A review of co-optimization approaches for operational and planning problems in the energy sector

This paper contributes to a comprehensive perspective on the application of co-optimization in the energy sector – tracking the frontiers and trends in the field and identifying possible research gaps – based on a systematic literature review of 211 related studies. The use of co-optimization is addressed from a variety of perspectives by splitting the studies into ten key categories. Research has consistently shown that co-optimization approaches can be technically challenging and it is usually a data-intensive procedure. Overall, a set of techniques such as relaxation, decomposition and linear approaches have been proposed for reducing the inherent nonlinear model's complexities. The need to coordinate the necessary data from multiples actors might increase the complexity of the problem since security and confidentiality issues would also be put on the table. The evidence from our review seems to suggest a pertinent role for addressing real-case systems in future models instead of using theoretical test cases as considered by most studies. The identified challenges for future co-optimization models include (i) dealing with the treatment of uncertainties and (ii) take into account the trade-offs among modelling fidelity, spatial granularity and geographical coverage. Although there is also a growing body of literature that recognizes the importance of co-optimization focused on integrating supply and demand-side options, there has been little work in the development of co-optimization models for long-term decision-making, intending to recognize the impact of short-term variability of both demand and RES supply and well suited to systems with a high share of RES and under different demand flexibility conditions. The research results represent a further step towards the importance of developing more comprehensive approaches for integrating short-term constraints in future co-optimized planning models. The findings provide a solid evidence base for the multi-dimensionality of the co-optimization problems and contriThis work is supported by the National Council for Scientific and Technological Development (CNPq), Brazil. This work has been supported by FCT – Fundaça˜o para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Transmission congestion management by optimal placement of FACTS devices

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 13/09/2010.This thesis describes the implementation of the Flexible AC Transmission Systems (FACTS) devices to develop a market-based approach to the problem of transmission congestion management in a Balancing Market. The causes, remedies and pricing methods of transmission congestion are briefly reviewed. Balancing Market exists in markets in which most of the trading is done via decentralized bilateral contracts. In these markets only final adjustments necessary to ensure secure system operation is carried out at a centralized Balancing Market. Each market player can participate in the Balancing Market by submitting offers and bids to increase and decrease its initially submitted active generation output. In this research a method is proposed to reduce costs associated with congestion re-dispatch in a Balancing Market by optimal placement of FACTS devices, and in particular Thyristor Controlled Phase Shifter Transformers (TCPST). The proposed technique is applicable to both Mixed Integer Linear Programming (MILP) and Mixed Integer Non-Linear Programming (MINLP). In the MILP a power system network is represented by a simplified DC power flow under a MILP structure and the Market participants' offers and bids are also represented by linear models. Results show that applications of FACTS devices can significantly reduce costs of congestion re-dispatch. The application of the method based on the MINLP creates a nonlinear and non-convex AC OPF problem that might be trapped in local sub-optima solutions. The reliability of the solution that determines the optimal placement of FACTS devices is an important issue and is carried out by investigation of alternative solvers. The behavior of the MINLP solvers is presented and finally the best solvers for this particular optimization problem are introduced. The application of DC OPF is very common in industry. The accuracy of the DC OPF results is investigated and a comparison between the DC and AC OPF is presented

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

Impact of optimally placed VAR support on electricity spot pricing

In view of deregulation and privatization processes, electricity pricing becomes one of the most important issues. The increases in power flows and environmental constraints are forcing electricity utilities to install new VAR equipment to enhance network operation. In this thesis a nonlinear multi-objective optimization problem has been formulated to maximize both social welfare and the maximum distance to collapse point in an open power market using reactive support like Static Var Compensator (SVC). The production and consumption costs of reactive power are intended to provide proper market signals to the electricity market agents. They are included in the multi-objective Optimal Power Flow (OPF) coupled with an (N-1) contingency criterion which is based on power flow sensitivity analysis.;Considering the cost associated with the investment of VAR support, placing them at the optimal location in the network is an important issue. An index to find the optimal site for VAR support considering various technical and economical parameters based on Cost Benefit Analysis (CBA) is proposed. The weights for these parameters are computed through an Analytic Hierarchy Process (AHP). A new approach of transmission pricing calculation taking VSC-OPF based multi-objective maximization as the objective and studied the impact of SVC on it. The integrated approach is illustrated on a 6-bus and a standard IEEE 14-bus test systems and shows promising results

Optimal coordination of energy sources for microgrid incorporating concepts of locational marginal pricing and energy storage

This research aims to coordinate energy sources for standalone microgrid (MG), incorporating locational marginal pricing (LMP) and energy storage. Two approaches are suggested for the optimal energy management of MG. First, the energy management of a standalone MG is performed utilising the concept of LMP. The objective is to minimise the average LMP to reduce network congestion and power loss costs. Second, energy management is performed using a dual-stage energy management approach. A BESS model is formulated considering charging and discharging characteristics and utilised in this research for dual-stage energy management. The impact of the battery state of charge (SOC) is assessed in the optimal day-ahead operation. An incremental cost factor is included with battery SOC when calculating the system operating cost. A new binary jellyfish search algorithm (BJSA) is developed to solve energy management problems. The suggested BJSA technique is implemented in solving the optimal energy management of MG considering LMP. The simulations of the suggested approach are conducted on the IEEE 14 and 30-bus test systems. Results show that the BJSA technique is more consistent than the binary particle swarm optimisation (BPSO) technique in determining the optimal solution. In addition, the BJSA technique is employed to solve the dual-stage energy management of MG considering BESS. The proposed approach is simulated on the IEEE 14 and 30-bus systems. Results also show that the BJSA technique is superior to the BPSO technique in minimising the operating cost in real-time economic dispatch (ED). The performance of the BJSA and BPSO techniques is exactly similar to the UC schedule with and without BESS considering the IEEE 30-bus system, like the IEEE 14-bus system. The BJSA technique minimises operating costs by up to 5% over the BPSO technique for the UC schedule with power loss. Operating costs are reduced by up to 5% using the BJSA technique rather than the BPSO technique for real-time ED with BESS. However, the BPSO technique is inconsistent and fails to obtain the same results for the IEEE 30-bus system. Overall, the findings confirm the superiority of the suggested BJSA technique and the suggested optimisation approaches in optimising the energy management of MG

Distribution Network Operation with High Penetration of Renewable Energy Sources. Joint Active/Reactive Power Procurement: A Market-Based Approach for Operation of Distribution Network

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.Ministry of Higher Education and Scientific Research - IraqThe selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright

Transmission congestion management by optimal placement of FACTS devices

This thesis describes the implementation of the Flexible AC Transmission Systems (FACTS) devices to develop a market-based approach to the problem of transmission congestion management in a Balancing Market. The causes, remedies and pricing methods of transmission congestion are briefly reviewed. Balancing Market exists in markets in which most of the trading is done via decentralized bilateral contracts. In these markets only final adjustments necessary to ensure secure system operation is carried out at a centralized Balancing Market. Each market player can participate in the Balancing Market by submitting offers and bids to increase and decrease its initially submitted active generation output. In this research a method is proposed to reduce costs associated with congestion re-dispatch in a Balancing Market by optimal placement of FACTS devices, and in particular Thyristor Controlled Phase Shifter Transformers (TCPST). The proposed technique is applicable to both Mixed Integer Linear Programming (MILP) and Mixed Integer Non-Linear Programming (MINLP). In the MILP a power system network is represented by a simplified DC power flow under a MILP structure and the Market participants' offers and bids are also represented by linear models. Results show that applications of FACTS devices can significantly reduce costs of congestion re-dispatch. The application of the method based on the MINLP creates a nonlinear and non-convex AC OPF problem that might be trapped in local sub-optima solutions. The reliability of the solution that determines the optimal placement of FACTS devices is an important issue and is carried out by investigation of alternative solvers. The behavior of the MINLP solvers is presented and finally the best solvers for this particular optimization problem are introduced. The application of DC OPF is very common in industry. The accuracy of the DC OPF results is investigated and a comparison between the DC and AC OPF is presented.EThOS - Electronic Theses Online ServiceGBUnited Kingdo