Electricity prices in a competitive market: a preliminary analysis of the deregulated Thai electricity industry

The electricity industry throughout the world is currently undergoing a significant transition towards restructuring and deregulation. Following this new legislation, Thailand has initiated an institutional and structural reform with a belief that this could be the best way forward for the Thai electricity supply industry (ESI) to improve efficiency, lower electricity prices, and tackle financial debts. This paper presents an analysis of the extent to which prices for generation services in a competitive market may differ from regulated electricity prices, if competitive prices are based on marginal costs and regulated prices are based on average costs, by using Thailand as a case study.     

A simulation model for predicting the performance of a solar photovoltaic system with alternating current loads

This paper describes the development of a simulation model for predicting the performance of a solar photovoltaic (PV) system under specified load requirements and prevailing meteorological conditions at the site location. This study is aimed at situations where the loads are provided by alternating current (AC) electrical devices. The model consists of several submodels for each of the main components of the PV system; namely, PV array, battery, controller, inverter and various loads. Mathematical equations developed for modeling the performance of each component are explained along with the methodology to determine the performance coefficients. In order to validate the developed simulation model, an experimental system has been set up and tested under a variety of climatic conditions. Simulated results from the model under the same operating and environmental conditions are compared with those observed from the experimental tests. Good agreement is found in the comparison. Slight discrepancies appearing in the results are described and recommendations are given for further improvement. The simulation model developed can be used not only for analyzing the PV system performance, but also for sizing the PV system which is most suitable to the load requirements at any specified location provided that the local meteorological data is available.     

Multi-objective optimal power flow considering wind power cost functions using enhanced PSO with chaotic mutation and stochastic weights

Electrical Engineering - A multi-objective optimal power flow (OPF) solution using an enhanced NSPSO, incorporating chaotic mutation and stochastic weight trade-off features, is proposed here. The...     

Augmented Lagrange Hopfield network based Lagrangian relaxation for unit commitment

This paper proposes an augmented Lagrange Hopfield network based Lagrangian relaxation (ALHN-LR) for solving unit commitment (UC) problem with ramp rate constraints. ALHN-LR is a combination of improved Lagrangian relaxation (ILR) and augmented Lagrange Hopfield network (ALHN) enhanced by heuristic search. The proposed ALHN-LR method solves the UC problem in three stages. In the first stage, ILR is used to solve unit scheduling satisfying load demand and spinning reserve constraints neglecting minimum up and down time constraints. In the second stage, heuristic search is applied to refine the obtained unit schedule including primary unit de-commitment, unit substitution, minimum up and down time repairing, and de-commitment of excessive units. In the last stage, ALHN which is a continuous Hopfield network with its energy function based on augmented Lagrangian relaxation is applied to solve constrained economic dispatch (ED) problem and a repairing strategy for ramp rate constraint violations is used if a feasible solution is not found. The proposed ALHN-LR is tested on various systems ranging from 17 to 110 units and obtained results are compared to those from many other methods. Test results indicate that the total production costs obtained by the ALHN-LR method are much less than those from other methods in the literature with a faster manner. Therefore, the proposed ALHN-LR is favorable for large-scale UC implementation.     

Optimal power flow with FACTS devices by hybrid TS/SA approach

In this paper, a hybrid tabu search and simulated annealing (TS/SA) approach is proposed to minimize the generator fuel cost in optimal power flow (OPF) control with flexible AC transmission systems (FACTS) devices. The problem is decomposed into the optimal setting of FACTS parameters subproblem that is searched by the hybrid TS/SA approach and the OPF with fixed FACTS parameters subproblem that is solved by the quadratic programming (QP). Two types of FACTS devices are used: thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifting (TCPS). Test results on the modified IEEE 30 bus system indicates that the proposed hybrid TS/SA approach can obtain better solutions and require less CPU times than genetic algorithm (GA), SA, or TS alone.     

Improved merit order and augmented Lagrange Hopfield network for short term hydrothermal scheduling

This paper proposes an improved merit order (IMO) combined with an augmented Lagrangian Hopfield network (ALHN) for solving short term hydrothermal scheduling (HTS) with pumped-storage hydro plants. The proposed IMO-ALHN consists of a merit order based on the average production cost of generating units enhanced by heuristic search algorithm for finding unit scheduling and a continuous Hopfield neural network with its energy function based on augmented Lagrangian relaxation for solving constrained economic dispatch (CED). The proposed method is applied to solve the HTS problem in five stages including thermal, hydro and pumped-storage unit commitment by IMO and heuristic search, constraint violations repairing by heuristic search and CED by ALHN. The proposed method is tested on the 24-bus IEEE RTS with 32 units including 4 fuel-constrained, 4-hydro, and 2 pumped-storage units scheduled over a 24-h period. Test results indicate that the proposed IMO-ALHN is efficient for hydrothermal systems with various constraints.     

An innovation idea for energy transition towards sustainable and resilient societies:Global energy interconnection

Global Energy Interconnection(hereafter GEI) is not only connectivity of power grid, but also a series of methodical innovations for energy transition towards sustainable and resilient societies,which is different from the traditional energy development mode in the past. This paper seeks to summarize the key features about the abovementioned innovations, as Green Clean, Balanced Reciprocal, Efficient Intelligent and Vitality Business opportunity. Finally it puts forward some reflections on the future development of GEI based on ASEAN practice cases.     

Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network

This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.     

Coordinated fuzzy constrained optimal power dispatch for bilateral contract, balancing electricity, and ancillary services markets

This paper proposes a coordinated fuzzy constrained optimal power dispatch (CFCOPD) algorithm for bilateral contract, balancing electricity, and ancillary services markets. The CFCOPD problem is decomposed into social welfare fuzzy maximization subproblem, which is solved by mixed-integer fuzzy linear programming (MIFLP), and combined reactive power cost and cost of real power loss fuzzy minimization subproblem, which is solved by fuzzy linear programming (FLP). The proposed CFCOPD algorithm is tested on the modified IEEE 30-bus system and the Thai power 424-bus system. The dispatch results show that the social welfare of the fuzzy constrained competitive electricity and ancillary services price (CEASP) scheme with bilateral contract curtailment bids is higher than those of competitive electricity price (CEP) scheme and CEASP scheme with and without bilateral contract curtailment bids, leading to a lower average electricity price.     

Improved merit order and augmented Lagrange Hopfield network for unit commitment

This paper proposes an improved merit order (IMO) and augmented Lagrange Hopfield network (ALHN) for unit commitment (UC). IMO is a merit-order method which is based on average production cost of generating units improved by heuristic search algorithms, whereas ALHN is a continuous Hopfield neural network with its energy function based on augmented Lagrange relaxation. The proposed IMO-ALHN solves UC problem in three stages. In the first stage, IMO is applied for unit scheduling. In the second stage, ALHN is used to solve ramp rate constrained economic dispatch (RED) based on the obtained unit schedule, and a strategy for repairing ramp rate constraint violation is performed if a feasible solution is not found. In the last stage, a heuristic search for unit decommitment is applied on the obtained solution from RED for further improvement and ALHN is again applied to solve RED if there is any change in the unit schedule. The proposed method is tested on systems up to 1000 generating units with schedule time horizon up to 168 h. Test results indicate that the proposed method is very attractive and favourable over many other methods due to substantial production cost savings and faster computational times.