs PIDFLC). Secondly, to avoid the difficulties to formulate the control rules with the input variable sum-of-error Σe in the case of PIFLC input as its steady-state value is unknown for most control problems. This method also enables us to design the controller to work as PDFLC, PIFLC or PIDFLC depending on two (one-bit) external signals with programmable fuzzy sets and programmable rule table using VHDL language for implementation on FPGA device, and to employ the new technique of fuzzy algorithm in order to serve a wide range of the physical systems which require a real-time operation. From the compilation and timing simulation results, the controller is able to produce a fast response in 20.8 ns with 75.85 MHz of frequency. The time required between validin for the first cycle is 4.423 ns. From analysis and synthesis summary, we got that the design contain of 127 total pins and 215 combinational functions and 215 logic elements. From these specification s and with compare it with other design using software; the controller has the ability to serve a wide range of the physical systems which require a real-time operation

A model reference-based adaptive PSS4B stabilizer for the multi-machines power system

Two-inputs adaptive IEEE multi-bands power system stabilizer (PSS4B) was developed for oscillations damping control in power systems. Two supplementary loops based on model reference (MR) adaptive control were added to the typical PSS4B design. The MR has the same loops’ parameters of the typical PSS4B, and hence, avoiding a complex tuning process. The proposed PSS has a self-tuning gain reduction block to avoid any negative impact due to the high gains value during the disturbance time. The proposed PSS was applied on the four-machine benchmark power system. To evaluate the robustness of the proposed PSS, it was tested in comparison with the Delta W PSS, one-input multi-bands PSS4B (1iMB) and two-inputs multi-bands PSS4B (2iMB) stabilizers. The integration of the proposed PSS was demonstrating using different study cases. These cases consider the small-signal stability (SSS), large-signal stability (LSS) and the coordination test for the local and inter-area excited power modes. The proposed PSS demonstrated robust and superior responses in all cases

Control of a population of battery energy storage systems for frequency response

The control of multiple battery energy storage systems (BESSs) to provide frequency response will be a challenge in future smart grids. This paper proposes a hierarchical control of BESSs with two decision layers: the aggregator layer and the BESS control layer. The aggregator layer receives the states of charge (SoC) of BESSs and sends a command signal to enable/disable the BESS control layer. The BESS controller was developed to enable the BESSs to respond from the highest to lowest SoC when the frequency drops, and from lowest to highest when it rises. Hence, the BESS’s response is prioritised to reduce the impact on the power system and end-users during the service. The BESS controller works independently when a failure occurs in the communication with the aggregator. The dynamic behaviour of the population of the controllable BESSs was modelled based on a Markov chain. The model demonstrates the value of aggregation of BESSs for providing frequency response and evaluates the effective capacity of the service. The model was demonstrated on the 14-machine South-East Australian power system with a 14.5 GW load. 254 MW of responsive capacity of aggregated batteries was effective in reducing the system frequency deviation below 0.2 Hz following a sequence of disturbances

Analysis and performance evaluation of PD-like fuzzy logic controller design based on Matlab and FPGA

This paper presents an analysis and performance evaluation of the proportional-derivative (PD) fuzzy logic controller design by using Matlab and field programmable gate array (FPGA). The fuzzy logic controller consists of a Fuzzifier, inference engine and Defuzzifier; the Fuzzifier block accepts two PD inputs. Two types of controller are designed; the first one is using fuzzy logic toolbox in Matlab. The second type is designed using VHDL language for implementation on FPGA. Mathematical models of robot arm and bench-top helicopter are used for the purpose of simulation with the first type. This controller is used with a unity feedback control system in Matlab Simulink, in order to control these systems and to generate the simulation results. The best response with the robot arm has 0.02 errors and zero overshot, and the best response with the bench-top helicopter has 0.01 error with 0.001 overshot. Altera Quartus II and ModelSim simulation program are used to generate the simulation results of the second type. A mathematical model that represents industrial processes, such as temperature, pressure, pH, and fluid-level controls with unity feedback control systems and subjected to 0.2 step input is used to generate these results. This FPGA-based controller is able to produce a fast response ranging from 0.3 μs, even with time delay added with the plant model

Potential of demand side response aggregation for the stabilization of the grids frequency

The role of ancillary services related to the frequency control have become increasingly important in the smart grids. Demand Side Response is a competitive resource that can be used to regulate the grid frequency. This paper describes the use of heat pumps and fridges to provide ancillary services of frequency response so that to continuously balance the supply with demand. The power consumption of domestic units is usually small and, therefore, the aggregation of large numbers of small units should be able to provide sufficient capacity for frequency response. In this research, dynamic frequency control was developed to evaluate the capacity that can be gathered from the aggregation of domestic heat pumps and fridges for frequency response. The potential of frequency response was estimated at a particular time during winter and summer days. We also investigated the relationship between both loads (domestic heat pumps and fridges) to provide Firm Frequency Response service. A case study on the simplified Great Britain power system model was developed. Based on this case study, three scenarios of load combination were simulated according to the availability of the load and considering cost savings. It was demonstrated that the aggregation of heat pumps and fridges offered large power capacity and, therefore, an instantaneous frequency response service was achievable. Finally, the economic benefit of using an aggregated load for Firm Frequency Response service was estimated

Design of field programmable gate array-based proportional-integral-derivative fuzzy logic controller with tunable ganin

Many of fuzzy control applications require real-time operation; higher density programmable logic devices such as Field Programmable Gate Array (FPGA) can be used to integrate large amounts of logic in a single IC. This thesis presents a design of improved Proportional-Integral-Derivative Fuzzy Logic Controller (PIDFC) with tunable gains method using FPGA. The PIDFC is designed as a PDFC and PIFC connected in parallel through a summer. To simplify the controller design, the PIFC is designed by accumulating the output of the PDFC. The benefits of doing so are twofold, as the number of rules that have to be written is reduced from 512 rules to 64 rules, and depending on two external signals, the controller is able to work as a PDFC, PIFC or PIDFC. The tuning gain block is designed at each input/output stage. This block involves a tuning via scaling the universe of discourse and is able to accept optimal scaling gains. The particle swarm optimization method (PSO) is used to obtain the optimal values of these gains. PIDFC is designed using VHDL language for implementation on FPGA device, and to employ the improved fuzzy algorithm that offer higher processing speed versus low utilization of chip resource. Two versions of the PIDFC are designed; the first one is 8-bits FPGA-based controller (8FBC), while the second one is 6-bits (6FBC) version for each inputs/output variables. To test the design, five case studies are used to test the controller in simulation environments in ModelSim and Matlab. The same design is coded in Matlab environment (MSBC) to enable a comparison with the FPGA-based design (FBC). PIDFC needs 16 clock cycles to complete one action. The simulation results showed that the 8FBC is superior to the 6FBC and its responses are much closer to or better to the MSBC or the results in the literature. 8FBC is able to produce an action in 0.3 μs after input latching with maximum frequency of 40 MHz. Therefore, the PIDFC will be able to control a wide range of the systems with high sampling rate