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Dr. Jayakrishnan Radhakrishna Pillai
Department of Energy Engineering, Aalborg University, Aalborg, Denmark

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Research Keywords & Expertise

0 Demand Response
0 Smart Grids
0 Multicarrier energy systems
0 Grid integration of distributed energy systems
0 Electric distribution systems

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Journal article
Published: 09 June 2021 in Energies
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Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy.

ACS Style

Dawid Jozwiak; Jayakrishnan Pillai; Pavani Ponnaganti; Birgitte Bak-Jensen; Jan Jantzen. Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems. Energies 2021, 14, 3397 .

AMA Style

Dawid Jozwiak, Jayakrishnan Pillai, Pavani Ponnaganti, Birgitte Bak-Jensen, Jan Jantzen. Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems. Energies. 2021; 14 (12):3397.

Chicago/Turabian Style

Dawid Jozwiak; Jayakrishnan Pillai; Pavani Ponnaganti; Birgitte Bak-Jensen; Jan Jantzen. 2021. "Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems." Energies 14, no. 12: 3397.

Journal article
Published: 27 December 2020 in Applied Sciences
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Integration of PV power generation systems at distribution grids, especially at low-voltage (LV) grids, brings in operational challenges for distribution system operators (DSOs). These challenges include grid over-voltages and overloading of cables during peak PV power production. Battery energy storage systems (BESS) are being installed alongside PV systems by customers for smart home energy management. This paper investigates the utilization of those BESS by DSOs for maintaining the grid voltages within limits. In this context, an incentive price based demand response (IDR) method is proposed for indirect control of charging/discharging power of the BESS according to the grid voltage conditions. It is shown that the proposed IDR method, which relies on a distributed computing application, is able to maintain the grid voltages within limits. The advantage of the proposed distributed implementation is that the DSOs can compute and communicate the incentive prices thereby encouraging customers to actively participate in the demand response program. An iterative distributed algorithm is used to compute the incentive prices of individual BESS to minimize the costs of net power consumption of the customer. The proposed IDR method is tested by conducting simulation studies on the model of a Danish LV grid for few study cases. The simulation results show that by using the proposed method for the control of BESS, node voltages are maintained within limits as well as the costs of net power consumption of BESS owners are minimized.

ACS Style

Karthikeyan Nainar; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen. Incentive Price-Based Demand Response in Active Distribution Grids. Applied Sciences 2020, 11, 180 .

AMA Style

Karthikeyan Nainar, Jayakrishnan Radhakrishna Pillai, Birgitte Bak-Jensen. Incentive Price-Based Demand Response in Active Distribution Grids. Applied Sciences. 2020; 11 (1):180.

Chicago/Turabian Style

Karthikeyan Nainar; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen. 2020. "Incentive Price-Based Demand Response in Active Distribution Grids." Applied Sciences 11, no. 1: 180.

Journal article
Published: 21 April 2020 in IEEE Access
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The daily load profiles modeling is of great significance for the economic operation and stability analysis of the distribution network. In this paper, a flow-based generative network is proposed to model daily load profiles of the distribution network. Firstly, the real samples are used to train a series of reversible functions that map the probability distribution of real samples to the prior distribution. Then, the new daily load profiles are generated by taking the random number obeying the Gaussian distribution as the input data of these reversible functions. Compared with existing methods such as explicit density models, the proposed approach does not need to assume the probability distribution of real samples, and can be used to model different loads only by adjusting the structure and parameters. The simulation results show that the proposed approach not only fits the probability distribution of real samples well, but also accurately captures the spatial-temporal correlation of daily load profiles. The daily load profiles with specific characteristics can be obtained by simply classification.

ACS Style

Leijiao Ge; Wenlong Liao; Shouxiang Wang; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai. Modeling Daily Load Profiles of Distribution Network for Scenario Generation Using Flow-Based Generative Network. IEEE Access 2020, 8, 77587 -77597.

AMA Style

Leijiao Ge, Wenlong Liao, Shouxiang Wang, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai. Modeling Daily Load Profiles of Distribution Network for Scenario Generation Using Flow-Based Generative Network. IEEE Access. 2020; 8 (99):77587-77597.

Chicago/Turabian Style

Leijiao Ge; Wenlong Liao; Shouxiang Wang; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai. 2020. "Modeling Daily Load Profiles of Distribution Network for Scenario Generation Using Flow-Based Generative Network." IEEE Access 8, no. 99: 77587-77597.

Journal article
Published: 11 April 2020 in International Journal of Electrical Power & Energy Systems
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The decentralised infrastructure of the Danish thermal and electricity infrastructure has improved security, efficiency and reliability in energy transmission and consumption in each of the systems. To further improve this trend, this paper investigates the concept of decentralised coupling of electrified thermal and transportation system in low voltage residential network to identify their operational flexibility. In this paper, diagnosis based on actual data from the energy distributors and surveys is used to understand and improve the flexibility of an integrated energy system. The main contribution is a set up model with an autonomous control system that can assess the potential flexibility from thermal units (eg heat pumps and storages) and electric vehicles (EV) charging systems, in the low voltage distribution network as a multi-energy system. Each thermal system and EV charging has its respective individual controller. The proposed control technique manages to successfully operate and control the thermal units and EVs charging system within the recommended operating limits of grid voltage, and by sharing flexibility within the specific network integrated with multi-carrier energy systems. It has the capability of sensing local key control parameters like node voltage, state of charge of EV, temperature and level of hot water in the storage tank. These control parameters allow scheduling, re-scheduling, and decision making on the operation of individual thermal and EV charging-unit with operational priorities. This enhances the sharing of flexibility for proper coordination, control, and management of thermal and EV charging systems in low voltage (LV) distribution networks with mutual technical benefits. From the results of the steady-state analysis of power system, the application of the proposed control architecture is found to be effective to manage grid congestions and local voltage control, satisfying the thermal energy requirements of the customer as well as charging needs of EV.

ACS Style

Rakesh Sinha; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai. Operational flexibility of electrified transport and thermal units in distribution grid. International Journal of Electrical Power & Energy Systems 2020, 121, 106029 .

AMA Style

Rakesh Sinha, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai. Operational flexibility of electrified transport and thermal units in distribution grid. International Journal of Electrical Power & Energy Systems. 2020; 121 ():106029.

Chicago/Turabian Style

Rakesh Sinha; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai. 2020. "Operational flexibility of electrified transport and thermal units in distribution grid." International Journal of Electrical Power & Energy Systems 121, no. : 106029.

Journal article
Published: 24 December 2019 in Energies
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Active use of heat accumulators in the thermal system has the potential for achieving flexibility in district heating with the power to heat (P2H) units, such as electric boilers (EB) and heat pumps. Thermal storage tanks can decouple demand and generation, enhancing accommodation of sustainable energy sources such as solar and wind. The overview of flexibility, using EB and storage, supported by investigating the nature of thermal demand in a Danish residential area, is presented in this paper. Based on the analysis, curve-fitting tools, such as neural net and similar day method, are trained to estimate the residential thermal demand. Utilizing the estimated demand and hourly market spot price of electricity, the operation of the EB is scheduled for storing and fulfilling demand and minimizing energy cost simultaneously. This demonstrates flexibility and controlling the EB integrated into a multi-energy system framework. Results show that the curve fitting tool is effectively suitable to acknowledge thermal demands of residential area based on the environmental factor as well as user behaviour. The thermal storage has the capability of operating as a flexible load to support P2H system as well as minimize the effect of estimation error in fulfilling actual thermal demand simultaneously.

ACS Style

Rakesh Sinha; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai; Hamidreza Zareipour. Flexibility from Electric Boiler and Thermal Storage for Multi Energy System Interaction. Energies 2019, 13, 98 .

AMA Style

Rakesh Sinha, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai, Hamidreza Zareipour. Flexibility from Electric Boiler and Thermal Storage for Multi Energy System Interaction. Energies. 2019; 13 (1):98.

Chicago/Turabian Style

Rakesh Sinha; Birgitte Bak-Jensen; Jayakrishnan Radhakrishna Pillai; Hamidreza Zareipour. 2019. "Flexibility from Electric Boiler and Thermal Storage for Multi Energy System Interaction." Energies 13, no. 1: 98.

Journal article
Published: 04 November 2019 in Smart Cities
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The smart active residential buildings play a vital role to realize intelligent energy systems by harnessing energy flexibility from loads and storage units. This is imperative to integrate higher proportions of variable renewable energy generation and implement economically attractive demand-side participation schemes. The purpose of this paper is to develop an energy management scheme for smart sustainable buildings and analyze its efficacy when subjected to variable generation, energy storage management, and flexible demand control. This work estimate the flexibility range that can be reached utilizing deferrable/controllable energy system units such as heat pump (HP) in combination with on-site renewable energy sources (RESs), namely photovoltaic (PV) panels and wind turbine (WT), and in-house thermal and electric energy storages, namely hot water storage tank (HWST) and electric battery as back up units. A detailed HP model in combination with the storage tank is developed that accounts for thermal comforts and requirements, and defrost mode. Data analytics is applied to generate demand and generation profiles, and a hybrid energy management and a HP control algorithm is developed in this work. This is to integrate all active components of a building within a single complex-set of energy management solution to be able to apply demand response (DR) signals, as well as to execute all necessary computation and evaluation. Different capacity scenarios of the HWST and battery are used to prioritize the maximum use of renewable energy and consumer comfort preferences. A flexibility range of 22.3% is achieved for the scenario with the largest HWST considered without a battery, while 10.1% in the worst-case scenario with the smallest HWST considered and the largest battery. The results show that the active management and scheduling scheme developed to combine and prioritize thermal, electrical and storage units in buildings is essential to be studied to demonstrate the adequacy of sustainable energy buildings.

ACS Style

Viktor Stepaniuk; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen; Sanjeevikumar Padmanaban. Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building. Smart Cities 2019, 2, 471 -495.

AMA Style

Viktor Stepaniuk, Jayakrishnan Radhakrishna Pillai, Birgitte Bak-Jensen, Sanjeevikumar Padmanaban. Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building. Smart Cities. 2019; 2 (4):471-495.

Chicago/Turabian Style

Viktor Stepaniuk; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen; Sanjeevikumar Padmanaban. 2019. "Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building." Smart Cities 2, no. 4: 471-495.

Journal article
Published: 12 June 2019 in Energies
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This paper presents a unique integrated approach to meter placement and state estimation to ensure the network observability of active distribution systems. It includes observability checking, minimum measurement utilization, network state estimation, and trade-off evaluation between the number of real measurements used and the accuracy of the estimated state. In network parameter estimation, observability assessment is a preliminary task. It is handled by data analysis and filtering followed by calculation of the triangular factors of the singular, symmetric gain matrix using an algebraic method. Usually, to cover the deficiency of essential real measurements in distribution systems, huge numbers of virtual measurements are used. These pseudo measurements are calculated values, which are based on the network parameters, real measurements, and forecasted load/generation. Due to the application of a huge number of pseudo-measurements, large margins of error exists in the calculation phase. Therefore, there is still a high possibility of having large errors in estimated states, even though the network is classified as being observable. Hence, an integrated approach supported by forecasting is introduced in this work to overcome this critical issue. Finally, estimation of the trade-off in accuracy with respect to the number of real measurements used has been evaluated in order to justify the method’s practical application. The proposed method is applied to a Danish network, and the results are discussed.

ACS Style

Basanta Raj Pokhrel; Birgitte Bak-Jensen; Jayakrishnan R. Pillai. Integrated Approach for Network Observability and State Estimation in Active Distribution Grid. Energies 2019, 12, 2230 .

AMA Style

Basanta Raj Pokhrel, Birgitte Bak-Jensen, Jayakrishnan R. Pillai. Integrated Approach for Network Observability and State Estimation in Active Distribution Grid. Energies. 2019; 12 (12):2230.

Chicago/Turabian Style

Basanta Raj Pokhrel; Birgitte Bak-Jensen; Jayakrishnan R. Pillai. 2019. "Integrated Approach for Network Observability and State Estimation in Active Distribution Grid." Energies 12, no. 12: 2230.

Journal article
Published: 21 February 2019 in IEEE Transactions on Industrial Electronics
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This paper proposes a novel structure for Industrial Demand Response Aggregators (IDRA) to provide operational flexibility for the power system. A robust self-scheduling approach is formulated for the first time to optimize different sub-processes of the whole production line of heavy industries. The new approach satisfies the customer order with the lowest energy cost. Numerical studies are implemented on 8 integrated cement factories, from Khorasan Regional Electric Company (KREC), in the east of Iran. The results show that the integrated model of heavy industries provides guaranteed flexibility to the system when a power shortage occurs or system reliability is jeopardized.

ACS Style

Hessam Golmohamadi; Reza Keypour; Birgitte Bak-Jensen; Jayakrishnan R. Pillai; Mohammad Hassan Khooban. Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators. IEEE Transactions on Industrial Electronics 2019, 67, 1387 -1395.

AMA Style

Hessam Golmohamadi, Reza Keypour, Birgitte Bak-Jensen, Jayakrishnan R. Pillai, Mohammad Hassan Khooban. Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators. IEEE Transactions on Industrial Electronics. 2019; 67 (2):1387-1395.

Chicago/Turabian Style

Hessam Golmohamadi; Reza Keypour; Birgitte Bak-Jensen; Jayakrishnan R. Pillai; Mohammad Hassan Khooban. 2019. "Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators." IEEE Transactions on Industrial Electronics 67, no. 2: 1387-1395.

Journal article
Published: 11 February 2019 in IEEE Transactions on Power Systems
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In this paper, a model-based predictive control method is proposed for utilization of flexible resources such as battery energy storage systems and heating systems effectively to provide demand response in low-voltage distribution networks with solar PV. The contributions of this paper are twofold. Firstly, a linear power flow method based on relaxation of branch power losses applicable to radial distribution networks is proposed and formulated. Secondly, a flexible resources controller which solves a multi-objective linear optimization problem in recedinghorizon fashion is formulated taking into account system states, forecasts of generation and loads. Using the proposed control algorithm, flexibility from network resources can be utilized for low-voltage network management with assurance of quality of service to the customers. Simulations are conducted for summer and winter cases on a simplified Danish low-voltage network using Matlab/Simulink to study the performance of the proposed control method. Compared to the methods in state of the art, the proposed linear power flow method is proven to be accurate for the calculation of network power flows. Simulation results also show that proposed flexible resources controller can meet the network control objectives while satisfying the network constraints and operation limits of the flexible resources.

ACS Style

Nainar Karthikeyan; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen; John William Simpson-Porco. Predictive Control of Flexible Resources for Demand Response in Active Distribution Networks. IEEE Transactions on Power Systems 2019, 34, 2957 -2969.

AMA Style

Nainar Karthikeyan, Jayakrishnan Radhakrishna Pillai, Birgitte Bak-Jensen, John William Simpson-Porco. Predictive Control of Flexible Resources for Demand Response in Active Distribution Networks. IEEE Transactions on Power Systems. 2019; 34 (4):2957-2969.

Chicago/Turabian Style

Nainar Karthikeyan; Jayakrishnan Radhakrishna Pillai; Birgitte Bak-Jensen; John William Simpson-Porco. 2019. "Predictive Control of Flexible Resources for Demand Response in Active Distribution Networks." IEEE Transactions on Power Systems 34, no. 4: 2957-2969.

Journal article
Published: 19 November 2016 in Energies
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As a long term bidding behavior, bid shading is exhibited by wind farms participating in real Uniform Price (UP) markets. This signifies that the wind farm owners bid far below their true long run marginal cost. In this paper, a method is proposed to consider the uncertainty of bidding admission in the long term expected revenue of wind farms. We show that this consideration could perfectly explain the observed bid shading behavior of wind farm owners. We use a novel market price model with a stochastic model of a wind farm to derive indices describing the uncertainty of bidding admission. The optimal behavior of the wind farm is then obtained by establishing a multi objective optimization problem and subsequently solved using genetic algorithm. The method is applied to the analysis of long term bidding behavior of a wind farm participating in a Pay-as-Bid (PAB) auction such as Iran Electricity Market (IEM). The results demonstrate that wind farm owners change their bid shading behavior in a PAB Auction. However, the expected revenue of the wind farm will also decrease in a PAB auction. As a result, it is not recommended to make an obligation for the wind farms to participate in a PAB auction as a normal market player.

ACS Style

Mazaher Haji Bashi; Gholamreza Yousefi; Claus Leth Bak; Jayakrishnan Radhakrishna Pillai. Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty. Energies 2016, 9, 945 .

AMA Style

Mazaher Haji Bashi, Gholamreza Yousefi, Claus Leth Bak, Jayakrishnan Radhakrishna Pillai. Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty. Energies. 2016; 9 (11):945.

Chicago/Turabian Style

Mazaher Haji Bashi; Gholamreza Yousefi; Claus Leth Bak; Jayakrishnan Radhakrishna Pillai. 2016. "Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty." Energies 9, no. 11: 945.